Cake International 2019 at the NEC. 01 Nov 2019, 11:11 by Marcus Queenborough, https://www.birminghammail.co.uk/authors/marcus-queenborough/ Tuba Geckil adding the finishing touches to her life-size creation of Villanelle from BBC drama 'Killing Eve', on display during Cake International. (Image: PA)1 of 18 Life-sized lorek the Armoured Bear from 'His Dark Materials', on display during Cake International. (Image: PA)2 of 18 A cake depicting US President Donald Trump and North Korea leader Kim Jong-un on display during Cake International. (Image: PA)3 of 18 Entries in the Pushing the Boundaries category on display during Cake International. (Image: PA)4 of 18 Entries on display during Cake International 2019 at the NEC. (Image: PA)5 of 18 Entries on display during Cake International 2019 at the NEC. (Image: PA)6 of 18 A visitor looks at wedding cakes on display during Cake International 2019 at the NEC. (Image: PA)7 of 18 A Wizard of Oz creation on display during Cake International. (Image: PA)8 of 18 Judges inspect wedding cakes on display during Cake International. (Image: PA)9 of 18 Comedian Rhod Gilbert delivering his creation during Cake International 2019 at the NEC. (Image: PA)10 of 18 The Incredible Indian welcome showpiece on display during Cake International. (Image: PA)11 of 18 Visitors take photographs of entries on display during Cake International 2019. (Image: PA)12 of 18 Competitors add the finishing touches to their creations during Cake International. (Image: PA)13 of 18 Judges make their way around Cake International 2019 at the NEC. (Image: PA)14 of 18 Tuba Geckil adding the finishing touches to her life-size creation of Villanelle from BBC drama 'Killing Eve'. (Image: PA)15 of 18 Life-sized lorek the Armoured Bear from 'His Dark Materials', on display during Cake International. (Image: PA)16 of 18 Cakes, including a 'Predator' entry, competing in the Pushing the Boundaries category at Cake International. (Image: PA)17 of 18 Comedian Rhod Gilbert delivering his creation during Cake International 2019 at the NEC. (Image: PA)18 of 18


Buttons
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Rhydderch Hael
The Radiation King
Registered: Oct 2001
Location: On station at a distant underground nuclear missile silo...
Posts: 1816 |
Elfin magic. Elves made the iris, so it's indestrooctible!
Actually, the going theory is that the iris, being situated so close to the emitting fields of the Stargate, prevent that overpressure wave from forming in the first place, and it is the movement of that wave that would disintegrate matter.
Akin to the waterhead behind a dam. Given enough room to accelerate and attain momentum, the mass of water in a reservoir could easily smash the dam and everything downriver of it—but only if it is given enough room to accelerate in the first place...
__________________
Dogs rock.
Last edited by Rhydderch Hael on 12-19-2002 at 06:50 PM
Report this post to a moderator | ? + *
|


ABOUT
zhu yu
#codeyu #jurik
I am a passionate about computers and problem solving.
My interests include Algos & DS, Mathematics, Puzzles, ...
And want to make my career as a data scientist.
Learn anything from anyone – anywhere, love opensource.
Don't fear, don't regret!
Specialties:
- Languages: CSharp, Golang, Python, JS, Lua, Java, C
- Framework: ASP.NET Core, WPF, Spring boot, Node.js, Electron, Flask, OpenResty, Odoo
- SQL: MySQL, PostgreSQL, Sqlite
- NoSQL: MongoDB, Cassandra, Redis, CouchDB, HBase
- Message queues: RabbitMQ, Kafka, NSQ
- Full text search: Elasticsearch
- Others: Microservices, Docker, Bigdata, Web crawling, Distributed system, Machine learning


Get to know us
Joepeter Engineering is a unique electrical company dedicated to offering professional electrical services.
We have a unique approach that builds long-term relationships with our customers, based on our values of oopen and honest communication, collaborative working, professional delivery, complete client satisfaction and a total commitment to quality.
Featured Services
Quality of service is our priority. We make sure you get the best for your budget. See some of our services below
Engineering & Design-Acoustics
Joepeter Engineering offers Acoustic analysis which address severe structural vibration and fatigue problems in a coupled fluid-structure system.
Learn more
ROBOTICS & CONTROL STRUCTURE INTERACTION
Our robotics & control group's multidisciplinary approach supports industrial customers as well as technology research and development.
Learn more
KINEMATIC & MULTIBODY DYNAMICS
We offer Kinematic analysis and accurate modeling of multibody interaction that are critical to understanding mechanism performance.
Learn more
THERMAL & AEROTHERMAL
Call on our experience in thermal analysis of aerospace and electronic systems and applying thermal loads to structural analysis models.
Learn more
AEROELASTICITY & FLUTTER
Our turnkey certification service connects you with a designated engineering representative (DER) for a more efficient FAA certification process.
Learn more
CFD & FSI
As part of our engineering analysis services, Joepeter Engineering also conducta CFD and FSI analyses for aerospace and industrial customers.
Learn more
Why choose us
Electrical Installations
Our highly skilled and experienced electrical contractors offer complete electrical engineering solutions across Africa and beyond
Control Panels & Switchgears
We manufacture bespoke Electrical and Pneumatic Control panels in our own workshops
Systems Design
Getting the design of the system right is crucial in delivering a product that fulfils both market and functional requirements. With our experience of both hardware and software we can make sure the right choices are made on the functional split of the system, alongside the correct choice of components and modules, and the interface between them. When combined this enables us to realise a solution that meets or exceeds the needs of both engineering and marketing.
Our recent work
Check out our portfolio
Testimonies from our clients
Joepeter Engineering are professional in are professionals in electrical and mechanical works.
Josh Elemand
Warri, Nigeria
Joepeter Engineering are professional in are professionals in electrical and mechanical works.
Josh Elemand
Joepeter Engineering are professional in are professionals in electrical and mechanical works.
Josh Elemand
Joepeter Engineering are professional in are professionals in electrical and mechanical works.
Josh Elemand


A refreshing JavaScript Timepicker base on Datepicker — lightweight, no dependencies, modular CSS.
a Timepicker base on Datepicker!
Youngs Luo


{% extends "simple.html" %} {% block head %} {% endblock %} {% block body %}
Autorunning the Reflow tests ...
Please wait while until all the tests are completed. At the end, your results will be sent back and automatically incorporated into the public result set.
{% if test %} Learn more about the {{ test.name }} test. {% else %} Clicking the button will run each of the reflow tests on the thick-bordered element below. {% endif %}
{% endif %}


【免责声明】本文仅代表作者本人观点，与本网站无关。本网站对文中陈述、观点判断保持中立，不对所包含内容的准确性、可靠性或完整性提供任何明示或暗示的保证。本文仅供读者参考，由此产生的所有法律责任均由读者本人承担。
[Disclaimer] This article only represents the author's opinions, and is irrelevant to this website. This website is neutral in terms of the statements and opinions in this article, and does not provide any express or implied warranty of accuracy, reliability, or completeness of the contents contained therein. This article is for readers' reference only, and all legal responsibilities arising therefrom are borne by the reader himself.


pacat(1) pacat(1) NAME pacat - Play back or record raw or encoded audio streams on a PulseAudio sound server SYNOPSIS paplay [options] [FILE] parecord [options] [FILE] pacat [options] [FILE] parec [options] [FILE] pamon [options] [FILE] pacat --help pacat --version DESCRIPTION pacat is a simple tool for playing back or capturing raw or encoded audio files on a PulseAudio sound server. OPTIONS -h | --help Show help. --version Show version information. -r | --record Capture audio data and write it to the specified file or to STDOUT if none is specified. If the tool is called under the name parec this is the default. -p | --playback Read audio data from the specified file or STDIN if none is speci‐ fied, and play it back. If the tool is called under the name pacat this is the default. -v | --verbose Enable verbose operation. Dumps the current playback time to STDERR during playback/capturing. -s | --server=SERVER Choose the server to connect to. -d | --device=SINKORSOURCE Specify the symbolic name of the sink/source to play/record this stream on/from. -n | --client-name=NAME Specify the client name paplay shall pass to the server when con‐ necting. --stream-name=NAME Specify the stream name paplay shall pass to the server when cre‐ ating the stream. --volume=VOLUME Specify the initial playback volume to use. Choose a value between 0 (silent) and 65536 (100% volume). --rate=SAMPLERATE Capture or play back audio with the specified sample rate. Defaults to 44100 Hz. --format=FORMAT Capture or play back audio with the specified sample format. Spec‐ ify one of u8, s16le, s16be, s32le, s32be, float32le, float32be, ulaw, alaw, s32le, s32be, s24le, s24be, s24-32le, s24-32be. Depending on the endianness of the CPU the formats s16ne, s16re, s32ne, s32re, float32ne, float32re, s32ne, s32re, s24ne, s24re, s24-32ne, s24-32re (for native, resp. reverse endian) are avail‐ able as aliases. Defaults to s16ne. --channels=CHANNELS Capture or play back audio with the specified number of channels. If more than two channels are used it is recommended to use the --channel-map option below. Defaults to 2. --channel-map=CHANNELMAP Explicitly choose a channel map when playing back this stream. The argument should be a comma separated list of channel names: front- left, front-right, mono, front-center, rear-left, rear-right, rear-center, lfe, front-left-of-center, front-right-of-center, side-left, side-right, top-center, top-front-center, top-front- left, top-front-right, top-rear-left, top-rear-right, top-rear- center, or any of the 32 auxiliary channel names aux0 to aux31. --fix-format If passed, the sample format of the stream is changed to the native format of the sink the stream is connected to. --fix-rate If passed, the sampling rate of the stream is changed to the native rate of the sink the stream is connected to. --fix-channels If passed, the number of channels and the channel map of the stream is changed to the native number of channels and the native channel map of the sink the stream is connected to. --no-remix Never upmix or downmix channels. --no-remap Never remap channels. Instead of mapping channels by their name this will match them solely by their index/order. --latency=BYTES Explicitly configure the latency, with a time specified in bytes in the selected sample format. If left out the server will pick the latency, usually relatively high for power saving reasons. Use either this option or --latency-msec, but not both. --latency-msec=MSEC Explicitly configure the latency, with a time specified in miliseconds. If left out the server will pick the latency, usually relatively high for power saving reasons. Use either this option or --latency, but not both. --process-time=BYTES Explicitly configure the process time, with a time specified in bytes in the selected sample format. If left out the server will pick the process time. Use either this option or --process-time- msec, but not both. --process-time-msec=MSEC Explicitly configure the process time, with a time specified in miliseconds. If left out the server will pick the process time. Use either this option or --process-time, but not both. --property=PROPERTY=VALUE Attach a property to the client and stream. May be used multiple times --raw Play/record raw audio data. This is the default if this program is invoked as pacat , parec or pamon --file-format[=FFORMAT] Play/record encoded audio data in the file format specified. This is the default if this program is invoked as paplay and parecord --list-file-formats List supported file formats. AUTHORS The PulseAudio Developers <pulseaudio-discuss (at) lists (dot) freedesk‐ top (dot) org>; PulseAudio is available from http://pulseaudio.org/ SEE ALSO pulseaudio(1), pactl(1) Manuals User pacat(1)


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Français Video, links, etc
Home
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Sunday, April 3, 2011An evening of New England contradances |
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CrowfootAdam Broome (guitar)Jaige Trudel (fiddle) Nicholas Williams (flutes, accordion)
"These three are wicked musicians ...
electrifying ... If this trio is playing
a dance or a festival anywhere near you, be there!" — Sing Out
"Lovely, powerful, danceable
"Their magical sound is spontaneous
and heart-stirring, an inspiration
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and |
Nils FredlandOne of the busiest and most sought-after artists in the field of traditional music and dance. Read about him by downloading the profile of him published in the newsletter of the Country Dance and Song Society: Part 1, Part 2. |
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at the |
Ukrainian Hall405 Fairmount W(at Hutchison) Montreal, H2V 4B4, Map |
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6.30 pm to 10 pm |
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| Regular: | $13 (Suggested: $15) | ||
| Students: | $9 (Suggested: $10) | ||
| First-timers: | Half price |


>
The concept of a self-contained, connected and easily portable device has been with us since the dawn of science fiction. When analysts and bloggers look at the future of computing, mobile or otherwise, they often focus on hardware developments.
Whether their enthusiasm is justified or not, people get excited about higher resolution screens, front facing cameras and dual-core processors. Researchers and analysts have predicted that by 2025 there will be six devices per human on the planet.
If this is true, it means that we would expect to see 50 billion more connected devices over the next decade. So, while a proclamation that, “5G phones with 3D cameras will become the norm in 2 – 3 years,” is a prediction that may possibly come true, it is disingenuous to say it without also discussing the software that will emerge to facilitate the trendVideo Here.
Near Field Communication (NFC):
Most of the press on NFC has gone to deals getting made between payment providers standardizing on a way for people to pay for goods with their phone. Mobile commerce, while potentially very lucrative for the key industry players, is a boring use of the technology. A more exciting use of NFC is for social interaction. Want to remember the friends you had drinks with last Tuesday? Launch the Facebook app and see who your phone auto-tagged that night.
3D cameras
No one cares about 3D TV. People hate wearing 3D glasses and the programming available for 3D television is non-existent. Mobile phone manufacturers are jumping on the 3D bandwagon so that they can check an extra box on a spec sheet. But, I believe, 3D and more specifically 3D cameras are not a lost cause. 3D cameras provide the device with a new input sensor for spatial relationships. With two cameras it is now possible for a device to gauge the speed and placement of objects in an environment. Imagine a radar gun app for measuring the velocity of a baseball, an app that renders physical objects on a device in 3D.
Future of Mobile Technoogy


Creating Your Own Chord Progression
a
b♭
b
c
c♯/d♭
d
e♭
e
f
f♯/g♭
g
g♯/a♭
major
minor
Chord Progression Name:
Please fill all four chord slots.


WITNESS LIST Appropriations-S/C on Criminal Justice Committee February 16, 1999-8:00A Budget On: Arens, James (Criminal Justice Correctional Health Advisory Committee) Hightower, Allen (Criminal Justice Correctional Health Advisory Committee) Lynaugh, Jim (Criminal Justice Correctional Health Advisory Committee) Rodriguez, Victor (Parole Board) Sapp, Allen (Criminal Justice Correctional Health Advisory Committee) Smith, David (Criminal Justice Correctional Health Advisory Committee)


{% extends "layout.html" %} {% block content %}
An exclusive mandate provides us with the sole or exclusive right to market a property on on the owner's behalf.
An offer to purchase (OTP) is the document governing the sale agreement of a property between the buyer and seller.


This is a test system designed to detect and prevent account hijacking. It collects data about the users normal browser and behaviors and uses this to identify malicious logins.
For more information you can view the code on GitHub or contact me at mhardy17@bayschoolsf.org


{include file="head"}
{position name="menu" /} {position name="slider" /} {position name="breadCrumb" /}


Now is the time for all good men to come to the aid of their country.
Now is the time for all good men to come to the aid of their country.
This card has a title but no subhead. It's using icons instead of text buttons for actions. This is generally not recommended, but it's working if you need it. Be sure to put "title" attributes on the icons.
Also notice the archive icon pushed to the right? Use the "spacer" element to push action items over to the right.
This card has no title. Notice how nicely this text is still vertically centered in the card?
This card has no image specified. It's still working!
This card has a title and action buttons pushed over to the right of the action area. Use the "spacer" element to push actions to the right.
This card has less content than it's peer in the flexbox but the action button should be lined up at the bottom.
This card also has less content.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Maecenas cursus feugiat leo, et pretium turpis suscipit sit amet. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Suspendisse iaculis neque sed massa auctor tristique. Vestibulum ante ipsum primis in faucibus orci luctus et ultrices posuere cubilia Curae; Nulla tincidunt molestie turpis, a eleifend nulla porta tincidunt. Integer quis dui posuere, commodo risus a, blandit lorem. Fusce eget aliquam mi.
Cards might have multiple headers in them.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Maecenas cursus feugiat leo, et pretium turpis suscipit sit amet. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Suspendisse iaculis neque sed massa auctor tristique. Vestibulum ante ipsum primis in faucibus orci luctus et ultrices posuere cubilia Curae; Nulla tincidunt molestie turpis, a eleifend nulla porta tincidunt. Integer quis dui posuere, commodo risus a, blandit lorem. Fusce eget aliquam mi.


No more data available.
There is nothing post, maybe I forget add.
{% extends 'base.html' %} {% import "_macros.html" as macros %} {% block title %} Home - {{ super() }} {% endblock %} {% block content %}
There is nothing post, maybe I forget add.


{% extends "base.html" %} {% load bootstrap3 %} {% block content %}
Are you sure you want to delete {{ activitycharge }}?


Priest of Dawn:
Glory to the twilight empire! The Seal of Death has awoken! We, the Lords of Dawn, will use our awesome power to achieve a new world order! [The competition is underway. New participants in the Seven Signs may start immediately.]
[Seven Signs Information]
What is the Seven Signs?
Purchase Record of the Seven Signs.
[Participate in the Seven Signs]
How do I participate in the Seven Signs?
Participation in the Seven Signs


ORACLE DataBase Placement Paper
Paper Type : Technical - Database
Oracle DBA Questions
1.SNAPSHOT is used for [DBA]
a. Synonym, b. Table space, c System server, d Dynamic data replication Ans : D
2.We can create SNAPSHOTLOG for[DBA]
a. Simple snapshots, b. Complex snapshots, c. Both A & B, d Neither A nor B Ans : A
3.Transactions per rollback segment is derived from[DBA]
a. Db_Block_Buffers, b. Processes, c. Shared_Pool_Size, d. None of the above
Ans : B
4.ENQUEUE resources parameter information is derived from[DBA]
a. Processes or DDL_LOCKS and DML_LOCKS, b. LOG_BUFFER, c. DB__BLOCK_SIZE..
Ans : A
5.LGWR process writes information into
a Database files, b Control files, c Redolog files, d All the above. Ans : C
6.SET TRANSACTION USE ROLLBACK SEGMENT is used to create user objects in a particular Tablespace
a True, b False Ans : False
7. Databases overall structure is maintained in a file called
a Redolog file, b Data file, c Control file, d All of the above.
Ans : C
8.These following parameters are optional in init.ora parameter file DB_BLOCK_SIZE, PROCESSES
a True, b False Ans : False
9.Constraints cannot be exported through EXPORT command
a True, b False Ans : False
10. It is very difficult to grant and manage common privileges needed by different groups of database users using the roles
a True, b False Ans : False
11. What is difference between a DIALOG WINDOW and a DOCUMENT WINDOW regarding moving the window with respect to the application window
a Both windows behave the same way as far as moving the window is concerned.
b A document window can be moved outside the application window while a dialog window cannot be moved
c A dialog window can be moved outside the application window while a document window cannot be moved
Ans : C
12.What is the difference between a MESSAGEBOX and an ALERT
A message box can be used only by the system and cannot be used in user application while an alert can be used in user application also.
13.A alert can be used only by the system and cannot be use din user application while an message box can be used in user application also.
14. An alert requires an response from the user while a message box just flashes a message and only requires an acknowledgment from the user
15. An message box requires an response from the user while a alert just flashes a message an only requires an acknowledgment from the user
16. Which of the following is not an reason for the fact that most of the processing is done at the server ?
a To reduce network traffic. b For application sharing, c To implement business rules centrally,d None of the above
Ans : D
17. Can a DIALOG WINDOW have scroll bar attached to it ?
a Yes, b No Ans : B
18.Which of the following is not an advantage of GUI systems ?
a. Intuitive and easy to use., b. GUI's can display multiple applications in multiple windows
c. GUI's provide more user interface objects for a developer d. None of the above
Ans :D
19.What is the difference between a LIST BOX and a COMBO BOX ?
a In the list box, the user is restricted to selecting a value from a list but in a combo box the user can type in value which is not in the list
b A list box is a data entry area while a combo box can be used only for control purposes
c In a combo box, the user is restricted to selecting a value from a list but in a list box the user can type in a value which is not in the list
d None of the above
Ans : A
20. In a CLIENT/SERVER environment , which of the following would not be done at the client ?
a User interface part, b Data validation at entry line, c Responding to user events,
d None of the above Ans : D
21.Why is it better to use an INTEGRITY CONSTRAINT to validate data in a table than to use a STORED PROCEDURE ?
a Because an integrity constraint is automatically checked while data is inserted into or updated in a table while a stored procedure has to be specifically invoked
b Because the stored procedure occupies more space in the database than a integrity constraint definition
c Because a stored procedure creates more network traffic than a integrity constraint definition
Ans : A
22.Which of the following is not an advantage of a client/server model ?
a. A client/server model allows centralised control of data and centralised implementation of business rules.
b A client/server model increases developer;s productivity
c A client/server model is suitable for all applications
d None of the above.
Ans : C
23. What does DLL stands for ?
a Dynamic Language Library
b Dynamic Link Library
c Dynamic Load Library
d None of the above
Ans : B
24.POST-BLOCK trigger is a
a Navigational trigger
b Key trigger
c Transactional trigger
d None of the above
Ans : A
25. The system variable that records the select statement that SQL * FORMS most recently used
to populate a block is
a SYSTEM.LAST_RECORD
b SYSTEM.CURSOR_RECORD
c SYSTEM.CURSOR_FIELD
d SYSTEM.LAST_QUERY
Ans: D
26. Which of the following is TRUE for the ENFORCE KEY field
a ENFORCE KEY field characterstic indicates the source of the value that SQL*FORMS uses to populate the field
b A field with the ENFORCE KEY characterstic should have the INPUT ALLOWED charaterstic turned off
a Only 1 is TRUE
b Only 2 is TRUE
c Both 1 and 2 are TRUE
d Both 1 and 2 are FALSE
Ans : A
27. What is the maximum size of the page ?
a Characters wide & 265 characters length
b Characters wide & 265 characters length
c Characters wide & 80 characters length
d None of the above
Ans : B
28. A FORM is made up of which of the following objects
a block, fields only,
b blocks, fields, pages only,
c blocks, fields, pages, triggers and form level procedures,
d Only blocks.
Ans : C
29. For the following statements which is true
1 Page is an object owned by a form
2 Pages are a collection of display information such as constant text and graphics.
a Only 1 is TRUE
b Only 2 is TRUE
c Both 1 & 2 are TRUE
d Both are FALSE
Ans : B
30. The packaged procedure that makes data in form permanent in the Database is
a Post
b Post form
c Commit form
d None of the above
Ans : C
31.Which of the following is TRUE for the SYSTEM VARIABLE $$date$$
a Can be assigned to a global variable
b Can be assigned to any field only during design time
c Can be assigned to any variable or field during run time
d None of the above
Ans : B
32.Which of the following packaged procedure is UNRESTRICTED ?
a CALL_INPUT, b CLEAR_BLOCK, c EXECUTE_QUERY, d USER_EXIT
Ans : D
33..Identify the RESTRICTED packaged procedure from the following
a USER_EXIT, b MESSAGE, c BREAK, d EXIT_FORM
Ans : D
34..What is SQL*FORMS
a SQL*FORMS is a 4GL tool for developing & executing Oracle based interactive applications.
b SQL*FORMS is a 3GL tool for connecting to the Database.
c SQL*FORMS is a reporting tool
d None of the above.
Ans : A
34.Name the two files that are created when you generate a form using Forms 3.0
a FMB & FMX, b FMR & FDX, c INP & FRM, d None of the above
Ans : C
35. What is a trigger
a A piece of logic written in PL/SQL
b Executed at the arrival of a SQL*FORMS event
c Both A & B
d None of the above
Ans : C
36. Which of the folowing is TRUE for a ERASE packaged procedure
1 ERASE removes an indicated Global variable & releases the memory associated with it
2 ERASE is used to remove a field from a page
1 Only 1 is TRUE
2 Only 2 is TRUE
3 Both 1 & 2 are TRUE
4 Both 1 & 2 are FALSE
Ans : 1
37. All datafiles related to a Tablespace are removed when the Tablespace is dropped
a TRUE
b FALSE
Ans : B
38. Size of Tablespace can be increased by
a Increasing the size of one of the Datafiles
b Adding one or more Datafiles
c Cannot be increased
d None of the above
Ans : B
39 Multiple Tablespaces can share a single datafile
a TRUE
b FALSE
Ans : B
40 A set of Dictionary tables are created
a Once for the Entire Database
b Every time a user is created
c Every time a Tablespace is created
d None of the above
Ans : A
41 Datadictionary can span across multiple Tablespaces
a TRUE
b FALSE
Ans : B
42 What is a DATABLOCK
a Set of Extents
b Set of Segments
c Smallest Database storage unit
d None of the above
Ans : C
43 Can an Integrity Constraint be enforced on a table if some existing table data does not satisfy the constraint
a Yes
b No
Ans : B
44 A column defined as PRIMARY KEY can have NULL's
a TRUE
b FALSE
Ans : B
45 A Transaction ends
a Only when it is Committed
b Only when it is Rolledback
c When it is Committed or Rolledback
d None of the above
Ans : C
46 A Database Procedure is stored in the Database
a In compiled form
b As source code
c Both A & B
d Not stored
Ans : C
47 A database trigger does not apply to data loaded before the definition of the trigger
a TRUE
b FALSE
Ans : A
48 Dedicated server configuration is
a One server process - Many user processes
b Many server processes - One user process
c One server process - One user process
d Many server processes - Many user processes
Ans : C
49 Which of the following does not affect the size of the SGA
a Database buffer
b Redolog buffer
c Stored procedure
d Shared pool
Ans : C
50 What does a COMMIT statement do to a CURSOR
a Open the Cursor
b Fetch the Cursor
c Close the Cursor
d None of the above
Ans : D
51 Which of the following is TRUE
1 Host variables are declared anywhere in the program
2 Host variables are declared in the DECLARE section
a Only 1 is TRUE
b Only 2 is TRUE
c Both 1 & 2are TRUE
d Both are FALSE
Ans : B
52 Which of the following is NOT VALID is PL/SQL
a Bool boolean;
b NUM1, NUM2 number;
c deptname dept.dname%type;
d date1 date := sysdate
Ans : B
Declare
fvar number := null; svar number := 5
Begin
goto << fproc>>
if fvar is null then
<< fproc>>
svar := svar + 5
end if;
End;
53 What will be the value of svar after the execution ?
a Error
b 10
c 5
d None of the above
Ans : A
54 Which of the following is not correct about an Exception ?
a Raised automatically / Explicitly in response to an ORACLE_ERROR
b An exception will be raised when an error occurs in that block
c Process terminates after completion of error sequence.
d A Procedure or Sequence of statements may be processed.
Ans : C
55Which of the following is not correct about User_Defined Exceptions ?
a Must be declared
b Must be raised explicitly
c Raised automatically in response to an Oracle error
d None of the above
Ans : C
56 A Stored Procedure is a
a Sequence of SQL or PL/SQL statements to perform specific function
b Stored in compiled form in the database
c Can be called from all client environmets
d All of the above
Ans : D
57 Which of the following statement is false
a Any procedure can raise an error and return an user message and error number
b Error number ranging from 20000 to 20999 are reserved for user defined messages
c Oracle checks Uniqueness of User defined errors
d Raise_Application_error is used for raising an user defined error.
Ans : C
58 Is it possible to open a cursor which is in a Package in another procedure ?
a Yes
b No
Ans : A
59 Is it possible to use Transactional control statements in Database Triggers?
a Yes
b No
Ans : B
60 Is it possible to Enable or Disable a Database trigger ?
a Yes
b No
Ans : A
61 PL/SQL supports datatype(s)
a Scalar datatype
b Composite datatype
c All of the above
d None of the above
Ans C
62 Find the ODD datatype out
a VARCHAR2
b RECORD
c BOOLEAN
d RAW
Ans : B
63 Which of the following is not correct about the "TABLE" datatype ?
a Can contain any no of columns
b Simulates a One-dimensional array of unlimited size
c Column datatype of any Scalar type
d None of the above
Ans : A
63 Find the ODD one out of the following
a OPEN
b CLOSE
c INSERT
d FETCH
Ans C
64 Which of the following is not correct about Cursor ?
a Cursor is a named Private SQL area
b Cursor holds temporary results
c Cursor is used for retrieving multiple rows
d SQL uses implicit Cursors to retrieve rows
Ans : B
65 Which of the following is NOT VALID in PL/SQL ?
a Select ... into
b Update
c Create
d Delete
Ans : C
66 What is the Result of the following 'VIK'||NULL||'RAM' ?
a Error
b VIK RAM
c VIKRAM
d NULL
Ans : C
67 Declare
a number := 5; b number := null; c number := 10;
Begin
if a > b AND a < c then
a := c * a;
end if;
End;
68 What will be the value of 'a' after execution ?
a 50
b NULL
c 5
d None of the above
Ans : C
69 Does the Database trigger will fire when the table is TRUNCATED ?
a Yes
b No
Ans : B
70 SUBSTR(SQUARE ANS ALWAYS WORK HARD,14,6) will return
a ALWAY
b S ALWA
c ALWAYS
Ans : C
71 REPLACE('JACK AND JUE','J','BL') will return
a JACK AND BLUE
b BLACK AND JACK
c BLACK AND BLUE
d None of the above
Ans : C
72 TRANSLATE('333SQD234','0123456789ABCDPQRST','0123456789') will return
a 333234
b 333333
c 234333
d None of the above
Ans : A
73 EMPNO ENAME SAL
A822 RAMASWAMY 3500
A812 NARAYAN 5000
A973 UMESH 2850
A500 BALAJI 5750
74 Use these data for the following Questions
Select SAL from EMP E1 where 3 > ( Select count(*) from Emp E2 where E1.SAL > E2.SAL ) will retrieve
a 3500,5000,2500
b 5000,2850
c 2850,5750
d 5000,5750
Ans : A
75 Is it possible to modify a Datatype of a column when column contains data ?
a Yes
b No
Ans B
76 Which of the following is not correct about a View ?
a To protect some of the columns of a table from other users
b Ocuupies data storage space
c To hide complexity of a query
d To hide complexity of a calculations
Ans : B
77.Which is not part of the Data Definiton Language ?
a CREATE
b ALTER
c ALTER SESSION
Ans : C
78 The Data Manipulation Language statements are
a INSERT
b UPDATE
c SELECT
d All of the above
Ans : D
79 EMPNO ENAME SAL
A822 RAMASWAMY 3500
A812 NARAYAN 5000
A973 UMESH
A500 BALAJI 5750
Using the above data
Select count(sal) from Emp will retrieve
a 1
b 0
c 3
d None of the above
Ans : C
80 If an UNIQUE KEY constraint on DATE column is created, will it accept the rows that are inserted with
SYSDATE ?
a Will
b Won't
Ans : B
81 What are the different events in Triggers ?
a Define, Create
b Drop, Comment
c Insert, Update, Delete
d All of the above
Ans : C
82 What built-in subprogram is used to manipulate images in image items ?
a Zoom_out
b Zoom_in'
c Image_zoom
d Zoom_image
Ans : C
83 Can we pass RECORD GROUP between FORMS ?
a Yes
b No
Ans : A
84 SHOW_ALERT function returns
a Boolean
b Number
c Character
d None of the above
Ans : B
85 What SYSTEM VARIABLE is used to refer DATABASE TIME ?
a $$dbtime$$
b $$time$$
c $$datetime$$
d None of the above
Ans : A
86 SYSTEM.EFFECTIVE.DATE varaible is
a Read only
b Read & Write
c Write only
d None of the above
Ans : C
87 How can you CALL Reports from Forms4.0 ?
a Run_Report built_in
b Call_Report built_in
c Run_Product built_in
d Call_Product built_in
Ans : C
88 When do you get a .PLL extension ?
a Save Library file
b Generate Library file
c Run Library file
d None of the above
Ans : A
89 What is built_in Subprogram ?
a Stored procedure & Function
b Collection of Subprogram
c Collection of Packages
d None of the above
Ans : D
90 GET_BLOCK property is a
a Restricted procedure
b Unrestricted procedure
c Library function
d None of the above
Ans : D
91 A CONTROL BLOCK can sometimes refer to a BASETABLE ?
a TRUE
b FALSE
Ans : B
92 What do you mean by CHECK BOX ?
a Two state control
b One state control
c Three state control
d none of the above
Ans : C - Please check the Correcness of this Answer ( The correct answeris 2 )
92 List of Values (LOV) supports
a Single column
b Multi column
c Single or Multi column
d None of the above
Ans : C
93.What is Library in Forms 4.0 ?
a Collection of External field
b Collection of built_in packages
c Collection of PL/SQl functions, procedures and packages
d Collection of PL/SQL procedures & triggers
Ans : C
94 Can we use a RESTRICTED packaged procedure in WHEN_TEXT_ITEM trigger ?
a Yes
b No
Ans : B
95 Can we use GO_BLOCK package in a PRE_TEXT_ITEM trigger ?
a Yes
b No
Ans : B
96 What type of file is used for porting Forms 4.5 applications to various platforms ?
a . FMB file
b . FMX file
c . FMT file
d . EXE file
Ans : C
97 What built_in procedure is used to get IMAGES in Forms 4.5 ?
a READ_IMAGE_FILE
b GET_IMAGE_FILE
c READ_FILE
d GET_FILE
Ans A
98 When a form is invoked with CALL_FORM does Oracle forms issues SAVEPOINT ?
a Yes
b No
Ans : A
100 Can we attach the same LOV to different fields in Design time ?
a Yes
b No
Ans : A
1How do you pass values from one form to another form ?
a LOV
b Parameters
c Local variables
d None of the above
Ans : B
2Can you copy the PROGRAM UNIT into an Object group ?
a Yes
b No
Ans : B
100. Can MULTIPLE DOCUMENT INTERFACE (MDI) be used in Forms 4.5 ?
a Yes
b No
Ans : A
3Can MULTIPLE DOCUMENT INTERFACE (MDI) be used in Forms 4.5 ?
a Yes
b No
Ans : A
3When is a .FMB file extension is created in Forms 4.5 ?
a Generating form
b Executing form
c Save form
d Run form
Ans : C
5What is a Built_in subprogram ?
a Library
b Stored procedure & Function
c Collection of Subprograms
d None of the above
Ans : D
What is a RADIO GROUP ?
a Mutually exclusive
b Select more than one column
c Above all TRUE
d Above all FALSE
Ans : A
Identify the Odd one of the following statements ?
a Poplist
b Tlist
c List of values
d Combo box
Ans : C
What is an ALERT ?
a Modeless window
b Modal window
c Both are TRUE
d None of the above
Ans : B
Can an Alert message be changed at runtime ?
a Yes
b No
Ans : A
Can we create an LOV without an RECORD GROUP ?
a Yes
b No
Ans : B
How many no of columns can a RECORD GROUP have ?
a 10
b 20
c 50
d None of the above
Ans D
Oracle precompiler translates the EMBEDDED SQL statemens into
a Oracle FORMS
b Oracle REPORTS
c Oracle LIBRARY
d None of the above
Ans : D
Kind of COMMENT statements placed within SQL statements ?
a Asterisk(*) in column ?
b ANSI SQL style statements(...)
c C-Style comments (/*......*/)
d All the above
Ans : D
What is TERM ?
a TERM is the terminal definition file that describes the terminal from which you are using R20RUN
( Reports run time )
b TERM is the terminal definition file that describes the terminal from which you are using R20DES
( Reports designer )
c There is no Parameter called TERM in Reports 2.0
d None of the above
Ans : A
If the maximum records retrieved property of a query is set to 10, then a summary value will
be calculated
a Only for 10 records
b For all the records retrieved
c For all therecords in the referenced table
d None of the above
Ans : A
With which function of a summary item in the COMPUTE AT optio required ?
a Sum
b Standard deviation
c Variance
d % of Total function
Ans : D
For a field in a repeating frame, can the source come from a column which does not exist in
the datagroup which forms the base of the frame ?
a Yes
b No
Ans : A
What are the different file extensions that are created by Oracle Reports ?
a . RDF file & .RPX file
b . RDX file & .RDF file
c . REP file & .RDF file
d None of the above
Ans : C
Is it possible to Disable the Parameter form while running the report?
a Yes
b No
Ans : A
What are the SQL clauses supported in the link property sheet ?
a WHERE & START WITH
b WHERE & HAVING
c START WITH & HAVING
d WHERE, START WITH & HAVING
Ans : D
What are the types of Calculated columns available ?
a Summary, Place holder & Procedure column
b Summary, Procedure & Formula columns
c Procedure, Formula & Place holder columns
d Summary, Formula & Place holder columns
Ans.: D
If two groups are not linked in the data model editor, what is the hierarchy between them?
a There is no hierarchy between unlinked groups
b The group that is right ranks higher than the group that is to theleft
c The group that is above or leftmost ranks higher than the group that is to right or below it
d None of the above
Ans : C
Sequence of events takes place while starting a Database is
a Database opened, File mounted, Instance started
b Instance started, Database mounted & Database opened
c Database opened, Instance started & file mounted
d Files mounted, Instance started & Database opened
Ans : B
SYSTEM TABLESPACE can be made off-line
a Yes
b No
Ans : B
ENQUEUE_RESOURCES parameter information is derived from
a PROCESS or DDL_LOCKS & DML_LOCKS
b LOG BUFFER
c DB_BLOCK_SIZE
d DB_BLOCK_BUFFERS
Ans : A
SMON process is used to write into LOG files
a TRUE
b FALSE
Ans : B
EXP command is used
a To take Backup of the Oracle Database
b To import data from the exported dump file
c To create Rollback segments
d None of the above
Ans : A
SNAPSHOTS cannot be refreshed automatically
a TRUE
b FALSE
Ans : B
The User can set Archive file name formats
a TRUE
b FALSE
Ans : A
The following parameters are optional in init.ora parameter file DB_BLOCK_SIZE, PROCESS
a TRUE
b FALSE
Ans : B
NOARCHIEVELOG parameter is used to enable the database in Archieve mode
a TRUE
b FALSE
Ans : B
Constraints cannot be exported through Export command?
a TRUE
b FALSE
Ans : B
It is very difficult to grant and manage common priveleges needed by
different groups of database users using roles
a TRUE
b FALSE
Ans : B
The status of the Rollback segment can be viewed through
a DBA_SEGMENTS
b DBA_ROLES
c DBA_FREE_SPACES
d DBA_ROLLBACK_SEG
Ans : D
Explicitly we can assign transaction to a rollback segment
a TRUE
b FALSE
Ans : A
What file is read by ODBC to load drivers ?
a ODBC.INI
b ODBC.DLL
c ODBCDRV.INI
d None of the above
Ans : A
Oracle SQL Questions and answers
Oracle Interview Questions and Answers : SQL
1. To see current user name
Sql> show user;
2. Change SQL prompt name
SQL> set sqlprompt “Manimara > “
Manimara >
Manimara >
3. Switch to DOS prompt
SQL> host
4. How do I eliminate the duplicate rows ?
SQL> delete from table_name where rowid not in (select max(rowid) from table group by
duplicate_values_field_name);
or
SQL> delete duplicate_values_field_name dv from table_name ta where rowid <(select min(rowid) from
table_name tb where ta.dv=tb.dv);
Example.
Table Emp
Empno Ename
101 Scott
102 Jiyo
103 Millor
104 Jiyo
105 Smith
delete ename from emp a where rowid < ( select min(rowid) from emp b where a.ename = b.ename);
The output like,
Empno Ename
101 Scott
102 Millor
103 Jiyo
104 Smith
5. How do I display row number with records?
To achive this use rownum pseudocolumn with query, like SQL> SQL> select rownum, ename from emp;
Output:
1 Scott
2 Millor
3 Jiyo
4 Smith
6. Display the records between two range select rownum, empno, ename from emp where rowid in
(select rowid from emp where rownum <=&upto minus select rowid from emp where rownum<&Start);
Enter value for upto: 10
Enter value for Start: 7
ROWNUM EMPNO ENAME
1 7782 CLARK
2 7788 SCOTT
3 7839 KING
4 7844 TURNER
7. I know the nvl function only allows the same data type(ie. number or char or date Nvl(comm, 0)),
if commission is null then the text “Not Applicable” want to display, instead of blank space. How do I write the query?
SQL> select nvl(to_char(comm.),'NA') from emp;
Output :
NVL(TO_CHAR(COMM),'NA')
NA
300
500
NA
1400
NA
NA
8. Oracle cursor : Implicit & Explicit cursors
Oracle uses work areas called private SQL areas to create SQL statements. PL/SQL construct to identify each and every work are used, is called as Cursor.
For SQL queries returning a single row, PL/SQL declares all implicit cursors. For queries that returning more than one row, the cursor needs to be explicitly declared.
9. Explicit Cursor attributes There are four cursor attributes used in Oracle cursor_name%Found, cursor_name%NOTFOUND, cursor_name%ROWCOUNT, cursor_name%ISOPEN
10. Implicit Cursor attributes Same as explicit cursor but prefixed by the word SQL SQL%Found, SQL%NOTFOUND, SQL%ROWCOUNT, SQL%ISOPEN
Tips : 1. Here SQL%ISOPEN is false, because oracle automatically closed the implicit cursor after executing SQL statements.
: 2. All are Boolean attributes.
11.  To view installed Oracle version information SQL> select banner from v$version;
13. Display the number value in Words SQL> select sal, (to_char(to_date(sal,'j'), 'jsp'))
from emp;
the output like,
SAL (TO_CHAR(TO_DATE(SAL,'J'),'JSP'))
800 eight hundred
1600 one thousand six hundred
1250 one thousand two hundred fifty
If you want to add some text like,
Rs. Three Thousand only.
SQL> select sal "Salary ",
(' Rs. '|| (to_char(to_date(sal,'j'), 'Jsp'))|| ' only.'))
"Sal in Words" from emp
/
Salary Sal in Words
800 Rs. Eight Hundred only.
1600 Rs. One Thousand Six Hundred only.
1250 Rs. One Thousand Two Hundred Fifty only.
14. Display Odd/ Even number of records Odd number of records:
select * from emp where (rowid,1) in (select rowid, mod(rownum,2) from emp);
1
3
5
Even number of records:
select * from emp where (rowid,0) in (select rowid, mod(rownum,2) from emp)
2
4
6
15. Which date function returns number value? months_between
16. Any three PL/SQL Exceptions?
Too_many_rows, No_Data_Found, Value_Error, Zero_Error, Others
17. What are PL/SQL Cursor Exceptions?
Cursor_Already_Open, Invalid_Cursor
18. Other way to replace query result null value with a text
SQL> Set NULL ‘N/A’
to reset SQL> Set NULL ‘’
19. What are the more common pseudo-columns?
SYSDATE, USER , UID, CURVAL, NEXTVAL, ROWID, ROWNUM
20. What is the output of SIGN function?
1 for positive value,
0 for Zero,
-1 for Negative value.
21. What is the maximum number of triggers, can apply to a single table?
12 triggers.


About
Organizers: Francisco J.
Marmolejo Cossio and Faidra Monachou
Contact:
<EMAIL_ADDRESS><EMAIL_ADDRESS>Program Chairs
Francisco J. Marmolejo Cossio, University of Oxford
Francisco J. Marmolejo Cossio is a Career Development Fellow in Computer Science at Balliol College within the University of Oxford. He is also a Research Fellow at Input Output Hong Kong (IOHK). His research lies at the intersection of Algorithmic Game Theory, Decentralised Consensus Protocols and Computational Learning Theory. His work has focused on establishing query-efficient protocols for equilibrium computation as well as understanding incentives in decentralised systems. Francisco holds a D.Phil. in Computer Science and an M.Sc. in Mathematics and Foundations of Computer Science from the University of Oxford, as well as a B.A. in Mathematics from Harvard University. Francisco is originally from San Luis Potosi, Mexico, and has been co-organizing the development working group since Spring 2019. Francisco has also been co-organizing the MD4SG initiative as a whole since Spring 2020.
Faidra Monachou, Stanford University
Faidra Monachou is a Ph.D. candidate in Operations Research at the Department of Management Science and Engineering at Stanford University, advised by Itai Ashlagi. Her work focuses on market design and matching theory, and aims at understanding the theoretical foundations of socioeconomic problems that arise in large-scale online markets. She is particularly interested in the study of bias and discrimination in the sharing economy, labor markets and education as well as the role of information design and learning in redesigning non-monetary matching markets. Before coming to Stanford, she graduated from National Technical University of Athens in Greece, where she studied Electrical Engineering and Computer Science. Faidra has been member of the MD4SG initiative since Fall 2018. She has been serving as a co-organizer of the MD4SG Bias, Discrimination, and Fairness working group since Fall 2019.
Steering Committee
- Rediet Abebe, Harvard University
- Kira Goldner, Columbia University
- Jon Kleinberg, Cornell University
- Illenin Kondo, University of Notre-Dame
- Sera Linardi, University of Pittsburgh
- Irene Lo, Stanford University
- Ana-Andreea Stoica, Columbia University
Area Chairs
- Theory: Daniel Freund, MIT Sloan; Sam Taggart, Oberlin College; Matt Weinberg, Princeton University
- Empirical Studies and Policy: Zoe B. Cullen, Harvard Business School; Robert Manduca, University of Michigan
- AI and ML: Dina Machuve, Nelson Mandela African Institution of Science and Technology; Ana-Andreea Stoica, Columbia University; Bryan Wilder, Harvard University
- Problems and Demos: Araba Sey, United Nations University; Abhishek Gupta, Microsoft and Montreal AI Ethics Institute
Workshop Chairs
- Diversity & Inclusion Chairs: Wanyi Li, Michelle Gonzalez & Meareg Hailemariam
- Poster Session Chairs: Duncan McElfresh & Jessie Finocchiaro
- Social Chairs: Lily Xu & Logan Stapleton
- Social Media Chair: Amita Shukla
Program Committee
- Itai Ashlagi, Stanford University
- Beatriz Ahumada, University of Pittsburgh
- Hamsa Bastani, Wharton School - University of Pennsylvania
- Michael Carlos Best, Columbia University
- Michael Best, Georgia Institute of Technology
- Elettra Bietti, Harvard Law School
- Abeba Birhane, University College Dublin
- Peter Blair, Harvard University
- Mark Braverman, Princeton University
- Sydnee Caldwell, UC Berkeley
- Augustin Chaintreau, Columbia University
- Jose R. Correa, Universidad de Chile
- Lenore Cowen, Tufts University
- Krishna Dasaratha, Harvard University
- Bikramaditya Datta, Indian Institute of Technology, Kanpur
- Jonathan Davis, University of Oregon
- Maria De-Arteaga, University of Texas at Austin
- Joann de Zegher, MIT Sloan
- John P. Dickerson, University of Maryland
- Edith Elkind, University of Oxford
- Meryem Essaidi, Princeton University
- Elizabeth Evans, Cayena Capital Management, LLC
- Elena Falcettoni, Federal Reserve Board of Governors
- Jessie Finnochiaro, University of Colorado Boulder
- Felix Fischer, Queen Mary University of London
- Rupert Freeman, Microsoft Research
- Jiarui Gan, University of Oxford
- Nikhil Garg, Stanford University
- Joel Goh, NUS Business School
- Michelle Gonzalez Amador, United Nations University
- Wade Hann-Caruthers, Caltech
- Yoan Hermstrüwer, Max Planck Institute for Research on Collective Goods
- Marc Juarez, University of Southern California
- Anson Kahng, Carnegie Mellon University
- Adam Kapor, Princeton University
- Maximilian Kasy, University of Oxford
- Matthew Kenney, Duke University
- Robizon Khubulashvili, Pennsylvania State University
- Lynn Kirabo, Carnegie Mellon University
- Sara Kingsley, Carnegie Mellon University
- Karen Levy, Cornell University
- Wanyi Li, Stanford University
- Edwin Lock, University of Oxford
- Vahideh Manshadi, Yale University
- Nicholas Mattei, Tulane University
- Duncan McElfresh, University of Maryland
- Jasmin McNealy, University of Florida
- Teddy Mekonnen, Brown University
- Eric Mibuari, Harvard University
- Ken Moon, University of Pennsylvania - Wharton
- Nyalleng Moorosi, Google AI South Africa
- Zanele Munyikwa, MIT Sloan
- George Obaido, University of the Witwatersrand, Johannesburg
- Chinasa Okolo, Cornell University
- Roya Pakzad, Taraaz
- Bobby Pakzad-Hurson, Brown University
- Lucy Qin, Brown University
- Manish Raghavan, Cornell University
- Evan Riehl, Cornell University
- Sarah Riley, Cornell University
- David Robinson, Upturn
- Daniela Saban, Stanford University
- Zhaowei She, Georgia Institute of Technology
- Eric Sodomka, Facebook Research
- Nicolas Stier, Facebook Research
- Inbal Talgam-Cohen, Technion - Israel Institute of Technology
- Alex Teytelboym, University of Oxford
- Neil Thakral, Brown University
- Winnie van Dijk, University of Chicago
- Daniel Waldinger, New York University
- Yixin Wang, Columbia University
- Anne Washington, New York University
- Lily Xu, Harvard University
- Angela Zhou, Cornell University


{% extends 'base.html' %} {% block title %}Instajam{% endblock %} {% block body %}
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The b8r demo pages require ES Modules support, including dynamic import()
.
Your browser appears not to support ES6 Modules.
Chrome (63+), Safari (11+), Firefox (66+) support ES6 Modules as of writing this.
Firefox users may need to enable them in about:config
.


My research work focuses on creating automated help features for students while programming in Snap!, a block-based programming environment.
In this project I added textual explanations to next step hints, and self-explanation prompts to encourage students to self-reflect on the hints they receive. I found that students prefer having hints with textual explanations; and that having self-explanations prompts improved students' learning. The following is a demo on how this help feature looks like, and you can check my publications page to check published papers on this project.
In this project I created data-driven positive and corrective immediate feedback through an objectives list that shows students their progress on subgoals. The objectives list provides students with progress bars on each subgoal using a hybrid data-driven subgoal detector model. The following is a demo on how this help feature looks like, and you can check my publications page to check published papers on this project.


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Investors are still betting on a rising stock market, but they've been doing so with less long-term conviction.
-
Intel to invest $1.5 billion in 20 percent stake in Chinese semiconductor ...
www.reuters.com
BEIJING (Reuters) - Intel Corp will invest $1.5 billion in a 20 percent stake in two semiconductor units of China's state-owned Tsinghua Unigroup, ...
-
Andreessen: Bubble Believers 'Don't Know What They're Talking About'
online.wsj.com
In an interview, venture capitalist Marc Andreessen discusses the current state of tech investing and why "this is a time of very big franchise ...
-
Microsoft pushes collaboration with Groups for Office 365
venturebeat.com
Groups might not sound like a huge advancement, drawing as it does on several Microsoft tools that have existed for years, like file sharing and ...
-
Alibaba Could Become a Victim of its Success
online.wsj.com
Alibaba's success has helped and encouraged other e-commerce companies to flood the market and try to lure away China's millions of increasingly ...
-
Hong Kong Beats Singapore in Corporate Governance Survey
www.bloomberg.com
Corporate governance in Singapore deteriorated in the past two years amid slowing reforms on the subject, dipping below the perceived strength of ...
-
Harvard Picks Insider to Run $36.4 Billion Endowment
www.bloomberg.com
Harvard University named Stephen Blyth as head of its $36.4 billion endowment, picking an insider as it looks to boost investment returns that have ...
-
Chinese Leaders Discuss Replacing PBOC Chief
online.wsj.com
China's Xi Jinping and other leaders are discussing replacing the central bank chief amid disagreements over the direction of financial policy, ...
-
Top 100 Richest Indians: India's Pharma Sector Mints Billionaires
www.forbes.com
Pharma is on a roll. More than a fifth of the 100 richest billionaires in India have pharma and health care riches, among them half of the eight ...
-
Flawed sparkler
www.economist.com
Fur real Napoleon the Great. By Andrew Roberts. Allen Lane; 936 pages; £30. To be published in America by Viking in November; $40. Buy from ...
-
Read all NSA related articles in English
www.svt.se
All articles published by Uppdrag granskning relating to the Snowden documents will be published in English under this headline.
-
ECB Draghi eady to use additional measures 25 September 2014 | ForexLive
www.forexlive.com
ECB Draghi comments on the wires - ready to use additional measures 25 September 2014
-
Yellen Warning on Unsettled Rate Timetable Ignored by Investors
www.bloomberg.com
Federal Reserve Chair Janet Yellen says she wants investors to be prepared for the possibility that the Fed will raise interest rates sooner than ...
-
Eric Schmidt: Apple-Google Competition More `Brutal' Now: Video
www.bloomberg.com
Google Inc. Chairman Eric Schmidt and former Senior Vice President Jonathan Rosenberg talk about their book "How Google Works," the mobile industry ...
-
Pimco Bought Some Little Bonds
www.bloombergview.com
The whole job of a fund manager is to buy things for less than you think they're worth. But then just marking them where you think they're worth ...
-
Property: Land of opportunity - FT.com
www.ft.com
The Brace & Limb building stands at 1125 Ninth Street in the small city of Altoona in central Pennsylvania. Its three modest storeys are handsome ...
-
Obamacare Website Costs Exceed $2 Billion, Study Finds
www.bloomberg.com
The federal government’s Obamacare enrollment system has cost about $2.1 billion so far, according to a Bloomberg Government analysis of contracts ...


Work Day Scheduler
A simple calendar app for scheduling your work day
Instructions
Click the button below to open a form and provide information for the following:
9AM
10AM
11AM
12PM
1PM
2PM
3PM
4PM
5PM
6PM
10PM
11PM


Iterave offers a full range of solutions that can transform your business. For small and medium sized companies, we can enable capabilities normally only found in larger companies. And for larger companies, we can scale back cost and complexity to find an effective balance for your teams and projects.
Iterave offers a full range of custom, mobile friendly, web based software solutions for your business. Using popular open-source software stacks, cost can be reduced, while achieving industry leading performance and stability. Why pay for commodity software, when you can instead invest in your competitive advantage?
The days of refrigerating your own server rooms are over. These are now commoditized services that can be leveraged as a utility, similar to electricity. The cloud offers stable, secure and scalable infrastructure as a service that can start small and grow quickly and easily with your company. The whole process can be integrated and automated to ease maintenance and reduce long-term costs.
We have over 18 years of experience with software development methodologies, including traditional, agile and even post-agile methods. Together we can find what works for your company and your teams. We draw from well proven methodologies like Lean, Scrum and XP, and implement practices with a practical and flexible approach.
Lean is a people focused set of principles that helps create a system through which people can succeed. Specific practices will help eliminate waste, focus on quality and reduce cycle time. However, Lean can be most successful when adopted more broadly throughout a company.
Scrum has gained immense popularity due to its simplicity and strong commercial support. Alone it's not enough, but together with support from other methodologies such as Lean and XP, Scrum can add key benefits such as greater visibility and more collaboration at a product management and project management level.
At the development level, XP focuses on creating rock solid software that is fast to build, easy to maintain, well-tested and with automated processes wherever possible to reduce costs and complexity.
The methods mentioned above were each created with experience and input from people at all levels and roles within the software development community. And there are others still! While they each differ, they all share common themes that can be explored and integrated into your methodology.
I have 18 years experience building scalable, connected applications using modern tools and practices. A diverse technology profile includes the full stack, from the web browser through to the database and integrated systems.
With over a decade of mentorship experience, I've transformed teams and entire companies into effective product development engines using custom tailored organizational structures and methodologies.
I have a modern focus on cloud architecture, platform as a service and infrastructure as a service. I believe in automating the integration of software applications from development through to production deployments.
It would be my pleasure to apply my experience to your needs.


The basic concepts involved in how the Strongtalk VM works have been published or discussed publically in the past, and are discussed here. The basic idea is very simple: a two-phase execution system is used, with the first phase determining which code is frequently executed. The second, optimizing phase is invoked only for frequently executed code.
This takes advantage of a well-known property of programs: most programs spend the vast majority of their time executing a very small portion of their code. By only optimizing performance critical code, extensive inlining and optimization can be done, which would cause too much overhead in code space and compilation time if it were done on the whole program.
Just as in other Smalltalks, source code is compiled into a portable byte-code format that is kept in the image. When the code is first executed, it is interpreted, as in an interpreted Smalltalk. But the similarities end there. The interpreted code is instrumented in several ways, to determine the execution characteristics of each section of code. This is done with two measurement techiques:
Invocation Counters: Counters are used to keep track of how many times each method is called, and how many times each loop iterates. This is used to determine how performance-critical each section of code is.
Inline-caching: Each message send is instrumented to determine what methods are invoked by that send. There are three important cases that are distinguished:
Monomorphic Sends: A monomorphic send is one that only ever invoked for one receiver class during execution. This does not mean that it can't invoke others in the future- it only means that up to this point, the send has only been invoked with a single receiver class (perhaps many times). The VM keeps track of this class using a standard inline-cache. The vast majority (over 90%) of dynamic sends fall into this category.
Slightly Polymorphic Sends: A slighly polymorphic send is one that invokes one of a very small number of receiver classes, but more than just one. The VM keeps track of the small set of receiver classes using a polymorphic inline-cache (PIC).
Megamorphic Sends: A megamorphic send is one that has many different receiver classes, too many to keep track of. Very few sends fall into this category.
The smaller the number of receiver classes invoked by a send (called the arity), the easier it is to optimize it using inlining in the second phase. An important associated technique called customization is used to help reduce the arity of sends, so that more of them can be optimized. Customization works by making copies of performance-critical methods for each concrete subclass, just as if inheritance were treated as a form of code copying. Many sends can become monomorphic after customization. For example, a self-send in a superclass method would not ordinarily be monomorphic, because self can be any one of a number of different subclasses. But if a copy of the method is made for every subclass, then each copy only ever has one class for self, and thus all self sends become monomorphic.


import LiteYouTubeEmbed from ‘react-lite-youtube-embed’; import ‘react-lite-youtube-embed/dist/LiteYouTubeEmbed.css’
React Redux is the official React UI bindings layer for Redux. It lets your React components read data from a Redux store, and dispatch actions to the store to update state.
React Redux 7.1+ requires React 16.8.3 or later, in order to make use of React Hooks.
The recommended way to start new apps with React and Redux is by using the official Redux+JS template or Redux+TS template for Create React App, which takes advantage of Redux Toolkit and React Redux’s integration with React components.
# Redux + Plain JS template
npx create-react-app my-app --template redux
# Redux + TypeScript template
npx create-react-app my-app --template redux-typescript
To use React Redux with your React app, install it as a dependency:
You’ll also need to install Redux and set up a Redux store in your app.
If you are using TypeScript, the React Redux types are maintained
separately in DefinitelyTyped, but included as a dependency of the
react-redux
package, so they should be installed
automatically. If you still need to install them manually, run:
Provider
React Redux includes a <Provider />
component, which
makes the Redux store available to the rest of your app:
import React from 'react'
import ReactDOM from 'react-dom'
import { Provider } from 'react-redux'
import store from './store'
import App from './App'
const rootElement = document.getElementById('root')
ReactDOM.render(
<Provider store={store}>
<App />
</Provider>,
rootElement
)
React Redux provides a pair of custom React hooks that allow your React components to interact with the Redux store.
useSelector
reads a value from the store state and subscribes
to updates, while useDispatch
returns the store’s
dispatch
method to let you dispatch actions.
import React from 'react'
import { useSelector, useDispatch } from 'react-redux'
import {
decrement,
increment,
incrementByAmount,
incrementAsync,
selectCount,
} from './counterSlice'
import styles from './Counter.module.css'
export function Counter() {
const count = useSelector(selectCount)
const dispatch = useDispatch()
return (

<button
className={styles.button}
aria-label="Increment value"
onClick={() => dispatch(increment())}
>
+
</button>
{count}
<button
className={styles.button}
aria-label="Decrement value"
onClick={() => dispatch(decrement())}
>
-
</button>

{/* omit additional rendering output here */}

)
}
Redux maintainer Mark Erikson appeared on the “Learn with Jason” show to explain how we recommend using Redux today. The show includes a live-coded example app that shows how to use Redux Toolkit and React-Redux hooks with Typescript, as well as the new RTK Query data fetching APIs.
See the “Learn Modern Redux” show notes page for a transcript and links to the example app source.
The #redux channel of the Reactiflux Discord community is our official resource for all questions related to learning and using Redux. Reactiflux is a great place to hang out, ask questions, and learn - come join us!
You can also ask questions on Stack Overflow using the #redux tag.


Working as a Research Assistant in the Science Gateway Research Center at Indiana University.
Primarily working on the Apache Airavata open source project to enable execution of jobs (high performance parallel MPI jobs, as well as serial jobs) on cloud & containerized resources - EC2, OpenStack, Docker & other HPC clusters.
Building a Mesos based meta-scheduler for Apache Airavata - using Apache Mesos, Marathon, etc.
Worked on the IBM Watson Health "Real World Evidence" (RWE) project. RWE is a cloud service offering that provides an analytics platform (single tenant, multi-user) for gaining deeper insights into healthcare related data, and potentially to transform the healthcare and life sciences space.
My contribution:
Software Research Engineer, part of the IBM Research Team researching Hybrid Clouds. Working towards integration and management of IaaS and PaaS across on-premise and off-premise cloud environments. On-going research to develop a Hybrid Cloud Broker that seamlessly operates across multiple technologies enabling integration of heterogeneous multiple IaaS/PaaS cloud platforms and services using standard API sets.
My work included: research, test and contributing significant input in shaping the process for adopting cloud computing at Indiana University.
Also worked on:
Software Research Engineer, part of the IBM Research Team researching Hybrid Clouds. Working towards integration and management of IaaS and PaaS across on-premise and off-premise cloud environments. On-going research to develop a Hybrid Cloud Broker that seamlessly operates across multiple technologies enabling integration of heterogeneous multiple IaaS/PaaS cloud platforms and services using standard API sets.


Sample Text Here
A shameless fork sorter specifically designed for most (if not all) Manga Time Kirara characters.
Certain options have details that you can hover to read if you're on a laptop.
Click on the character you like better from the two, or tie them if you like them equally or don't know them.
Unless you picked Agony Mode (WIP), in which case, you can't tie them; instead, you can do a coin flip (You will not be informed who won the coin flip).
Depending on how many sources you pick (especially under default settings), you'll get up to 700+ picks, so set aside a good few cups of tea and possibly your revolver for this.
Keyboard controls during sorting: H/LeftArrow (pick left) J/DownArrow (undo) K/UpArrow (tie) L/RightArrow (pick right) S (save progress).
Before sorting: S/Enter (start sorting) L (load progress).
1/2/3 always correspond to the first/second/third buttons.
Inspired by this site and this one.. Thumbnail Art: Official Sources from Ayaya. For everything else, I forgot: Blame Google. And Wikia.
May 21, 2022 - Added alot of characters (I had to catch up to 2 years worth of content, woops.)
May 15, 2020 - Added Koisuru Asteroid + All the event cards from March to May.
Mar 02, 2020 - Added some characters and updated images; You will now occasionally encounter alternate images.
Jan 06, 2020 - Added some characters and updated images, including datamined items.
Jun 24, 2019 - Added some characters and updated images, including datamined items.
Mar 29, 2019 - Added more characters. Man, these are alot of characters...
Jan 18, 2019 - (Technically Jan 17 but whatever) Added more Anima Yell characters and Lamp, who is one of the Kirara Fantasia mascots waifus.
Dec 24, 2018 - Added the needed updates in art; added GU and Sansha Sanyou (placeholder art only), as well as other released charas in Kirara Fantasia.
Jul 07, 2018 - The first more stable-ish version; everything except Original are there.
Jun 25, 2018 - Almost all of the series in-game are done with 5 remaining. I'm working on the non-confirmed series.
Jun 22, 2018 - Edited index.html; WIP lots of things as there's way too many charas in Kirara


GSF is a language infrastructure for NetBeans. The purpose of GSF is to help create first-class editing support for a group languages (like Ruby, Groovy, JavaScript, Python, Scala, PHP, etc). By "first-class" editing support I mean all the features that we currently have for Java in NetBeans. Deep editing support including intelligent code completion, quick fixes and hints, and so on.
The abbreviation "GSF" is an historical artifact and a new name should probably be assigned.
The GSF API is intended for "language plugins". These are modules which add support for new languages (such as Ruby, JavaScript, HTML, CSS and so on) to NetBeans. The key philosophy behind GSF is:
The language plugin deals only with language specific details.
The implication of this is that nearly all UI, and all "infrastructure" code like listening on editor changes, scheduling parsing, implementing editor actions etc. are handled by the GSF infrastructure. A language plugin should just focus on specific features as they pertain to this language.
If you are trying to get started writing a new language using GSF, see the Getting Started document, which will try to order the tasks involved and point to the relevant sections.
For an example of this, take a look at the following diagram. This shows how "Instant Rename" works in GSF. The Instant Rename action itself (editor action implementation, keybinding registration, etc.) is provided by GSF. The language plugin implements two services:
As you can see, GSF provides implementations for a lot of the UI and interactions that you need for deep editing support for your language. You implement your lexer, parser, and feature implementations like code completion, go to declaration, quickfixes etc. based on analyzing your own parse trees. You talk through feature specific APIs to GSF, and GSF does the rest.
Here's a rough architecture diagram for GSF:
As you can see, language plugins talk mostly through the GSF APIs
to implement their features. GSF is in turn implemented in many cases
on top of existing NetBeans APIs. In some cases, the abstraction on
top of existing APIs (such as the Hyperlink API) is very thin. In other
cases, such as for quickfixes, mark occurrences or semantic highlighting,
GSF provides a lot of UI implementation under the hood on top of the
existing APIs. You might wonder why GSF should bother with features
such as code completion and hyperlinking when the existing APIs are
pretty complete. There are several reasons for this:
Furthermore, for many actions, there is a LOT of code behind the scenes that is not language specific. Take mark occurrences for example. The only language specific thing there is determining, for a given offset, what the other corresponding occurrences are in terms of editor offsets. Everything else: ensuring that the parse information is up to date, listening on caret changes, painting highlights for the occurrences, defining and implementing "goto previous occurrence" and "goto next occurrence", and so on, should all be implemented in just one shared place.
One thing which is not obvious from the diagram above is that clients are free to use NetBeans APIs directly. For example, in NetBeans 6.1, the HTML module uses GSF for parsing, navigator, embedding etc. - but it registers its own CompletionProvider using the NetBeans APIs instead of GSF's code completion handler interface. It is possible to combine GSF with for example Schliemann or a custom written editor kit or custom written data loaders. More details about this are found in the custom editor kit section.
One of the key principles of GSF is to keep all UI in GSF. In the old days, each language support would define all its own logical editor types, color definitions, and so on. That made it really tricky to provide editor themes, as well as keep things consistent. A literal string may have one color in one file type, and another color in another filetype.
This has some implications for GSF:
JavaSource.runUserActionTask()
).
This lets modules create arbitrary features for Java - and this
is how the various Java modules (navigation, hints, etc)
operate.
SourceModel
class, but you're discouraged
from using it).
getIcon()
method, where you normally return null,
but you can override the icon there. This is how I return a
Ruby specific icon for Ruby keywords in code completion (and
ditto for JavaScript). But overriding UI is the exception, not
the norm.
 These are invoked at appropriate times by the infrastructure. There are two types of callbacks:
GSF uses the Lexer API in NetBeans directly. All GSF languages must provide a Lexer language. It must also be registered in the Editors mime folder. See the Registration section for more details.
GSF provides a parser interface. You can register a parser, and GSF will call your parser when needed.
NOTE: There is a new Parsing API underway. This will be something equivalent to the Lexer API, but applied to parsing. The plan is for GSF to remove its own Parser registration and interfaces and replace it with the standard Parser API. This will allow embedding and coordination not just among GSF-based languages, but for all languages that implement the parsing API (such as Java, and C/C++, which are not GSF based).
The Parser API basically just asks you to parse a given CharSequence, and return the result as your own subclass of the ParserResult interface. It is in your own parser result that you store your own AST reference. You will probably need it to implement most of the features. There is a separate document describing the parsing aspects of GSF. (Eventually you'll also want to implement incremental parsing.)
Indexing lets you register a service which will extract information from your parse results, and store them in an index which can be queried quickly later. Your indexer will be called "at the right times" by the infrastructure:
To implement semantic highlighting, you need to
register an implementation of the
SemanticAnalyzer interface.
You will be given your own ParserResult
object, and
you need to return a Map<OffsetRange, Set<ColoringAttributes>>
.
So, you'll iterate your own AST, look for things to highlight, such as
method definitions, parameters and unused variables, and for each node,
look up its source offsets (start, end integer offsets in the document),
and then place them in the document:
// Aha, this is an unused variable reference! int nodeStart = node.getStartOffset(); int nodeEnd = node.getEndOffset(); result.put(new OffsetRange(nodeStart, nodeEnd), ColoringAttribute.UNUSED_SET);Mark Occurrences is very similar to this. You implement the OccurrencesFinder interface, where you return a Set<OffsetRange> for the symbols that should be highlighted as other occurrences of the symbol at the given offset.
TODO: I plan to write some documents explaining how to do keystroke handling, formatting, declaration finding, code completion, etc.
GSF services, such as the lexer, parser, and feature implementations, must all be registered with the GSF infrastructure. For details on how to do this, see the Registration document.
GSF supports language embedding - supporting nested languages, like JavaScript and CSS support inside HTML files, Ruby support (and JavaScript and CSS support) inside ERb/RHTML files, and so on. The mechanism of how this works is described fully in the embedding document.
There is a separate module in the contrib repository, gsf.tools
,
which provides a number of tools in the Tools | GSF Development menu.
Details are described in the GSF Development Tools document.
GSF makes it really easy to unit test your feature implementations. Details on how to do this is described in the unit testing document.
I will describe the various GSF limitations here. For now, they are
listed (in very brief form) in the following Wiki page:
http://wiki.netbeans.org/GsfIssues


REAT: Regional Economic Analysis Toolbox
Collection of models and analysis methods used in regional and urban economics and (quantitative) economic geography, e.g. measures of inequality, regional disparities and convergence, regional specialization as well as accessibility and spatial interaction models.
| Version: |
2.2.0 |
| Published: |
2018-11-29 |
| Author: |
Thomas Wieland |
| Maintainer: |
Thomas Wieland <thomas.wieland.geo at googlemail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
REAT results |
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=REAT
to link to this page.


Machine learning is the science of giving computers the ability to learn without being explicitly programmed. The idea is that there exist generic algorithms which can be used to find patterns in a broad class of data sets without having to write code specifically for each problem. The algorithm will build its own logic based on the data.
Machine learning is a subfield of computer science, and is closely related to computational statistics. It evolved from the study of pattern recognition in artificial intelligence (AI) research, and has made contributions to AI tasks like computer vision, natural language processing and speech recognition. It has also, especially in later years, found applications in a wide variety of other areas, including bioinformatics, economy, physics, finance and marketing.
The approaches to machine learning are many, but are often split into two main categories. In supervised learning we know the answer to a problem, and let the computer deduce the logic behind it. On the other hand, unsupervised learning is a method for finding patterns and relationship in data sets without any prior knowledge of the system. Some authours also operate with a third category, namely reinforcement learning. This is a paradigm of learning inspired by behavioural psychology, where learning is achieved by trial-and-error, solely from rewards and punishment.
Another way to categorize machine learning tasks is to consider the desired output of a system. Some of the most common tasks are:
This behaviour has inspired a simple mathematical model for an artificial neuron. $$ \begin{equation} y = f\left(\sum_{i=1}^n w_ix_i\right) = f(u) \label{artificialNeuron} \end{equation} $$ Here, the output \( y \) of the neuron is the value of its activation function, which have as input a weighted sum of signals \( x_i, \dots ,x_n \) received by \( n \) other neurons.
An artificial neural network (NN), is a computational model that consists of layers of connected neurons, or nodes. It is supposed to mimic a biological nervous system by letting each neuron interact with other neurons by sending signals in the form of mathematical functions between layers. A wide variety of different NNs have been developed, but most of them consist of an input layer, an output layer and eventual layers in-between, called hidden layers. All layers can contain an arbitrary number of nodes, and each connection between two nodes is associated with a weight variable.
Nodes are represented by circles, while the arrows display the connections between the nodes, including the direction of information flow. Additionally, each arrow corresponds to a weight variable, not displayed here. We observe that each node in a layer is connected to all nodes in the subsequent layer, making this a so-called fully-connected FFNN.
A different variant of FFNNs are convolutional neural networks (CNNs), which have a connectivity pattern inspired by the animal visual cortex. Individual neurons in the visual cortex only respond to stimuli from small sub-regions of the visual field, called a receptive field. This makes the neurons well-suited to exploit the strong spatially local correlation present in natural images. The response of each neuron can be approximated mathematically as a convolution operation.
CNNs emulate the behaviour of neurons in the visual cortex by enforcing a local connectivity pattern between nodes of adjacent layers: Each node in a convolutional layer is connected only to a subset of the nodes in the previous layer, in contrast to the fully-connected FFNN. Often, CNNs consist of several convolutional layers that learn local features of the input, with a fully-connected layer at the end, which gathers all the local data and produces the outputs. They have wide applications in image and video recognition
So far we have only mentioned NNs where information flows in one direction: forward. Recurrent neural networks on the other hand, have connections between nodes that form directed cycles. This creates a form of internal memory which are able to capture information on what has been calculated before; the output is dependent on the previous computations. Recurrent NNs make use of sequential information by performing the same task for every element in a sequence, where each element depends on previous elements. An example of such information is sentences, making recurrent NNs especially well-suited for handwriting and speech recognition.
There are many other kinds of NNs that have been developed. One type that is specifically designed for interpolation in multidimensional space is the radial basis function (RBF) network. RBFs are typically made up of three layers: an input layer, a hidden layer with non-linear radial symmetric activation functions and a linear output layer (''linear'' here means that each node in the output layer has a linear activation function). The layers are normally fully-connected and there are no cycles, thus RBFs can be viewed as a type of fully-connected FFNN. They are however usually treated as a separate type of NN due the unusual activation functions.
Other types of NNs could also be mentioned, but are outside the scope of this work. We will now move on to a detailed description of how a fully-connected FFNN works, and how it can be used to interpolate data sets.
One use often so-called fully-connected feed-forward neural networks with three or more layers (an input layer, one or more hidden layers and an output layer) consisting of neurons that have non-linear activation functions.
Such networks are often called multilayer perceptrons (MLPs)
According to the Universal approximation theorem, a feed-forward neural network with just a single hidden layer containing a finite number of neurons can approximate a continuous multidimensional function to arbitrary accuracy, assuming the activation function for the hidden layer is a non-constant, bounded and monotonically-increasing continuous function. Note that the requirements on the activation function only applies to the hidden layer, the output nodes are always assumed to be linear, so as to not restrict the range of output values.
We note that this theorem is only applicable to a NN with one hidden layer. Therefore, we can easily construct an NN that employs activation functions which do not satisfy the above requirements, as long as we have at least one layer with activation functions that do. Furthermore, although the universal approximation theorem lays the theoretical foundation for regression with neural networks, it does not say anything about how things work in practice: A neural network can still be able to approximate a given function reasonably well without having the flexibility to fit all other functions.
First, for each node \( i \) in the first hidden layer, we calculate a weighted sum \( u_i^1 \) of the input coordinates \( x_j \), $$ \begin{equation} u_i^1 = \sum_{j=1}^2 w_{ij}^1 x_j + b_i^1 \label{_auto1} \end{equation} $$ This value is the argument to the activation function \( f_1 \) of each neuron \( i \), producing the output \( y_i^1 \) of all neurons in layer 1, $$ \begin{equation} y_i^1 = f_1(u_i^1) = f_1\left(\sum_{j=1}^2 w_{ij}^1 x_j + b_i^1\right) \label{outputLayer1} \end{equation} $$ where we assume that all nodes in the same layer have identical activation functions, hence the notation \( f_l \) $$ \begin{equation} y_i^l = f_l(u_i^l) = f_l\left(\sum_{j=1}^{N_{l-1}} w_{ij}^l y_j^{l-1} + b_i^l\right) \label{generalLayer} \end{equation} $$ where \( N_l \) is the number of nodes in layer \( l \). When the output of all the nodes in the first hidden layer are computed, the values of the subsequent layer can be calculated and so forth until the output is obtained.
The output of neuron \( i \) in layer 2 is thus, $$ \begin{align} y_i^2 &= f_2\left(\sum_{j=1}^3 w_{ij}^2 y_j^1 + b_i^2\right) \label{_auto2}\\ &= f_2\left[\sum_{j=1}^3 w_{ij}^2f_1\left(\sum_{k=1}^2 w_{jk}^1 x_k + b_j^1\right) + b_i^2\right] \label{outputLayer2} \end{align} $$ where we have substituted \( y_m^1 \) with.  The complete functional form is, $$ \begin{align} &y^{l+1}_1\! = \!f_{l+1}\!\left[\!\sum_{j=1}^{N_l}\! w_{1j}^3 f_l\!\left(\!\sum_{k=1}^{N_{l-1}}\! w_{jk}^2 f_{l-1}\!\left(\! \dots \!f_1\!\left(\!\sum_{n=1}^{N_0} \!w_{mn}^1 x_n\! + \!b_m^1\!\right) \!\dots \!\right) \!+ \!b_k^2\!\right) \!+ \!b_1^3\!\right] && \label{completeNN} \end{align} $$ which illustrates a basic property of MLPs: The only independent variables are the input values \( x_n \).
This confirms that an MLP, despite its quite convoluted mathematical form, is nothing more than an analytic function, specifically a mapping of real-valued vectors \( \vec{x} \in \mathbb{R}^n \rightarrow \vec{y} \in \mathbb{R}^m \). In our example, \( n=2 \) and \( m=1 \). Consequentially, the number of input and output values of the function we want to fit must be equal to the number of inputs and outputs of our MLP.
Furthermore, the flexibility and universality of a MLP can be illustrated by realizing that the expression is essentially a nested sum of scaled activation functions of the form $$ \begin{equation} h(x) = c_1 f(c_2 x + c_3) + c_4 \label{_auto5} \end{equation} $$ where the parameters \( c_i \) are weights and biases. By adjusting these parameters, the activation functions can be shifted up and down or left and right, change slope or be rescaled which is the key to the flexibility of a neural network.
Additionally, we can represent the biases and activations as layer-wise column vectors \( \vec{b}_l \) and \( \vec{y}_l \), so that the \( i \)-th element of each vector is the bias \( b_i^l \) and activation \( y_i^l \) of node \( i \) in layer \( l \) respectively.
We have that \( \mathrm{W}_l \) is a \( N_{l-1} \times N_l \) matrix, while \( \vec{b}_l \) and \( \vec{y}_l \) are \( N_l \times 1 \) column vectors. With this notation, the sum in becomes a matrix-vector multiplication, and we can write the equation for the activations of hidden layer 2 in $$ \begin{equation} \vec{y}_2 = f_2(\mathrm{W}_2 \vec{y}_{1} + \vec{b}_{2}) = f_2\left(\left[\begin{array}{ccc} w^2_{11} &w^2_{12} &w^2_{13} \\ w^2_{21} &w^2_{22} &w^2_{23} \\ w^2_{31} &w^2_{32} &w^2_{33} \\ \end{array} \right] \cdot \left[\begin{array}{c} y^1_1 \\ y^1_2 \\ y^1_3 \\ \end{array}\right] + \left[\begin{array}{c} b^2_1 \\ b^2_2 \\ b^2_3 \\ \end{array}\right]\right). \label{_auto6} \end{equation} $$
A property that characterizes a neural network, other than its connectivity, is the choice of activation function(s). As described in, the following restrictions are imposed on an activation function for a FFNN to fulfill the universal approximation theorem
The second requirement excludes all linear functions. Furthermore, in a MLP with only linear activation functions, each layer simply performs a linear transformation of its inputs.
Regardless of the number of layers, the output of the NN will be nothing but a linear function of the inputs. Thus we need to introduce some kind of non-linearity to the NN to be able to fit non-linear functions Typical examples are the logistic Sigmoid $$ \begin{equation} f(x) = \frac{1}{1 + e^{-x}}, \label{sigmoidActivationFunction} \end{equation} $$ and the hyperbolic tangent function $$ \begin{equation} f(x) = \tanh(x) \label{tanhActivationFunction} \end{equation} $$
Why use a generative ("dreaming") model rather than the more well known discirminative deep neural networks (DNN)?
The network layers:
The goal of the hidden layer is to increase the model's expressive power. We encode complex interactions between visible variables by introducing additional, hidden variables that interact with visible degrees of freedom in a simple manner, yet still reproduce the complex correlations between visible degrees in the data once marginalized over (integrated out).
Examples of this trick being employed in physics:
The function \( E(\mathbf{x},\mathbf{h}) \) gives the energy of a configuration (pair of vectors) \( (\mathbf{x}, \mathbf{h}) \). The lower the energy of a configuration, the higher the probability of it. This function also depends on the parameters \( \mathbf{a} \), \( \mathbf{b} \) and \( W \). Thus, when we adjust them during the learning procedure, we are adjusting the energy function to best fit our problem.
RBMs were first developed using binary units in both the visible and hidden layer. The corresponding energy function is defined as follows: $$ \begin{align} E(\mathbf{x}, \mathbf{h}) = - \sum_i^M x_i a_i- \sum_j^N b_j h_j - \sum_{i,j}^{M,N} x_i w_{ij} h_j, \label{_auto10} \end{align} $$ where the binary values taken on by the nodes are most commonly 0 and 1.
Another varient is the RBM where the visible units are Gaussian while the hidden units remain binary: $$ \begin{align} E(\mathbf{x}, \mathbf{h}) = \sum_i^M \frac{(x_i - a_i)^2}{2\sigma_i^2} - \sum_j^N b_j h_j - \sum_{i,j}^{M,N} \frac{x_i w_{ij} h_j}{\sigma_i^2}. \label{_auto11} \end{align} $$
Metropolis sampling starts by suggesting a new configuration \( \boldsymbol{x}^{k+1} \). In the brute force method this is done by some random change of the visible units. The new configuration is then accepted with the acceptance probability $$ \begin{align} A(\boldsymbol{x}^k \rightarrow \boldsymbol{x}^{k+1}) = \text{min} (1, \frac{P(\boldsymbol{x}^{k+1})}{P(\boldsymbol{x}^k)}), \label{_auto12} \end{align} $$ where we need the marginalized probability $$ \begin{align} P(\boldsymbol{x}) &= \sum_\mathbf{h} P_{rbm}(\mathbf{x}, \mathbf{h}) \label{_auto13}\\ &= \frac{1}{Z}\sum_\mathbf{h} e^{-E(\mathbf{x}, \mathbf{h})}. \label{_auto14} \end{align} $$
In this method we sample from the joint probability \( P_{rbm} (\mathbf{x}, \mathbf{h}) \) by way of a two step sampling process. We alternately update the visible and hidden units. New samples are generated according to the conditional probabilities \( P(x_i|\mathbf{h}) \) and \( P(h_j|\mathbf{x}) \) respectively and accepted with the probability of \( 1 \). While the the visible nodes are dependent on the hidden nodes and vice versa, the nodes are independent of other nodes within the same layer. This is due to there being no intra layer interactions in the restricted Boltzmann machine.
The conditional probabilities are often referred to as the activitation functions in the neural networks context due to their role in determining the node outputs. For the binary-binary RBM they are $$ \begin{align} P(h_j = 1 | \boldsymbol{x}) &= \frac{1}{1 + e^{-b_j - \sum_i x_i w_{ij}}} \label{_auto15}\\ P(x_i = 1 | \boldsymbol{h}) &= \frac{1}{1 + e^{-a_j - \sum_j h_j w_{ij}}}, \label{_auto16} \end{align} $$ where we recognize the logistic sigmoid function \( \sigma (x) = 1/(1+exp(-x)) \).
We now need the gradient of the cost function in order to minimize it. We find that $$ \begin{align} \frac{\partial \mathcal{C}(\{ \theta_i\})}{\partial \theta_i} &= \langle \frac{\partial E(\boldsymbol{x}; \theta_i)}{\partial \theta_i} \rangle_{data} + \frac{\partial \text{log} Z(\{ \theta_i\})}{\partial \theta_i} \label{_auto22}\\ &= \langle O_i(\boldsymbol{x}) \rangle_{data} - \langle O_i(\boldsymbol{x}) \rangle_{model}, \label{_auto23} \end{align} $$ where in order to simplify notation we defined the "operator" $$ \begin{align} O_i(\boldsymbol{x}) = \frac{\partial E(\boldsymbol{x}; \theta_i)}{\partial \theta_i}, \label{_auto24} \end{align} $$ and used the statistical mechanics relationship between expectation values and the log-partition function: $$ \begin{align} \langle O_i(\boldsymbol{x}) \rangle_{model} = \text{Tr} P_\theta(\boldsymbol{x})O_i(\boldsymbol{x}) = - \frac{\partial \text{log} Z(\{ \theta_i\})}{\partial \theta_i}. \label{_auto25} \end{align} $$
The gradient of the negative log-likelihood cost function of a Binary-Binary RBM is then $$ \begin{align} \frac{\partial \mathcal{C} (w_{ij}, a_i, b_j)}{\partial w_{ij}} =& \langle x_i h_j \rangle_{data} - \langle x_i h_j \rangle_{model} \label{_auto26}\\ \frac{\partial \mathcal{C} (w_{ij}, a_i, b_j)}{\partial a_{ij}} =& \langle x_i \rangle_{data} - \langle x_i \rangle_{model} \label{_auto27}\\ \frac{\partial \mathcal{C} (w_{ij}, a_i, b_j)}{\partial b_{ij}} =& \langle h_i \rangle_{data} - \langle h_i \rangle_{model}. \label{_auto28}\\ \label{_auto29} \end{align} $$ To get the expecation values with respect to the \textit{data}, we set the visible units to each of the observed samples in the training data, then update the hidden units according to the conditional probability found before. We then average over all samples in the training data to calculate expectation values with respect to the data.
Some of their motivation included
Carleo and Troyer applied the RBM to the quantum mechanical spin lattice systems of the Ising model and Heisenberg model, with encouraging results. Our goal is to test the method on systems of moving particles. For the spin lattice systems it was natural to use a binary-binary RBM, with the nodes taking values of 1 and -1. For moving particles, on the other hand, we want the visible nodes to be continuous, representing position coordinates. Thus, we start by choosing a Gaussian-binary RBM, where the visible nodes are continuous and hidden nodes take on values of 0 or 1. If eventually we would like the hidden nodes to be continuous as well the rectified linear units seem like the most relevant choice.


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