नेब्रास्का मराठी मंडळ
(NMM) started with an objective to celebrate and practice marathi culture with Nebraska's Indian community. Few families came with a thought of bringing people together, and with their planning, NMM was officially formed on Sept 6th 2014.
NMM was registered with State of Nebraska as a non profit organization in Jan 2015. NMM is also affiliated with BMM (Bruhan Maharashtra Mandal) of North America. Year 2015 started with celebrating various events and also Ganesh festival in Hindu Temple.
Year 2016 started with new participative leadership, and board focused on the Community, Culture and Nature (Environment). 'GO GREEN': the care for environment, is the most top achievement that received endorsement from all. Nebraska Marathi Mandal with community help raised fund and took full responsibility for Ganesh Utsav celebration at Hindu temple of Omaha with use of Bio-degradable.  Diwali Dhamaka was the most active, cultural and exciting program for NMM in 2016. NMM received First prize in Rhythms of India 2016 for presenting and displaying various aspects of Marathi Culture. NMM also participated in 'Siddhi Vinayak Vyas-Puraskar' held in 2016.
Year 2017 started with the vibrant celebration of 'Gudi Padwa' showcasing Maharashtra-chi Lokadhara (महाराष्ट्राची लोकधारा) and cultural display for the auspicious welcome of Marathi New Year. The NMM board's focus is on amendment into NMM bylaws, board members election process and pilot programs along with all yearly events and workshops. BMM 2017 Convention Participation is another accomplishment.Support of community people, encouraged to establish the organization 'तुमचं आमचं सर्वांचं नेब्रास्का मराठी मंडळ'. NMM is proud of its members, volunteers and people for their inspiration to enable to serve community and culture, alongwith the 'GO GREEN' initiative to protect nature.
| Name |
|---|
| Vijay and Chhaya Gayee |
| Prashant and Supriya Deshmukh |
| Devendra and Priyanwada Athalye |
| Avdhoot and Prachi Paranjape |
| Jitendra and Sanchali Pandit |
| Bhushan and Sneha Vairagade |


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Gecode::ProjectorPropagatorSpec Class Reference
#include <projectors-compiler.hh>
Detailed Description
Specification for a C++ finite set propagator.
Definition at line 33 of file projectors-compiler.hh.
Public Attributes | |
| std::string | _name |
| The name of the propagator. | |
| std::string | _namespace |
| The namespace to place the propagator in. | |
| int | _arity |
| Arity of the generated propagator, 0 meaning n-ary. | |
| bool | _reified |
| Whether this propagator is reified. | |
| bool | _negated |
| Whether this propagator is negated. | |
| ProjectorSet | _ps |
Member Data Documentation
|
|
The name of the propagator.
Definition at line 36 of file projectors-compiler.hh. |
|
|
The namespace to place the propagator in.
Definition at line 38 of file projectors-compiler.hh. |
|
|
Arity of the generated propagator, 0 meaning n-ary.
Definition at line 41 of file projectors-compiler.hh. |
|
|
Whether this propagator is reified.
Definition at line 43 of file projectors-compiler.hh. |
|
|
Whether this propagator is negated.
Definition at line 45 of file projectors-compiler.hh. |
|
|
Definition at line 47 of file projectors-compiler.hh. |
The documentation for this class was generated from the following file:
- gecode/set/projectors-compiler.hh (Revision: 3188)


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Define a class across XML, SQL, and Java.
| Attribute | Description | Required |
| name | the fully-qualified name of the class (in Java). | Yes |
| identity | field-name for primary key in database | Yes if a database class ('-factories' is turned on) |
| extends | a java class to extend - must be a class specified in a map-file (or org.ephman.abra.utils.Versioned | Identified). | No |
| implements | a comma seperated list of fully-qualified Java classes to implement. | No |
| descendant | a hand-written class that will extend this one - tells the generated factory to create the instances of 'descendant' using the generic constructor. | No |
| end-date | boolean specifying if end-dateing should be used instead of deleting (Column END_DATE will be added and given a timestamp on delete instead of deleting row). | No (Database-only) |
| cache-type | if set to 'persistent' keep objects cached-indefinitely (Identfied) these are static-data classes; otherwise extend Versioned and do in transaction cache only. | No (will default to 'transacted' and become a Versioned object) |
| abstract | boolean to make this class abstract. | No |
| many-to-many | boolean to make this class define a many-to-many relationship. Special case where exactly 2 nested field expected each a database class in the map-file. | No |
the map-to node specifies table-names and xml-node names for mapping
the class-view node allows description of data abstractions where mapping/translation can be generated. The <view> tag is used on a field-by-field basis to specify which fields belong in a view. A class may have multiple class-views.
The constraint node describes an sql constraint which exists on a set of fields.
The repeating field node describes a field.
Copyright © 2000,2001,2002 Paul Bethe and Richie Bielak. All rights Reserved.


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| stamina | 14 |
| attack | 12 |
| defense | 11 |
| name | Tangela |
| cp | 962 |
| stamina | 14 |
| attack | 10 |
| defense | 12 |
| name | Nidoran ♂ |
| cp | 453 |
| stamina | 9 |
| attack | 15 |
| defense | 10 |
| name | Abra |
| cp | 365 |
| stamina | 10 |
| attack | 9 |
| defense | 7 |
| name | Nidoking |
| cp | 1492 |
| stamina | 15 |
| attack | 15 |
| defense | 14 |
| name | Grimer |
| cp | 730 |
| stamina | 14 |
| attack | 15 |
| defense | 11 |
| name | Charmander |
| cp | 533 |
| stamina | 14 |
| attack | 12 |
| defense | 13 |
| name | Parasect |
| cp | 1069 |
| stamina | 6 |
| attack | 7 |
| defense | 5 |
| name | Spearow |
| cp | 328 |
| stamina | 11 |
| attack | 11 |
| defense | 15 |
| name | Zubat |
| cp | 414 |
| stamina | 13 |
| attack | 13 |
| defense | 10 |
| name | Starmie |
| cp | 1210 |
| stamina | 9 |
| attack | 7 |
| defense | 9 |
| name | Shellder |
| cp | 310 |
| stamina | 3 |
| attack | 8 |
| defense | 12 |
| name | Machoke |
| cp | 645 |
| stamina | 13 |
| attack | 10 |
| defense | 11 |
| name | Marowak |
| cp | 901 |
| stamina | 9 |
| attack | 7 |
| defense | 14 |
| name | Rattata |
| cp | 176 |
| stamina | 10 |
| attack | 15 |
| defense | 13 |
| name | Porygon |
| cp | 849 |
| stamina | 11 |
| attack | 15 |
| defense | 10 |
| name | Pinsir |
| cp | 649 |
| stamina | 3 |
| attack | 3 |
| defense | 13 |
| name | Pidgey |
| cp | 304 |
| stamina | 8 |
| attack | 10 |
| defense | 8 |
| name | Nidoran ♂ |
| cp | 259 |
| stamina | 11 |
| attack | 12 |
| defense | 11 |
| name | Tentacruel |
| cp | 1008 |
| stamina | 1 |
| attack | 15 |
| defense | 4 |
| name | Flareon |
| cp | 1394 |
| stamina | 13 |
| attack | 11 |
| defense | 12 |
| name | Cubone |
| cp | 545 |
| stamina | 3 |
| attack | 15 |
| defense | 2 |
| name | Exeggcute |
| cp | 486 |
| stamina | 14 |
| attack | 12 |
| defense | 15 |
| name | Vulpix |
| cp | 460 |
| stamina | 1 |
| attack | 15 |
| defense | 15 |
| name | Koffing |
| cp | 638 |
| stamina | 15 |
| attack | 13 |
| defense | 8 |
| name | Venomoth |
| cp | 1150 |
| stamina | 11 |
| attack | 15 |
| defense | 11 |
| name | Electabuzz |
| cp | 1180 |
| stamina | 13 |
| attack | 15 |
| defense | 13 |
| name | Golduck |
| cp | 1348 |
| stamina | 6 |
| attack | 14 |
| defense | 11 |
| name | Primeape |
| cp | 1115 |
| stamina | 15 |
| attack | 11 |
| defense | 4 |
| name | Kadabra |
| cp | 542 |
| stamina | 1 |
| attack | 14 |
| defense | 3 |
| name | Venonat |
| cp | 447 |
| stamina | 6 |
| attack | 2 |
| defense | 1 |
| name | Pidgey |
| cp | 212 |
| stamina | 7 |
| attack | 9 |
| defense | 1 |
| name | Geodude |
| cp | 229 |
| stamina | 1 |
| attack | 2 |
| defense | 6 |
| name | Pidgey |
| cp | 103 |
| stamina | 14 |
| attack | 15 |
| defense | 15 |
| name | Machamp |
| cp | 1256 |
| stamina | 6 |
| attack | 13 |
| defense | 15 |
| name | Onix |
| cp | 477 |
| stamina | 10 |
| attack | 1 |
| defense | 15 |
| name | Pidgeotto |
| cp | 711 |
| stamina | 1 |
| attack | 2 |
| defense | 7 |
| name | Pidgey |
| cp | 227 |
| stamina | 11 |
| attack | 14 |
| defense | 15 |
| name | Growlithe |
| cp | 215 |
| stamina | 12 |
| attack | 14 |
| defense | 15 |
| name | Kakuna |
| cp | 269 |
| stamina | 10 |
| attack | 12 |
| defense | 11 |
| name | Abra |
| cp | 283 |
| stamina | 13 |
| attack | 14 |
| defense | 14 |
| name | Tentacool |
| cp | 505 |
| stamina | 7 |
| attack | 4 |
| defense | 4 |
| name | Pidgey |
| cp | 316 |
| stamina | 15 |
| attack | 2 |
| defense | 15 |
| name | Fearow |
| cp | 973 |
| stamina | 14 |
| attack | 4 |
| defense | 6 |
| name | Pidgey |
| cp | 113 |
| stamina | 11 |
| attack | 10 |
| defense | 15 |
| name | Sandshrew |
| cp | 427 |
| stamina | 13 |
| attack | 14 |
| defense | 15 |
| name | Weedle |
| cp | 250 |
| stamina | 15 |
| attack | 13 |
| defense | 15 |
| name | Charmeleon |
| cp | 879 |
| stamina | 6 |
| attack | 4 |
| defense | 5 |
| name | Slowbro |
| cp | 103 |
| stamina | 8 |
| attack | 12 |
| defense | 5 |
| name | Paras |
| cp | 259 |
| stamina | 2 |
| attack | 15 |
| defense | 1 |
| name | Flareon |
| cp | 1249 |
| stamina | 13 |
| attack | 11 |
| defense | 15 |
| name | Electabuzz |
| cp | 1179 |
| stamina | 9 |
| attack | 3 |
| defense | 7 |
| name | Poliwhirl |
| cp | 299 |
| stamina | 12 |
| attack | 13 |
| defense | 8 |
| name | Geodude |
| cp | 320 |
| stamina | 4 |
| attack | 10 |
| defense | 1 |
| name | Raichu |
| cp | 1116 |
| stamina | 10 |
| attack | 13 |
| defense | 15 |
| name | Staryu |
| cp | 510 |
| stamina | 11 |
| attack | 6 |
| defense | 3 |
| name | Rattata |
| cp | 250 |
| stamina | 11 |
| attack | 12 |
| defense | 12 |
| name | Clefairy |
| cp | 654 |
| stamina | 10 |
| attack | 12 |
| defense | 15 |
| name | Doduo |
| cp | 533 |
| stamina | 14 |
| attack | 15 |
| defense | 13 |
| name | Jolteon |
| cp | 1151 |
| stamina | 11 |
| attack | 10 |
| defense | 12 |
| name | Beedrill |
| cp | 661 |
| stamina | 7 |
| attack | 3 |
| defense | 4 |
| name | Pidgeot |
| cp | 1005 |
| stamina | 10 |
| attack | 12 |
| defense | 4 |
| name | Meowth |
| cp | 408 |
| stamina | 13 |
| attack | 12 |
| defense | 14 |
| name | Omanyte |
| cp | 524 |
| stamina | 15 |
| attack | 10 |
| defense | 10 |
| name | Arbok |
| cp | 1113 |
| stamina | 3 |
| attack | 13 |
| defense | 15 |
| name | Magikarp |
| cp | 140 |
| stamina | 14 |
| attack | 3 |
| defense | 12 |
| name | Pidgey |
| cp | 271 |
| stamina | 12 |
| attack | 11 |
| defense | 11 |
| name | Kabutops |
| cp | 1168 |
| stamina | 14 |
| attack | 11 |
| defense | 14 |
| name | Hitmonlee |
| cp | 950 |
| stamina | 7 |
| attack | 9 |
| defense | 8 |
| name | Geodude |
| cp | 322 |
| stamina | 7 |
| attack | 15 |
| defense | 15 |
| name | Rhydon |
| cp | 1070 |
| stamina | 6 |
| attack | 13 |
| defense | 3 |
| name | Paras |
| cp | 419 |
| stamina | 13 |
| attack | 11 |
| defense | 4 |
| name | Meowth |
| cp | 372 |
| stamina | 12 |
| attack | 12 |
| defense | 14 |
| name | Magnemite |
| cp | 485 |
| stamina | 10 |
| attack | 12 |
| defense | 15 |
| name | Slowpoke |
| cp | 670 |
| stamina | 7 |
| attack | 6 |
| defense | 5 |
| name | Rattata |
| cp | 232 |
| stamina | 15 |
| attack | 12 |
| defense | 15 |
| name | Poliwag |
| cp | 443 |
| stamina | 15 |
| attack | 8 |
| defense | 15 |
| name | Ekans |
| cp | 356 |
| stamina | 15 |
| attack | 14 |
| defense | 14 |
| name | Horsea |
| cp | 403 |
| stamina | 11 |
| attack | 11 |
| defense | 11 |
| name | Dragonair |
| cp | 951 |
| stamina | 2 |
| attack | 15 |
| defense | 6 |
| name | Hitmonchan |
| cp | 146 |
| stamina | 12 |
| attack | 2 |
| defense | 2 |
| name | Pidgey |
| cp | 107 |
| stamina | 12 |
| attack | 13 |
| defense | 7 |
| name | Persian |
| cp | 933 |
| stamina | 14 |
| attack | 13 |
| defense | 14 |
| name | Poliwrath |
| cp | 1692 |
| stamina | 4 |
| attack | 14 |
| defense | 3 |
| name | Growlithe |
| cp | 757 |
| stamina | 13 |
| attack | 13 |
| defense | 12 |
| name | Weedle |
| cp | 243 |
| stamina | 9 |
| attack | 15 |
| defense | 8 |
| name | Rapidash |
| cp | 157 |
| stamina | 4 |
| attack | 1 |
| defense | 1 |
| name | Pidgey |
| cp | 132 |
| stamina | 10 |
| attack | 15 |
| defense | 5 |
| name | Arcanine |
| cp | 1885 |
| stamina | 8 |
| attack | 1 |
| defense | 12 |
| name | Pidgey |
| cp | 369 |
| stamina | 13 |
| attack | 15 |
| defense | 14 |
| name | Staryu |
| cp | 526 |
| stamina | 13 |
| attack | 7 |
| defense | 4 |
| name | Spearow |
| cp | 220 |
| stamina | 13 |
| attack | 1 |
| defense | 7 |
| name | Arbok |
| cp | 904 |
| stamina | 14 |
| attack | 11 |
| defense | 13 |
| name | Primeape |
| cp | 1033 |
| stamina | 4 |
| attack | 9 |
| defense | 15 |
| name | Arbok |
| cp | 1029 |
| stamina | 14 |
| attack | 14 |
| defense | 12 |
| name | Hitmonlee |
| cp | 837 |
| stamina | 10 |
| attack | 11 |
| defense | 11 |
| name | Pikachu |
| cp | 517 |
| stamina | 3 |
| attack | 10 |
| defense | 11 |
| name | Paras |
| cp | 276 |
| stamina | 13 |
| attack | 14 |
| defense | 10 |
| name | Rhyhorn |
| cp | 326 |
| stamina | 1 |
| attack | 15 |
| defense | 1 |
| name | Rhyhorn |
| cp | 581 |
| stamina | 6 |
| attack | 15 |
| defense | 7 |
| name | Magmar |
| cp | 918 |
| stamina | 15 |
| attack | 6 |
| defense | 13 |
| name | Sandslash |
| cp | 680 |
| stamina | 10 |
| attack | 8 |
| defense | 13 |
| name | Spearow |
| cp | 284 |
| stamina | 13 |
| attack | 15 |
| defense | 12 |
| name | Zubat |
| cp | 358 |
| stamina | 10 |
| attack | 13 |
| defense | 12 |
| name | Nidoran ♀ |
| cp | 475 |
| stamina | 14 |
| attack | 14 |
| defense | 11 |
| name | Gloom |
| cp | 756 |
| stamina | 14 |
| attack | 15 |
| defense | 15 |
| name | Haunter |
| cp | 784 |
| stamina | 12 |
| attack | 14 |
| defense | 11 |
| name | Arcanine |
| cp | 1250 |
| stamina | 7 |
| attack | 10 |
| defense | 3 |
| name | Golbat |
| cp | 1156 |
| stamina | 14 |
| attack | 13 |
| defense | 8 |
| name | Cubone |
| cp | 550 |
| stamina | 11 |
| attack | 15 |
| defense | 15 |
| name | Machop |
| cp | 614 |
| stamina | 5 |
| attack | 7 |
| defense | 12 |
| name | Rattata |
| cp | 51 |
| stamina | 12 |
| attack | 15 |
| defense | 15 |
| name | Fearow |
| cp | 987 |
| stamina | 9 |
| attack | 6 |
| defense | 7 |
| name | Rattata |
| cp | 51 |
| stamina | 7 |
| attack | 7 |
| defense | 4 |
| name | Rattata |
| cp | 205 |
| stamina | 15 |
| attack | 13 |
| defense | 9 |
| name | Geodude |
| cp | 466 |
| stamina | 4 |
| attack | 11 |
| defense | 7 |
| name | Seaking |
| cp | 1134 |
| stamina | 6 |
| attack | 10 |
| defense | 4 |
| name | Graveler |
| cp | 350 |
| stamina | 15 |
| attack | 14 |
| defense | 14 |
| name | Arcanine |
| cp | 1693 |
| stamina | 12 |
| attack | 4 |
| defense | 7 |
| name | Rattata |
| cp | 308 |
| stamina | 9 |
| attack | 5 |
| defense | 11 |
| name | Dugtrio |
| cp | 417 |
| stamina | 4 |
| attack | 15 |
| defense | 6 |
| name | Abra |
| cp | 207 |
| stamina | 4 |
| attack | 13 |
| defense | 6 |
| name | Mankey |
| cp | 245 |
| stamina | 15 |
| attack | 7 |
| defense | 5 |
| name | Magneton |
| cp | 1004 |
| stamina | 13 |
| attack | 15 |
| defense | 7 |
| name | Dratini |
| cp | 511 |
| stamina | 4 |
| attack | 12 |
| defense | 15 |
| name | Paras |
| cp | 62 |
| stamina | 11 |
| attack | 15 |
| defense | 13 |
| name | Caterpie |
| cp | 245 |
| stamina | 14 |
| attack | 12 |
| defense | 15 |
| name | Ekans |
| cp | 457 |
| stamina | 10 |
| attack | 13 |
| defense | 9 |
| name | Paras |
| cp | 63 |
| stamina | 6 |
| attack | 15 |
| defense | 15 |
| name | Arcanine |
| cp | 1623 |
| stamina | 11 |
| attack | 15 |
| defense | 15 |
| name | Sandslash |
| cp | 1021 |
| stamina | 12 |
| attack | 9 |
| defense | 12 |
| name | Fearow |
| cp | 373 |
| stamina | 6 |
| attack | 15 |
| defense | 13 |
| name | Voltorb |
| cp | 453 |
| stamina | 7 |
| attack | 8 |
| defense | 5 |
| name | Machoke |
| cp | 729 |
| stamina | 3 |
| attack | 15 |
| defense | 5 |
| name | Vaporeon |
| cp | 1951 |
| stamina | 10 |
| attack | 11 |
| defense | 13 |
| name | Kakuna |
| cp | 253 |
| stamina | 12 |
| attack | 10 |
| defense | 11 |
| name | Oddish |
| cp | 616 |
| stamina | 2 |
| attack | 13 |
| defense | 5 |
| name | Mankey |
| cp | 482 |
| stamina | 2 |
| attack | 15 |
| defense | 14 |
| name | Eevee |
| cp | 290 |
| stamina | 12 |
| attack | 10 |
| defense | 11 |
| name | Ponyta |
| cp | 820 |
| stamina | 7 |
| attack | 7 |
| defense | 5 |
| name | Tentacruel |
| cp | 1215 |
| stamina | 4 |
| attack | 9 |
| defense | 7 |
| name | Venomoth |
| cp | 934 |
| stamina | 9 |
| attack | 15 |
| defense | 10 |
| name | Exeggcute |
| cp | 14 |
| stamina | 13 |
| attack | 15 |
| defense | 10 |
| name | Kingler |
| cp | 1019 |
| stamina | 15 |
| attack | 14 |
| defense | 14 |
| name | Geodude |
| cp | 479 |
| stamina | 14 |
| attack | 9 |
| defense | 5 |
| name | Ekans |
| cp | 492 |
| stamina | 4 |
| attack | 12 |
| defense | 3 |
| name | Meowth |
| cp | 411 |
| stamina | 2 |
| attack | 9 |
| defense | 7 |
| name | Geodude |
| cp | 332 |
| stamina | 15 |
| attack | 14 |
| defense | 10 |
| name | Krabby |
| cp | 440 |
| stamina | 11 |
| attack | 11 |
| defense | 10 |
| name | Bulbasaur |
| cp | 573 |
| stamina | 6 |
| attack | 6 |
| defense | 6 |
| name | Cloyster |
| cp | 360 |
| stamina | 15 |
| attack | 6 |
| defense | 8 |
| name | Hitmonlee |
| cp | 790 |
| stamina | 12 |
| attack | 15 |
| defense | 14 |
| name | Hitmonchan |
| cp | 246 |
| stamina | 12 |
| attack | 12 |
| defense | 10 |
| name | Squirtle |
| cp | 545 |
| stamina | 15 |
| attack | 14 |
| defense | 10 |
| name | Persian |
| cp | 958 |
| stamina | 7 |
| attack | 15 |
| defense | 8 |
| name | Eevee |
| cp | 580 |
| stamina | 11 |
| attack | 11 |
| defense | 7 |
| name | Diglett |
| cp | 239 |
| stamina | 4 |
| attack | 15 |
| defense | 10 |
| name | Tauros |
| cp | 78 |
| stamina | 10 |
| attack | 13 |
| defense | 10 |
| name | Rapidash |
| cp | 1267 |
| stamina | 14 |
| attack | 10 |
| defense | 14 |
| name | Nidorina |
| cp | 770 |
| stamina | 15 |
| attack | 10 |
| defense | 12 |
| name | Nidoran ♀ |
| cp | 472 |
| stamina | 2 |
| attack | 10 |
| defense | 11 |
| name | Pikachu |
| cp | 442 |
| stamina | 3 |
| attack | 1 |
| defense | 13 |
| name | Pidgey |
| cp | 107 |
| stamina | 11 |
| attack | 11 |
| defense | 12 |
| name | Goldeen |
| cp | 518 |
| stamina | 3 |
| attack | 15 |
| defense | 11 |
| name | Exeggcute |
| cp | 202 |
| stamina | 10 |
| attack | 15 |
| defense | 15 |
| name | Wigglytuff |
| cp | 1233 |
| stamina | 13 |
| attack | 10 |
| defense | 14 |
| name | Seel |
| cp | 539 |
| stamina | 2 |
| attack | 8 |
| defense | 15 |
| name | Spearow |
| cp | 257 |


{{experience.company}} {{experience.location}} {{experience.start_date | date:'MMMM yyyy'}} - {{experience.end_date | date:'MMMM yyyy'}} Company Website{{experience.url}} Role Acquired Skills{{experience.skill}}


BodyPick()
Syntax
Result = BodyPick(#Camera, Picked, x, y, Locked)Description
Simulates a mouse click and starts the manipulate the entity at the specified coordinate.
Parameters
#Camera The camera to use. Picked If #True, the picked body won't be released until a new function call with this parameter sets to #False. It can only have one picked body at the same time. x, y The coordinates, in pixels, of the point. Locked (optional) If sets to #True, the picked body won't be able to freely rotate when moving it. If sets to #False, the body will rotate freely according to body move.
Return value
The #Entity picked, or -1 if no entity are found at these coordinates.
Supported OS
All


"Same same, but different", this Thailish philosophy sums up Bangkok. With so much daily life conducted on the street, there're few cities in the world that reward exploration handsomely as Bangkok. It's never prevented anybody from getting on with Thai people.
Thailand's northern capital is an escape from the whirlwind pace of its southern rival life. Despite the constant arrival of sightseers, this is a place to relax after the chaos of Bangkok and recharge your batteries with fabulous food and leisurely wandering.
Ko Samui is like a well-established Hollywood celebrity: she's outrageously manicured, has lovely blonde tresses. She's been in the tourism business longer than almost any other Thai island, and she's embraced a new generation of resort goers.
Phuket was an island of rubber trees, tin mines and cash-hungry merchants. Today the city is testament to the island’s historical soul. Wander down streets clogged with Sino-Portuguese architecture housing arty coffee shops, and eccentric galleries.
Bustling Krabi Town is majestically situated among angular limestone karsts jutting from the mangroves, but mid-city you’re more likely to be awe-struck by the sheer volume of guesthouses. It's a transport hub and a busy traveller scene continues to evolve.
Sun-scorched Russians in bad knock-off T-shirts, an overwhelming disregard for managed development and a knack for turning the midlife crisis into a full-scale industry make Patong rampant with unintentional comedy.


Hello there! My name is Diego Marcon and I'm a mobile developer working mostly with iOS for the past five years. Today I develop at Globo.com.
I have a Computer Science degree from UFRGS and I'm based in Porto Alegre, Brazil. Below you can find some of the apps I've worked in the past years ;)


Save Big On iOttie & Belkin Wireless Chargers Today
Today, in Amazon's Gold Box Deal of the Day, you'll find a number of great wireless chargers from Belkin and iOttie are on sale up to 35-percent off of its regular price.
These wireless chargers, and other accessories, are going to make for some really great stocking stuffers this holiday season. And what better time to pick them up, than when they are 35-percent off.
It's important to remember that since these are part of Amazon's Gold Box Deal of the Day, that these won't be available for long. And will expire at midnight tonight.
Advertisement
Included in this sale, you'll find the Belkin Boost Up Wireless Charging Pad for just $23.99. There's also the iOttie Easy One Touch 2 Car Mount, on sale for just $11.94. There is also the CD slot version available for the same price of $11.94.
Now if you're looking for a rather cool looking wireless charger, there is also the iOttie Ion Fast Wireless Charger. This is a fabric wireless charger that looks really nice. And it is priced at just $25.97 right now.
There are more than just wireless chargers from Belkin and iOttie included in this sale too. Mophie has a number of battery packs available. This includes the Mophie Powerstation for $27.99. The Mophie Powerstation XXL is priced at $56.50 and there's much more.
Advertisement
This sale isn't just for wireless chargers, there are also a number of battery packs and even USB cables available in this sale. This is a great time to stock up on some Secret Santa and stocking stuffer gifts ahead of the Black Friday rush. That way you'll know you'll have them before the holiday parties.
You can pick up these wireless chargers, battery packs and so much more in Amazon's one day sale by clicking here. Remember these prices will only be good through midnight PST tonight.
Wireless Charger Sale - Amazon
Advertisement


AirGuitar
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Trusted Root Certificate
Enter CRL URLs
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Use PFX/P12 File Use Certificate From IE Certificate Store
Selected Certificate Subject:


Thanks to our amazing developer community, Qlik Branch has grown into a great place to find open source projects that leverage and extend Qlik products. The types of innovative extensions created by developers have far exceeded our expectations and understanding of what is possible with Qlik and the Qlik Associative Engine.
As is often the case with open source, however, deploying these projects to production can be perceived to be risky and difficult, especially for enterprise companies. Our customers also say they’re not sure where they can find high quality partners and developers who can build and support extensions they trust.
Customers and developers alike have expressed a great need to have more transparency into extension security, code stability and overall quality.
We’ve heard the feedback and are happy to announce a new program to address these needs: Qlik’s Trusted Extension Developer (TED) Program. This program will help to identify and vet partners who are active in the development of high quality, commercially viable extensions.
Once they are part of the program, partners will have access to our accreditation process which will ensure their extensions adhere to Qlik’s standards of supported functionality, security and completeness. The accreditation process will also provide useful tools and tests which should make the development process itself easier and safer.
Customers benefit from this program as they will be able to easily find extensions that are production-ready, created by the best of the best extension developers. We’ve been working hard with existing partners like Climber and Vizlib to create a program that will hopefully further ease accelerate extension development and deployment in the future.
To register your interest in being invited to the TED Program, follow these instructions…
And please, feel free to visit Qlik Market for more information on extensions available today.


IQR
Grade Calculator
BY SAQIB ALI
FAST-NU
Enter the average out of 100. If that is not available, just estimate.
ENTER THE ABSOLUTES THAT YOU HAVE SECURED
This tool has been made in accordance of the new grading policy that was introduced by the management of FAST-NU for Spring 2020 Semester.


floodmap.io is a free, crowdsourced flood reporting service originally launched to help communities impacted by Hurricane Harvey. It's the next evolution of the successful U-Flood Project. Start here to practice mapping flooded streets.
The Miami metro area
Fort Lauderdale to Deerfield Beach
Boca Raton to West Palm Beach
Naples to Punta Gorda
The Tampa metro area
The Orlando metro area
The Jacksonville metro area
The Tallahassee metro area
The Savannah metro area
The Charleston metro area


Service Base Costs TOTAL:
from ${{ minMaintenancePrice }} to
${{ totalMaintenancePrice }}
Outright Purchase Price TOTAL:
{{ fmvIndex }} Year Lease (Return) Price TOTAL:
{{ oneOutIndex }} Year Lease to Own Price TOTAL:
from ${{ minDisplayedPrice }} to
${{ totalDisplayedPrice }}


--- layout: post title: Back again. published: true date: 2010-09-01 categories: [] posterous_url: http://blog.hungerandthirstdesign.com/post/1047905729/back-again posterous_slug: post/1047905729/back-again ---
Couple of posts upcoming.
First one will be on a mini-app I’m working on for Hargray. Its just kinda a shout-out to a cool little helper for Textile forms. Hargray peeps needed a quick way to do email blasts, since the Oracle Forms stuff doesn’t give a slick/easy way to format emails. So I got the request to build a simple form for emailing stuff to customers.
Well I’ve become a big fan of Textile. I use it right here for formatting my blog entries right here. Its just a super slick way to format text without the craziness of HTML markup. Plus its a little more intuitive for non-technical users. At first I figured, hey, I’ll just point email creators at the textile formatting guide and they can do all the markup by hand. But lo and behold, I found felttippens Textile-Editor-Helper. It adds a nifty little editor bar with a lot of the markup tools you’d expect to see so that you can simply press the button and it generates the markup for you.
Then I wanted to give the users a way to preview the actual email content before sending, so I created a little helper that does the following
$("#render_preview").click(function (e) { e.preventDefault(); $('.preview').load("preview", {text:$("#email_blast_message").val()}); }); :textile #{@text} def translate @text = params[:text] render "shared/translate" end
Which is a super fast way of ajaxing the text-area text to an ActionController::Metal action, which faster than thought possible, returns the HTML output version of the Textile markup’d text! Its incredibly fast since I’m only using Metal rather than a full ActionController object. Plus its very simple in what it does, so I’m pretty happy with how it worked out.


Here's the deal: Shubhu got her white coat on Aug 15th to celebrate the start of medical coursework at UMKC School of Medicine! Let's bombard her with texts to show our support!


--- layout: default title: API Specification Toolbox ---
This is a toolbox of many specifications, services, tools, people, and other resources. There is a lot of information available here, and it is something that is always expanding. Feel free to sort through all of the information here, or you can just get started with three of the most important specifications to the world of APIs.
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Below is a calendar of containing all regular meetings and offices hours across the specifications. Feel free to jump in!
This project runs on Github allowing this entire directory to be run locally, forked to add information, and update the webite using pull request. We are happy to accept community submisions, and edit are always welcome! The goal of this site i to bring in as much information about the space as posible, then provide tools for filtering out the noise.


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1. Lets getting starting.First you need to register with the messenger. Go to Home Page and open tab 'Register'. Then type your user name and password (two times for confirmation). Your partner needs to register too and to share his/her user name with you. You need to login after registration. Use 'Login' tab for this. After successful login you come to 'Contacts' tab. Now you need to add your partner user name to the contacts list. Type the user name in text box and click button. This is important to create contacts list. You can send or receive messages from your partner only if the partner was added to contact list. You can send messages to your partner now. Click button following contact's name and messenger will switch to 'Chat' tab. Now you can type message in text area and click send button Message will go to your communication partner. You can see sent messages with timestamp in message board below. When your partner responses with a message then the partner's message will appear in the message board just below your message. If you send message when the partner was disconnected then the message will be stored on server while your partner becomes online. In this moment your message will arrive to destination. The same will be happened if you was offline when your partner sent message. You do not miss the message but receive it in next time you login to messenger. |


Way
Mesbah Uddin
Created: 2020-01-12 Sun 01:08
Page-1
- Name: Mesbah Uddin
- Born: Dec 28, 1977 Dhaka (now Japanese by naturalization)
- High school: Dhaka College (est. 1841)
- Slected by Japanese Govt. as a MEXT scholar (1996 - 2003)
- Osaka-Gaidai: 1-year Japanese language and culture training
- Kyushu University: Bachelor of engineering, Master of engineering
(Research area: ASIC design optimization research for low power and energy)
- {dot-com bubble, 9-11, the-world-is-flat, the-code-book, RFID early adaptation etc. => realized security/privacy is going to be the keyWo}
- Work 0: Became interested in information security field and proceeded to Kyushu University's doctoral course as a self finance student
- Studied different identity management schemes including PKI
- As an RA helped the rolling-out of smart-card-id project, looked after organizations infrastructure as a system administrator
- As a TA helped several graduate/undergraduate courses, tutored foreing students, etc.
- Recieved scholarships from MEXT (1-year), Rotary foundation (2-year), JSPS DC (1-year)
- Collaborated with other institutions to develop compilers, CPU on FPGA, help teaching etc.
- Work 1: Kyushu University Faculty (2007-2010)
(Became highly motivated to join in the rolling-out of a pilot project to foster highly-skilled ICT personnels)
- Work 2: Space-Time Engineering, Inc. https://www.spacetime-eng.com/en/
- Scratch-development consultant
- Product feature enhancement (iterative SLDC)
- Work 3: The MathWorks, Inc. https://www.mathworks.com/
- Others:
- Coordinator BITPJ (Signed MOA with Bangaladesh Govt. Ministry)
- Member Global Marketing Committee at Meiji University
Entrepreneurship
- Entrepreneurship is the process of creating something new
with value by devoting the necessary time and effort,
assuming the accompanying financial, psychic and social risks,
and receiving the resulting rewards of monetary and personal satisfaction
and independence.
Entrepreneurs
- Entrepreneurs are people that notice opportunities and take the initiative to mobilize resources to make new goods and services.
- Entrepreneurship is a mindset
- Opportunity-focused
- Innovative
- Growth-oriented
Target group
- The market of buyer in the case of business innovation
- The hospitals administration in the case of a new admission procedure and software
- Prospective students in the case of a new course or even college of entrepreneurship
- The constituency for a new service provided by the nonprofit agency
Small Business Owners
- Small business owners are people who own a major equity stake in a company with fewer than 500 employees.
- In 1997 there were 22.56 million small business in the United States.
- 47% of people are employed by a small business.
Intrapreneurship
- Starting business within an organization
- Intrapreneurs also notice opportunities and take initiative to mobilize resources, however they work in large companies and contribute to the innovation of the firm.
- Intrapreneurs often become entrepreneurs.
Types of Start-ups
- Lifestyle firm: Small venture that supports the owners and usually does not grow (40emplo)
- Foundation company: A type of company formed from research and development that usually does not go public (40-400employee)
- High potential venture: A venture that has high growth potential and therefore receives great investor interest(500 empl.)
- Gazelles: Very high growth ventures
Employee Satisfaction
- In companies with less than 50 employees, 44% were satisfied.
- In companies with 50-999 employees, 31% are satisfied.
- Business with more than 1000, only 28% are satisfied.
Advantages of a Small Business
- Greater Opportunity to get rich through stock options
- Feel more important
- Feel more secure
- Comfort Level
Disadvantages of a Small Business
- Lower guaranteed pay
- Fewer benefits
- Expected to have many skills
- Too much cohesion
- Hard to move to a big company
- Large fluctuations in income possible
Who are entrepreneurs?
- Common traits
- Original thinkers
- Risk takers
- Take responsibility for own actions
- Feel competent and capable
- Set high goals and enjoy working toward them
- Common traits
- Self employed parents
- Firstborns
- Between 30-50 years old
- Well educated – 80% have college degree and 1/3 have a graduate level degree
Successful and Unsuccessful Entrepreneurs
Successful
- Creative and Innovative
- Position themselves in shifting or new markets
- Create new products
- Create new processes
- Create new delivery
- Unsuccessful
- Poor Managers
- Low work ethic
- Inefficient
- Failure to plan and prepare
- Poor money managers
Characteristics of Entrepreneurs (Figure)
Key Personal Attributes
- Entrepreneurs are Made, Not Born!
- Many of these key attributes are developed early in life, with the family environment playing an important role
- Entrepreneurs tend to have had self employed parents who tend to support and encourage independence, achievement, and responsibility
- Firstborns tend to have more entrepreneurial attributes because they receive more attention, have to forge their own way, thus creating higher self-confidence
Key Personal Attributes (cont.)
- Need for Achievement
- A person’s desire either for excellence or to succeed in competitive situations
- High achievers take responsibility for attaining their goals, set moderately difficult goals, and want immediate feedback on their performance
- Success is measured in terms of what those efforts have accomplished
Key Personal Attributes (cont.)
- Desire for Independence
- Entrepreneurs often seek independence from others
- As a result, they generally aren’t motivated to perform well in large, bureaucratic organizations
- Entrepreneurs have internal drive, are confident in their own abilities, and possess a great deal of self-respect
Key Personal Attributes (cont.)
- Self-Confidence
- Because of the high risks involved in running an entrepreneurial organization, having an “upbeat” and self-confident attitude is essential
- A successful track record leads to improved self-confidence and self-esteem
- Self-confidence enables that person to be optimistic in representing the firm to employees and customers alike
Key Personal Attributes (cont.)
- Self-Sacrifice
- Essential
- Nothing worth having is free
- Success has a high price, and entrepreneurs have to be willing to sacrifice certain things
Technical Proficiency
- Many entrepreneurs demonstrate strong technical skills, typically bringing some related experience to their business ventures
- For example, successful car dealers usually have lots of technical knowledge about selling and servicing automobiles before opening their dealerships
- Especially important in the computer industry
- NOT ALWAYS NECESSARY
Entrepreneurial process
- Identify and evaluate the opportunity
- Develop the business plan
- Determine the resources required
- Manage the resulting enterprise created
Opportunity
- Creation and length of opportunity
- Real and perceived value of opportunity
- Risk and returns of opportunity
- Opportunity versus personal skills and goals
- Competitive situation
Planning
- Business Plan – A step-by-step outline of how an entrepreneur or the owner of an enterprise expects to turn ideas into reality.
- Tile page:
- Table of Contents
- Executive summery
- Description of Business
- Description of Industry
- Marketing Plan
- Production Plan
- Organizational Plan
- Operational Plan
- Summry
- Appendices
Resources Required
- Existing resources for the Entrepreneur
- Resource gaps and available supplies
- Access to needed resources
Manage the Enterprise
- Management Style
- Key variable for success
- Identification of problems and potential problems
- Implementation of control system
Questions To Keep In Mind
- What are my motivations for owning a business?
- Should I start or buy a business?
- What and where is the market for what I want to sell?
- How much will all this cost me?
- Should my company be domestic or global?
Motivations
- Deciding based on motivations can direct one toward what type of business fits you best.
- Types:
- Lifestyle Venture
- Smaller Profit Venture
- High Growth Venture
What about the cost?
- Plan realistically, not optimistically
- Don’t overestimate your profits
- Don’t underestimate your costs
- Sources of Funds
- Banks
- Venture Capitalists – filthy rich, high risk investors looking for a many-times-over yield
- Angels – seem to have altruistic motives and less stringent demands than venture capitalists
Entrepreneurship: Growth Pressures
Entrepreneurial and Formal Organizations differ in six business dimensions:
- Strategic orientation
- Commitment to opportunity
- Commitment to resources
- Control of resources
- Management structure
- Compensation policy
Entrepreneurship: Growth Pressures (Table)


This package will help us to scrape all Flipkart products through Flipkart affiliate API.
Please refer API Documentation here.
See the Examples here
Install using 'npm'
npm i flipkart-scraper
Install using 'yarn'
yarn add flipkart-scraper
import flipkartScraper from "flipkart-scraper";
const scraper = new flipkartScraper(
"<Affiliate-Id-Here>",
"<Affiliate-Token-Here>"
);
// 'data' event handler
scraper.on("data", (data) => {
console.log(data.products.length);
});
// Start the scraper
scraper.start();
This module will help us to scrape all the Flipkart products.
This will create instance of the FlipkartScraper
class with required authentication params.
concurrency?
{number} Number for parallel processing in the queue, Default set to 2
maxRequest?
{number} Maximum request to Flipkart affliate server, Default set to 0
- means unlimitedmaxPage?
{number} Maximum number of pages to scrape per category, Default set to 0
- means unlimitedExample
const scraper = new flipkartScraper(
"<Affiliate-Id-Here>",
"<Affiliate-Token-Here>",
{
/**
* It will make 5 parallel request to Flipkart.
* This is optional param, default is set to 2
**/
concurrency: 5,
/**
* It will make only 500 request to Flipkart. After that program ends.
* This is optional param, default is set to 0 means unlimited
**/
maxRequest: 500,
/**
* Maximum 3 request per category
**/
maxPage: 3,
}
);
This method will start scraping through Flipkart affiliate API.
categoriesToScrape?
{string[]} Pass the list of categories that you want to scrape. Default set to []
which means all categories.Example
scraper.start(["telivision", "mobiles"]); // It will scrape only specified categories
Emitted when successful HTTP response from the Flipkart Affiliate server.
Example
// 'response' event handler
scraper.on("response", (response) => {
console.log(response);
});
Emitted when products returned from Flipkart affiliate API.
Example
// 'data' event handler
scraper.on("data", (data) => {
console.log(data.apiData.products);
});
Emitted when all products scraped by category.
Example
// 'completed' event handler
scraper.on("completed", (info) => {
console.log(info);
});
Emitted when scraper finished
Example
// 'finished' event handler
scraper.on("finished", (info) => {
console.log(info);
});
Emitted if any errors occured.
Example
// Error handler
scraper.on("error", (error) => {
console.error(error);
});
Generated using TypeDoc


Responsive
Everything should be 100% responsive. Your website should work regardless of a users device or screensize.
...from tachyons.io
Everything should be 100% responsive. Your website should work regardless of a users device or screensize.
No matter the lighting, or the device, font-sizes should be large enough and contrast should be high enough for your users to easily read your content.
Tachyons isn't just a monolithic framework. It's a collection of small modules that can be mixed and matched or used independently. Use what you need. Leave the rest.
Accessibility is important to us. Throughout both the css and the documentation we provide numerous tools and methods for making it easier to maximize the accessibility of your site.
Code should be optimized for performance.
Clear documentation helps create a shared understanding of design patterns amongst your team. This helps promote reuse and reduces the amount of redundancy in a codebase.


I've never been one to experiment with drugs. Raised in a Catholic household in South Philadelphia, I was not only taught the typical anti-drug lingo, but saw Junkies and what-not first hand in my neighborhood. At thirteen, I had smoked my first joint - It was an amusing experience, to say the least, but nothing noteworthy.
I won't go into details about how I started my usage with the sister's Percocet and Vicodin. It involved dentistry and a trip to the ER - But a prescription later, I couldn't believe how I felt after taking my medicine. Euphoric isn't really the proper word to utilize - I think I just felt at peace with a lot of my passions and hobbies. Everything I loved became something that made my life worth living. But, at the time, I really didn't need a drug to feel so passionate - So when the 'script ran out - I forgot about my experiences with it and continued onward without it.
Another dentistry nightmare scored me another prescription. This time, however, I used the medicine to my complete advantage and forgot about it again. This was around 2002-2003.
Around 2004, long after my dentist dramas were over - Life happened. A five year relationship fell apart at my feet, my life changed dramatically - Some things for the better, but a lot for the worse. I suffered bouts of anxiety and depression. I found that the passion I once had for life, for my obsessions, simply ran out of steam. I didn't care, really. I had gotten a new job, which I loved, but couldn't shake the sense of innocence lost that I once held in such ease. Until I once again discovered the Sisters.
Wham - I was sent back to a time when life was a little more amusing, where my obsessions were something I cherished. And more importantly, I saw how my creativity seemed to unleash itself to ends I couldn't even foresee. I was back to recrafting Barbies into characters, drawing and sketching like a true artist, writing. I had smoked pot a while during my depression - which helped a tad, but didn't dare hold a candle to the sensations and energetic creativity I felt with Percocet or Vicodin. Both of which offered the same sense of energetic creative euphoria that can only be described as childlike innocence laced with a sugar high.
Now - I'm faced with a dilemma. Procuring them for when I binge, which has become often, is difficult. I don't resort to street dealers, and I'd dare not steal or lie to anyone [save the occasional doctor] for my habit. I don't hurt anyone, nor do I allow myself to get so high that I'm incoherent. I take it and become a pure powerhouse of creativity. Not only that, but I'm kinder and happier. I compliment everyone, and I'm simply ecstatic at living.
But I know all good things must come to an end. I am hoping to score a prescription today/tomorrow - And that will be the last for quite some time. My binge that I am going to go through, I hope, will help me inspire myself to live without it. But because I adore it so much - I've no intention of stopping it completely. I respect the power of the drug, and my own weaknesses and addictive personality. For those reasons, I must stop if I am to enjoy the use of it.
In any event, I simply wanted to share with like-minded individuals how, sometimes, drugs can affect me in positive ways. Yes, the 80's propoganda rises within me to warn me that it's not me, but it's the drug. Therefore it isn't real. The drug doesn't invent my passions or obsessions, nor does it give me talent I never had - it enhanced what I love and can do, and makes it all link together in such beautiful unison. To feel like this forever would be divine - but it's not possible.
Be wary and take note; Percocet, Vicodin, and even the more daring Oxycontin [which I refuse to take] are very addictive. The sensation I get is unlike anything I've ever felt. It rivals orgasm, for me, and can be breathtaking. But I must be careful, and use responsibly.
I know it sounds odd, but knowing completely about whatever path I'm about to wander down makes it a little easier to walk - and respecting the power behind the drug is simply a good way to not abuse it. I know it will always be available if I don't excessively use it.
Namaste.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


| Exported Interfaces - Summary |
| XDiagram |
- (referenced entity's summary:)
- manages the diagram of the chart document.
|
| XAxisSupplier |
Provides easier access to the differnet axes and their sub elements.
(details)
|
| XSecondAxisTitleSupplier |
Provides access to the titles of the secondary X axis and Y axis.
(details)
|
| XDiagramPositioning |
|
| ::com::sun::star::beans::XPropertySet |
- (referenced entity's summary:)
- provides information about and access to the
properties from an implementation.
|
| Properties' Summary |
boolean
AutomaticPosition |
[ OPTIONAL ]
If this property is true the position is calculated by the application automatically.
Setting this property to false will have no effect. Instead use the interface ::com::sun::star::drawing::XShape
to set a concrete position (note XDiagram is derived from ::com::sun::star::drawing::XShape).
|
boolean
AutomaticSize |
[ OPTIONAL ]
If this property is true the size is calculated by the application automatically.
Setting this property to false will have no effect. Instead use the interface ::com::sun::star::drawing::XShape
to set a concrete size (note XDiagram is derived from ::com::sun::star::drawing::XShape).
|
ChartDataRowSource
DataRowSource |
determines if the data for a data row is contained in the
columns or in the rows of the data array.
|
long
DataCaption |
specifies how the caption of data points is displayed.
|
long
MissingValueTreatment |
[ OPTIONAL ]
specifies how empty or invalid cells in the provided data should be handled when displayed
|
| Exported Interfaces - Details |
XDiagram
- (referenced entity's summary:)
- manages the diagram of the chart document.
|
|
XAxisSupplier
- Usage Restrictions
- optional
- Description
- Provides easier access to the differnet axes and their sub elements.
- Since
- OOo 3.4
|
|
XSecondAxisTitleSupplier
- Usage Restrictions
- optional
- Description
- Provides access to the titles of the secondary X axis and Y axis.
- Since
- OOo 3.0
|
|
XDiagramPositioning
- Usage Restrictions
- optional
- Since
- OOo 3.3
|
|
::com::sun::star::beans::XPropertySet
- (referenced entity's summary:)
- provides information about and access to the
properties from an implementation.
|
|
| Properties' Details |
AutomaticPosition
boolean AutomaticPosition;
- Usage Restrictions
- optional
- Description
- If this property is true the position is calculated by the application automatically.
Setting this property to false will have no effect. Instead use the interface ::com::sun::star::drawing::XShape
to set a concrete position (note XDiagram is derived from ::com::sun::star::drawing::XShape).
|
|
AutomaticSize
boolean AutomaticSize;
- Usage Restrictions
- optional
- Description
- If this property is true the size is calculated by the application automatically.
Setting this property to false will have no effect. Instead use the interface ::com::sun::star::drawing::XShape
to set a concrete size (note XDiagram is derived from ::com::sun::star::drawing::XShape).
|
|
| DataRowSource
|
DataCaption
long DataCaption;
- Description
- specifies how the caption of data points is displayed.
- See also
- ChartDataCaption
|
|
MissingValueTreatment
long MissingValueTreatment;
- Usage Restrictions
- optional
- Description
- specifies how empty or invalid cells in the provided data should be handled when displayed
- See also
- MissingValueTreatment
|
|
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pymatgen.analysis.defects.dilute_solution_model module¶
-
compute_defect_density
(structure, e0, vac_defs, antisite_defs, T=800, trial_chem_pot=None, plot_style='highcharts')[source]¶ Wrapper for the dilute_solution_model. The computed plot data is prepared based on plot_style.
Parameters: - structure – pymatgen.core.structure.Structure object representing the primitive or unitcell of the crystal.
- e0 – The total energy of the undefected system. This is E0 from VASP calculation.
- vac_defs – List of vacancy defect parameters in the dictionary format. The keys of the dict associated with each vacancy defect are 1) site_index, 2) site_specie, 3) site_multiplicity, and 4) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class. Site index is expected to start with 1 (fortran index).
- antisite_defs – List of antisite defect parameters in the dictionary format. The keys of the dict associated with each antisite defect are 1) site_index, 2) site_specie, 3) site_multiplicity, 4) substitution_specie, and 5) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class.
- T – Temperature in Kelvin
- trial_chem_pot (optional) – Trial chemical potentials to speedup the plot generation. Format is {el1:mu1,…}
- plot_style (string) – Allowed options are 1) highcharts (default) 2) gnuplot
Returns: The plot data is generated and returned in asked format.
-
solute_defect_density
(structure, e0, vac_defs, antisite_defs, solute_defs, solute_concen=0.01, T=800, trial_chem_pot=None, plot_style='highchargs')[source]¶ Wrapper for the solute_site_preference_finder. The computed plot data is prepared based on plot_style.
Parameters: - structure – pymatgen.core.structure.Structure object representing the primitive or unitcell of the crystal.
- e0 – The total energy of the undefected system. This is E0 from VASP calculation.
- vac_defs – List of vacancy defect parameters in the dictionary format. The keys of the dict associated with each vacancy defect are 1) site_index, 2) site_specie, 3) site_multiplicity, and 4) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class. Site index is expected to start with 1 (fortran index).
- antisite_defs – List of antisite defect parameters in the dictionary format. The keys of the dict associated with each antisite defect are 1) site_index, 2) site_specie, 3) site_multiplicity, 4) substitution_specie, and 5) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class.
- solute_defs – List of solute defect parameters in the dictionary format. Similary to that of antisite defs, wtih solute specie specified in substitution_specie
- solute_concen – Solute concentration (in fractional value)
- T – Temperature in Kelvin
- trial_chem_pot (optional) – Trial chemical potentials to speedup the plot generation. Format is {el1:mu1,…}
- plot_style (string) – Allowed options are 1) highcharts (default) 2) gnuplot
Returns: The plot data is generated and returned in asked format.
-
solute_site_preference_finder
(structure, e0, T, vac_defs, antisite_defs, solute_defs, solute_concen=0.01, trial_chem_pot=None)[source]¶ Compute the solute defect densities using dilute solution model. :param structure: pymatgen.core.structure.Structure object representing the
primitive or unitcell of the crystal.Parameters: - e0 – The total energy of the undefected system. This is E0 from VASP calculation.
- T – Temperature in Kelvin
- vac_defs – List of vacancy defect parameters in the dictionary format. The keys of the dict associated with each vacancy defect are 1) site_index, 2) site_specie, 3) site_multiplicity, and 4) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class. Site index is expected to start with 1 (fortran index).
- antisite_defs – List of antisite defect parameters in the dictionary format. The keys of the dict associated with each antisite defect are 1) site_index, 2) site_specie, 3) site_multiplicity, 4) substitution_specie, and 5) energy. 1-3 can be obtained from pymatgen.analysis.defects.point_defects.Vacancy class.
- solute_defs – List of solute defect parameters in the dictionary format. Similary to that of antisite defs, wtih solute specie specified in substitution_specie
- solute_concen – Solute concentration (in fractional value)
- trial_chem_pot – Trial chemical potentials to speedup the plot generation. Format is {el1:mu1,…}
Returns: The data for plotting the solute defect concentration.
Return type: plot_data


Thank you for installing WSO2 API MAnager.
Open a new terminal and run the following command to get start with APIM server:
$ wso2am-2.6.0 [command]
Run the following command to uninstall WSO2 API Manager.
$ sudo bash /Library/__PRODUCT__/__VERSION__/uninstall.sh
Copyright © 2019 WSO2 Inc. All rights reserved. API Manager and its use subject to a license agreement and are also subject to copyright, trademark patent and/or other laws.


Introduction
We analysed the controversy on the most visited video-sharing social network in the world.
Knowing that the user base would lean towards pro-net neutrality, we wanted to dive into the debate that was happening inside and outside the videos: we scraped speeches and dialogues recorded on video, and the relative comments and reactions of those who watched and shared them.
We started from a sample of 20 videos, obtained filtering the whole database by view count during 2014 under the "net neutrality" keyword. We watched them and removed 3 misleading results, due to inflated view count or deceptive content, replacing them with subsequents videos on the ranking. Videos were manually classified into 4 macro-areas based on their production scale:
video blogs
web shows
talk shows
politics
Youtube thus allowed us to examine the controversy on two layers: on one side the voice of authors who strive to spread knowledge, on the other side thoughts and concerns of users looking for enlightenment or willing to share their point of view.


"x" "1" "SUNAKAWA,T AND TAKAHASHI,Y, SAFETY EVALUATION OF CLIMBAZOLE(ANTIDANDRUFF AGENTS). I. MUTAGENICITY TESTS OF CLIMBAZOLE, NIPPON KOSHOHINKAGAKKAI 20(4):304-311, 1996"


name;scope;parent;department;owner;assistant name(*) Group name, will be normalized to create the identifier scope(*) Container scope, see {{container-scope}}. Case is sensitive. parent Parent name, must exists. Case insensitive. department Identifier of flag such as department. Multivalued, use comma as separator. owner Owner user identifiers of this group. Not yet used. Multivalued, use comma as separator. assistant Assistant user identifiers of this group. Not yet used. Multivalued, use comma as separator.
Sample Group2;Group;;ligoj-admin;ligoj-user West Coast HR;organization;HR Lawyers;organization;;78945,19067;user1;user2,user3


Mallory Smart is a poet from Chicago, Illinois. Her book I’m AntiSocial, Coffee Never Lies is available now from Bottlecap Press. Snapchat/Twitter: @malsmart


- Source:
Calculates the LUP decomposition of the Matrix,
where L is lower triangular matrix which diagonal entries are always 1,
U is upper triangular matrix, and P is permutation matrix.
It is implemented using Gaussian Elimination with Partial Pivoting in order to reduce the error caused by floating-point arithmetic.
Note that if optimized is true, P is a Permutation Array and both L and U are merged into one matrix in order to improve performance.
It is implemented using Gaussian Elimination with Partial Pivoting in order to reduce the error caused by floating-point arithmetic.
Note that if optimized is true, P is a Permutation Array and both L and U are merged into one matrix in order to improve performance.


Detail-oriented professional with 4.5+ years of experience and proven knowledge of application development, programming, and professional trading platform development.


AWS::Batch::ComputeEnvironment
The AWS::Batch::ComputeEnvironment
resource to define your AWS Batch compute
environment. For more information, see Compute Environments in
the AWS Batch User Guide.
Syntax
To declare this entity in your AWS CloudFormation template, use the following syntax:
JSON
{ "Type" : "AWS::Batch::ComputeEnvironment", "Properties" : { "Type" :
String
, "ServiceRole" :String
, "ComputeEnvironmentName" :String
, "ComputeResources" : ComputeResources, "State" :String
} }
YAML
Type: AWS::Batch::ComputeEnvironment Properties: Type:
String
ServiceRole:String
ComputeEnvironmentName:String
ComputeResources: ComputeResources State:String
Properties
Type
-
The type of the compute environment.
Required: Yes
Type: String
Update requires: Replacement
ServiceRole
-
The service role associated with the compute environment that allows AWS Batch to make calls to AWS API operations on your behalf.
Required: Yes
Type: String
Update requires: No interruption
ComputeEnvironmentName
-
The name of the compute environment.
Required: No
Type: String
Update requires: Replacement
ComputeResources
-
The compute resources defined for the compute environment.
Required: Yes
Type: AWS Batch ComputeEnvironment ComputeResources
Update requires: No interruption
State
-
The state of the compute environment. The valid values are
ENABLED
orDISABLED
. AnENABLED
state indicates that you can register instances with the compute environment and that the associated instances can accept jobs.Required: No
Type: String
Update requires: No interruption
Return Values
Ref
When you pass the logical ID of an AWS::Batch::ComputeEnvironment
resource to the intrinsic Ref
function, the function returns the compute
environment ARN, such as
arn:aws:batch:
.
us-east-1
:555555555555
:compute-environment/M4OnDemand
For more information about using the Ref
function, see Ref.
Examples
Managed Compute Environment
The following example creates a managed compute environment called
C4OnDemand
that uses C4 On-Demand instances and a custom AMI.
JSON
{ "ComputeEnvironment": { "Type": "AWS::Batch::ComputeEnvironment", "Properties": { "Type": "MANAGED", "ServiceRole": "arn:aws:iam::111122223333:role/service-role/AWSBatchServiceRole", "ComputeEnvironmentName": "C4OnDemand", "ComputeResources": { "MaxvCpus": 128, "SecurityGroupIds": [ "sg-abcd1234" ], "Type": "EC2", "Subnets": [ "subnet-aaaaaaaa", "subnet-bbbbbbbb", "subnet-cccccccc" ], "MinvCpus": 0, "ImageId": "ami-a1b2c3d4", "InstanceRole": "ecsInstanceRole", "InstanceTypes": [ "c4.large", "c4.xlarge", "c4.2xlarge", "c4.4xlarge", "c4.8xlarge" ], "Ec2KeyPair": "id_rsa", "Tags": {"Name": "Batch Instance - C4OnDemand"}, "DesiredvCpus": 48 }, "State": "ENABLED" } } }
YAML
ComputeEnvironment: Type: AWS::Batch::ComputeEnvironment Properties: Type:
MANAGED
ServiceRole:arn:aws:iam::111122223333:role/service-role/AWSBatchServiceRole
ComputeEnvironmentName:C4OnDemand
ComputeResources: MaxvCpus:128
SecurityGroupIds: -sg-abcd1234
Type:EC2
Subnets: -subnet-aaaaaaaa
-subnet-bbbbbbbb
-subnet-cccccccc
MinvCpus:0
ImageId:ami-a1b2c3d4
InstanceRole:ecsInstanceRole
InstanceTypes: -c4.large
-c4.xlarge
-c4.2xlarge
-c4.4xlarge
-c4.8xlarge
Ec2KeyPair:id_rsa
Tags:{"Name": "Batch Instance - C4OnDemand"}
DesiredvCpus:48
State:ENABLED
The following example creates a compute environment named my-first-compute-environment
and specifies tags for the compute resources.
JSON
"MyComputeEnv": { "Type": "AWS::Batch::ComputeEnvironment", "Properties": { "Type": "MANAGED", "ServiceRole": "AWSBatchServiceRole", "ComputeEnvironmentName": "my-first-compute-environment", "ComputeResources": { "MinvCpus": "4", "MaxvCpus": "256", "DesiredvCpus": "4", "SecurityGroupIds": [ "sg-a1b2c3d4", "sg-4d3c2ba1" ], "Type": "EC2", "Subnets": [ "subnet-12345678", "subnet-87654321" ], "InstanceRole": "batch-instance-profile", "InstanceTypes": [ "optimal" ], "Ec2KeyPair": { "Ref": "MyKeyPair" }, "Tags": { "Owner": "A", "Project": "B" } }, "State": "ENABLED" } }
YAML
MyComputeEnv: Type: AWS::Batch::ComputeEnvironment Properties: Type: MANAGED ServiceRole: AWSBatchServiceRole ComputeEnvironmentName: my-first-compute-environment ComputeResources: MinvCpus: 4 MaxvCpus: 256 DesiredvCpus: 4 SecurityGroupIds: - sg-a1b2c3d4 - sg-4d3c2ba1 Type: EC2 Subnets: - subnet-12345678 - subnet-87654321 InstanceRole: batch-instance-profile InstanceTypes: - optimal Ec2KeyPair: !Ref MyKeyPair Tags: Owner: A Project: B State: ENABLED


--- title: Construct a Categorical Column with a Vocabulary File type: docs repo: https://github.com/rstudio/tfestimators menu: main: name: Construct a Categorical Column with a Vocabulary File - tfestimators parent: tfestimators-reference aliases: - /reference/tfestimators/column_categorical_with_vocabulary_file.html - /tfestimators/reference/column_categorical_with_vocabulary_file.html - /guide/tfestimators/reference/column_categorical_with_vocabulary_file.html - /tools/tools/tfestimators/reference/column_categorical_with_vocabulary_file.html - /installation/tfestimators/reference/column_categorical_with_vocabulary_file.html - /tutorials/tfestimators/reference/column_categorical_with_vocabulary_file.html - /guide/tools/tfestimators/reference/column_categorical_with_vocabulary_file.html - /deploy/tfestimators/reference/column_categorical_with_vocabulary_file.html - /tools/tfestimators/reference/column_categorical_with_vocabulary_file.html - /tutorials/tools/tfestimators/reference/column_categorical_with_vocabulary_file.html ---
Use this when your inputs are in string or integer format, and you have a
vocabulary file that maps each value to an integer ID. By default,
out-of-vocabulary values are ignored. Use either (but not both) of
num_oov_buckets
and default_value
to specify how to include
out-of-vocabulary values. For input dictionary features
, features[key]
is
either tensor or sparse tensor object. If it's tensor object, missing values can be
represented by -1
for int and ''
for string. Note that these values are
independent of the default_value
argument.
column_categorical_with_vocabulary_file(..., vocabulary_file,
vocabulary_size, num_oov_buckets = 0L, default_value = NULL,
dtype = tf$string)
| ... | Expression(s) identifying input feature(s). Used as the column name and the dictionary key for feature parsing configs, feature tensors, and feature columns. |
| vocabulary_file | The vocabulary file name. |
| vocabulary_size | Number of the elements in the vocabulary. This must be
no greater than length of |
| num_oov_buckets | Non-negative integer, the number of out-of-vocabulary
buckets. All out-of-vocabulary inputs will be assigned IDs in the range
|
| default_value | The integer ID value to return for out-of-vocabulary
feature values, defaults to |
| dtype | The type of features. Only string and integer types are supported. |
A categorical column with a vocabulary file.
ValueError: vocabulary_file
is missing.
ValueError: vocabulary_size
is missing or < 1.
ValueError: num_oov_buckets
is not a non-negative integer.
ValueError: dtype
is neither string nor integer.


About Me
I’m a second year PhD student advised by Ke Yuan and Roderick Murray-Smith at the Univeristy of Glasgow, Computing Science department.
I’m interested in generative models, Bayesian nonparametrics, representation learning and interpretability of latent variable models. Additionally, my current research focuses on applying generative models to histopathology and how these models can help to better understand cancer tissue.
On a personal level, I’m interested in U.S., U.K. and E.U. politics, electoral/polling data and their intersection with machine learning.
Before starting the PhD, I worked in the semiconductor industry as a SoC Design engineer in the FPGA field at Altera Coporation and Intel Corporation in San Jose, CA. I received an M.S. in Electrical Engineering at the IIT in Chicago, and M.S. and B.S. degrees in Telecommunications Engineering at ETSIT-UPM in Madrid.
Research Experience
Preprints
'Learning a low dimensional manifold of realcancer tissue with PathologyGAN' Adalberto Claudio Quiros, Roderick Murray-Smith, Ke Yuan. 2020.
Abstract: Application of deep learning in digital pathology shows promise on improving disease diagnosis and understanding. We present a deep generative model that learns to simulate high-fidelity cancer tissue images while mapping the real images onto an interpretable low dimensional latent space. The key to the model is an encoder trained by a previously developed generative adversarial network, PathologyGAN.  We find that the latent space encodes morphological characteristics of tissues (e.g. patterns of cancer, lymphocytes, and stromal cells). In addition, the latent space reveals distinctly enriched clusters of tissue architectures in the high-risk patient group.
'Pathology GAN: Learning deep representations of cancer tissue' Adalberto Claudio Quiros, Roderick Murray-Smith, Ke Yuan. 2019.
https://arxiv.org/abs/1907.02644Abstract: We apply Generative Adversarial Networks (GANs) to the domain of digital pathology. Current machine learning research for digital pathology focuses on diagnosis, but we suggest a different approach and advocate that generative models could drive forward the understanding of morphological characteristics of cancer tissue. In this paper, we develop a framework which allows GANs to capture key tissue features and uses these characteristics to give structure to its latent space. To this end, we trained our model on 249K H&E breast cancer tissue images. We show that our model generates high quality images, with a Frechet Inception Distance (FID) of 16.65. We additionally assess the quality of the images with cancer tissue characteristics (e.g. count of cancer, lymphocytes, or stromal cells), using quantitative information to calculate the FID and showing consistent performance of 9.86. Additionally, the latent space of our model shows an interpretable structure and allows semantic vector operations that translate into tissue feature transformations. Furthermore, ratings from two expert pathologists found no significant difference between our generated tissue images from real ones.
Publications
'DNNLibGen : Deep Neural Network Based Fast Library Generator' Eunice Naswali, Adalberto Claudio Quiros, Pravin Chandran. 2019.
https://ieeexplore.ieee.org/document/896519126th IEEE International Conference on Electronics Circuits and Systems
Abstract: We propose a new modeling methodology using deep learning techniques for generating timing models for Static Timing Analysis (STA). Current device behavior is non-linear, non-monotonic and exhibits high sensitivity to (Process Voltage Temperature) PVT variation which imposes a myriad of design challenges including the need for analysis at several PVT corners. While complete PVT coverage is crucial for detecting design issues early and achieving time-to-market goals with improved predictability, the number of PVT corners are growing exponentially and library generation has also become a significant bottleneck in current design cycles. To this end, we have developed a novel methodology for timing library generation that uses data from sparse characterization in PVT space and generates delay models at required sign-off corners. We have employed deep neural nets with residual connections for delay modeling and our methodology enables a ‘single model’ to fully comprehend multiple cell types, PVT corners and generate required PVT timing libraries. The proposed library-generator uses a novel inter-corner model to generate delay tables at 17 test corners using 7 corners as reference. In addition, we have developed an intra-corner model, to generate dense 8x8 delay tables using delays from 10 slew/load points as reference. The results show that, using these models, we are able to achieve key improvements with over 98.7% of calculated delays within acceptable tolerance while reducing characterization run-time for early milestones by up to 60%.
Miscellaneous
- March, 2020: Gave a lecture at the ‘Deep Learning’ course of MSc in Data Science, introducing Generative Adversarial Networks (GANs): Slides
- January, 2020: Wrote a tutorial document (Draft) and code implementations of related concepts to Dirichlet Processes: GEM distribution, Polya Urn, Chinese restaurant process, Stick-Breaking construction, DP Posterior, and DP Mixture Models.
- October - December, 2020: Worked as a teaching assistant and gave two lectures at the ‘Machine Learning for Data Scientists’ course of MSc in Data Science, briefly introducing Sampling methods and Variational Inference: Sampling slides, MCMC Bayesian Linear regression example, Variational Inference slides, and VI Bayesian Linear regression example
- March, 2019: Wrote a brief survey on GANs: slides and code for relevant models.
Professional Experience
Intel Corporation
San Jose, CA, USASenior SoC Design Engineer - Fabric Performance Leadership Team
April 2017 – September 2018
I worked in the Fabric Performance Leadership team, our goal was to analyze the Stratix 10 FPGA design from the hardware and software perspective to find flaws and push the FPGA frequency performance forward.
During this period, a few of the most important achievements were:
- A Python graph builder tool that generates a graph of the FPGA’s routing structure, prunes it and creates a visualization from an register-transfer level netlist design.
- Implementated a device End-of-Life (EOL) methodology tool that obtained the aging degradation delay on FPGA’s transistors.
- Analyzed logical and physical implementation of Adders: From the FPGA software, integrated circuit design and architecture perspective. The result of this study was a redesign of the adder’s implementation leading to a 70% improvement on frequency performance for adders.
- Published ‘DNNLibGen : Deep Neural Network Based Fast Library Generator’ Eunice Naswali, Adalberto Claudio Quiros, Pravin Chandran.
Altera Coporation/Intel Corporation
San Jose, CA, USASenior SoC Design Engineer - Full Chip Timing Team
June 2014 – April 2017
Worked in the Full Chip Timing team on Static Timing Analysis, first to verify the hardware FPGA designs running at the frequency specifications, and secondly to correlate the FPGA software models with the hardware designs and silicon devices.
- Developed a Stratix 10 full chip timing violation tool: This tool gathers all full chip timing violations due to maximum transition (~100K instances), cross reference each violation to a lower system blocks, and compiles them for each block designer.
- Arria 10 Frequency binning and register to register timing correlation lead: Silicon/Quartus-FPGA-SW/HSPICE model frequency correlation, given an internal Altera Quality Award in 2015 Q2.
- Developed a timing tool in Python, HSPICE, and Quartus FPGA Software significantly impacting the process: Increasing the number of data points from 10 to 7K, with different features including Power-Voltage-Temperature (PVT), voltage threshold and sheet resistance sweeping options.
Worked developing bots for web data scraping, additionally I help in maintaining and developing improvements on middle tier code and servers, which controled the bots and jobs executions. Most of this work was done in SQL, C#, Python, C++.
Education
Illinois Institute of Technology
Master of Science in Electrical Engineering - 3.53/4
Chicago, IL, USA
Polytechnic University of Madrid, ESTIT-UPM
Master & Bachelor of Science in Telecommunications Engineering - 7.23/10
Madrid, Spain


Format: http://dep.debian.net/deps/dep5/
Source: http://www.openbsd.org/cgi-bin/cvsweb/src/usr.bin/nc/
Files: netcat.c
Copyright: 2001 Eric Jackson
License: BSD-3-Clause
Files: atomicio.*
Copyright: 2005 Anil Madhavapeddy
1995,1999 Theo de Raadt
License: BSD-3-Clause
Files: socks.c
Copyright: 1999 Niklas Hallqvist
2004, 2005 Damien Miller
License: BSD-3-Clause
Files: debian/*
Copyright: 2008, 2009, 2010 Decklin Foster
2008, 2009, 2010 Soren Hansen
2012 Aron Xu
License: BSD-3-Clause
License: BSD-3-Clause
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
.
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
3. The name of the author may not be used to endorse or promote products
derived from this software without specific prior written permission.
.


I am self taught graphic designer with vast knowledge in the Adobe graphic design tool such as Illustrator, Photoshop, XD. I joined Moringa school because I felt the need to understand the basics of programming. I hope to gain the knowledge needed to help me transition to UI/UX design in the future.
I studied in Strathmore University and graduated with a Bachelors of Commerce, Marketing Major.My hobbies include travelling, hiking, biking,listening to music, drawing and illustrating, reading books, watching movies/series,modelling, going through pinterest. *LOL*


The Public House is a Multi-cuisine restaurant located in Sector 126, Noida. The cafe offers a beautiful and vibrant ambience and has a very lively vibe. It becomes an ideal place to hang out with friends and spend quality time over good food and games. The courteous and kind staff elates the dining experience and the affordable menu is like icing on the cake. The cafe stands near mega mall seasonal ingredients.
We offer full-service catering for any event, large or small. We understand your needs and we will cater the food to satisfy the biggerst criteria of them all, both look and taste. Do not hesitate to contact us.
The Public House ,Sector 6 Noida,U.P.
You can also contact us by phone<PHONE_NUMBER> or email<EMAIL_ADDRESS>or you can send us a message here:


Load and Play Local Audio Files
Open an audio file from your local folder and play/stop it by clicking the buttons.
Play
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Enum ActionType
Namespace: DotNetHelper.ObjectToSql.Enum
Assembly: DotNetHelper.ObjectToSql.dll
Syntax
public enum ActionType
Fields
| Name | Description |
|---|---|
| Delete | |
| Insert | |
| Update | |
| Upsert |
public enum ActionType
| Name | Description |
|---|---|
| Delete | |
| Insert | |
| Update | |
| Upsert |


class: center, middle, inverse, title-slide # A Crash lesson in R, Integration, and descriptive statistics ### Sebastian Hoyos-Torres --- ### Welcome! - Why this class? -- - What's the point? -- - R? --- ### An introduction to R - Although there are some materials in this class that should be figured out by hand, everyone should download and use R from the Comprehensive R Archive Network (CRAN) - In fact, the presentations for this class are made using R with Rstudio as the integrated developer environment (IDE). - Once you get the hang of R, you should be able to figure out problems much quicker than working the problem out by hand - For example, let's say we had a vector of values from 0-100 and wanted to add the values together. Using a calculator, this process would look like `\(0 +1 + 2 + 3+...100\)` . in R, you could solve this problem relatively quickly ```r x <- c(0:100) # this creates an array of values from 0 to 100 sum(x) #this command adds all of the values together and gives you the answer you're looking for ``` ``` ## [1] 5050 ``` --- ### What you need to know: - This all said, although the class does require you to learn how to use R; it does **not** require mastery of R. - We should start with the simplest data structure in R, the vector ```r is.atomic(1)||is.list(1) #returns true. R does not use scalars #although there are things that seem to behave like scalars like the following 1+1 # this does not mean they are scalars ``` --- ### Types of Vectors - Vectors come in two types; atomic vectors and lists. We will focus on the former rather than the latter in this course. -- - Atomic vectors come in the following types: logical, integer, character, double, and character -- - We will mostly use integer and doubles in the course to avoid confusion ```r dbl_vector <- c(1,2,3,4,5) chr_vector <- c("cat","dog","apple") log_vector <- c(TRUE, FALSE,FALSE) int_vector <- c(1L,2L,3L) ``` --- ### R and vector behavior: - Although it is not the focus of the class, it should be noted that R can exhibit some interesting features which may lead to some problems. - First, let's look at these examples: ```r .1 == .3/3 seq(0,1, by = .1) == .3 TRUE + TRUE + TRUE FALSE + FALSE + FALSE "one" == 1 1 == "1" "one" < 2 "3" < 2 ``` - What do you think the results will be without putting these into R? --- ### R as a tool - Although there are more things to consider with datatypes when using R, this does not take away from the value of using R to help solve problems. - Aside from R's weird behavior with floating points, the problems shouldn't affect our computations for most problems. however, it will be useful later on. - Throughout the course, we will also be using a mixture of Base R and the tidyverse --- ### Base vs Tidy - There are some disagreements on whether to use Base or tidy approaches to analysis. - Base R would require teaching syntax such as $ and [[]], loops, and conditionals, data types. - tidy allows us to use popular packages such as ggplot2 and magrittr's %>% so we will use a mixture of both in this course (this requires you use tidyverse so you should probably install it). --- ### Functions - most functions that we write out by hand can be written directly into R - We are familiar with the formula for the mean being `\(\frac{\Sigma x_i}{n}\)` - This is directly translatable into R ```r formula_for_average <- function(x){ sum(x)/length(x) #this is directly equivalent to the mathematical formula } samples <- rnorm(100) #we'll delve into these functions later in the semester formula_for_average(samples)# use the average ``` ``` ## [1] -0.05947543 ``` --- ### Functions continued... - Defining a function will save you time in the long run as long as you know the formula and how to apply it - It will also prevent you from writing the same code over and over again to solve similar problems. - If you ever have a question on an r function that has already been defined, use ? before the function ```r ?rnorm #for those who are curious as to what rnorm does ``` --- ### Integrals - Understanding what integrals do will help in understanding probability distributions in the future - For example, take the following function from the interval of 0-1 `\(f(x) = x^2\)` when we integrate the function, we do the following `$$\int_0^1x^2dx = [\frac{1}{3}x^3]_0^1 = (\frac{1}{3}(1))-(\frac{1}{3}(0)) = \frac{1}{3}$$` --- ```r library(tidyverse) fun1 <- function(x){x^2} ggplot(NULL, aes(c(0,2)))+ stat_function(fun = fun1)+ geom_area(stat = "function",fun = fun1,xlim = c(0,1), fill = "red")+ labs(x = "x-axis", y = "y-axis", title = "Integral of x") ``` <img src="week1_files/figure-html/unnamed-chunk-7-1.png" style="display: block; margin: auto;" /> --- ### How will integrals be used in this course? - later on in this course, we will use integrals to interpret the probability density and cumulative density functions of multiple distributions. - Since integrals are not a prerequisite for this course, we will find ways in R to integrate for definite integrals. For example, the calculations for a definite integral can also be found using R - let's try the previous example using R ```r functiontointegrate <- function(x){ x^2 } integrate(functiontointegrate,0,1) #this gives us 1/3 as well ``` ``` ## 0.3333333 with absolute error < 3.7e-15 ``` --- ### Applications, Part 1 - When will we use probability or statistics? - Currently, probability and statistics are used in almost every field. - Let's look at Sports. --- ### Bayes Theorem - Let's look at basketball. Lebron makes 49 percent of his clutch shots. If the probability ESPN mentions the end of a game is 80 percent of the time and mentions the end of the game if a game winner is made at 95 percent; what is the probability that Lebron made the shot if ESPN mentioned the end of the game? - What do you think is the probability that Lebron made the shot if the game is mentioned on ESPN? --- --- ### Bayes pt 1 - Typically, some people might want to say that Lebron has approximately a 50%, 80%, or 95 chance to make the shot. - Those people have not taken this class. - Given the information, we would approach the problem using Bayes Theorem. `$$P(A|B) = \frac{P(B|A)P(A)}{P(B)}$$` --- ### Bayes Cont. - This problem requires us to take a few steps. Problem is asking for P(A|B) or P(Lebron makes the clutch shot | ESPN mentions end of the game) First, identify P(A) or P(Lebron makes a clutch shot) = .49 Next, identify P(B) or P(ESPN mentions end of the game) = .8 Also, identify P(B|A) or P(ESPN mentions end of game | Lebron clutch shot made ) = .95 We can solve this manually or through R after we finished identifying the necessary components --- ### Bayes and R - Remember, you can always define functions in R to do your computations. Be careful with the formulas! ```r bayes <- function(A,B,BA){ (BA*A)/(B) } bayes(.49,.8,.95) #just remember to assign the right arguments ``` ``` ## [1] 0.581875 ``` --- ### Descriptive statistics - We will explore more formal applications of Bayes Theorem and the principles of probability next week. - At this point, it is worth exploring descriptive statistics before we delve into our journey into probability and statistics. - Everyone in a science is concerned with data and statistics are a tool to understand patterns within the data of a particular scientific field. --- ### Descriptive stats cont. - Statistics are aimed at studying a particular *population* through the use of a *sample* - Let's try another Bayes theorem problem and see how we could use descriptive statistics and models to illustrate the logical mechanics. --- ### The Taxicab Problem - A taxicab was involved in a hit and run accident at night. Two cab companies, the Green(all cabs green) and the Blue(all cabs blue), operate in the city. The following facts are known: - 85% of the cabs in the city are green and 15% are blue and these proportions are on the street at any one time - A witness identified the cab as blue. The court tested the reliability of the witness under the same circumstances that existed on the night of the accident and concluded that the witness correctly identified each one of the two colors 80% of the time and failed 20% of the time. - Let's run a simulation of this problem and see some of the mechanics behind why Bayes Theorem works. --- ### Simulation of taxi cab - Let's say there were 1000 cabs in the city. Following the problem, 850 are green and 150 are blue (85 percent green, 15 percent blue) - If the cab was blue, the witness would say blue 80 percent of the time or for 20 percent of the green cabs (chance he makes a mistake). This looks as follows in R ```r green <- 850 blue <- 150 chancebluecorrect <- .8 chanceblueincorrect <- 1-.8 blueasblue <- blue*chancebluecorrect #turns out to be 120 blue identified correctly blueasgreen<- green*chanceblueincorrect #turns out to be 170 #of blue answers, we see that the person would identify 170 incorrectly #if person correctly identifies 120 cabs correctly, then: totblueidentified <- blueasblue+blueasgreen paste(round(blueasblue/totblueidentified*100,2),"%") ``` ``` ## [1] "41.38 %" ``` --- ```r #Bayes Theorem applied (for those curious) pblue <- .15 pgreen <- .85 pblueidblue <- .8 pgreenidblue <- .2 #law of total probability = P(B) = P(B|A)*P(A) + P(B|A1)*P(A1) pidblueall<- (pblueidblue*pblue) + (pgreenidblue*pgreen) pblueidblue*pblue/pidblueall ``` ``` ## [1] 0.4137931 ``` --- ### Enumerative Study - As previously mentioned, descriptive statistics helps us understand trends within our data. - If we use descriptive statistics, we would be conducting an enumerative study. - An example would be the average GPA of students at John Jay. - This would use a sampling frame listing all items in the population that might be part of the sample. Hopefully, the sample is representative. --- ### Some sampling methods. - **Simple Random Sample**: when members of a sample have an equal chance of being selected as any other member. - Often considered the gold standard when you want to obtain information about a population from a sample. - **Stratified Sample**: separates population units into non-overlapping groups and taking a random sample from each one. - **Convenience Sample** : selecting individuals or objects without randomization - **Self- selected sample**: respondents decide individually decide whether or not to take part within a study --- ### Sampling in R - Computers are great for selecting a random sample and thus, here is how to sample in R. ```r x <- 1:20 sample(x,5) ``` ``` ## [1] 15 13 1 7 17 ``` --- ### Some basic descriptives - R is useful for enumerative purposes - let's try it out ```r x <- rnorm(100, mean = 50,sd = 10 ) x %>% mean() #gets the mean ``` ``` ## [1] 51.36371 ``` ```r x %>% median() #summarizes the median ``` ``` ## [1] 51.41645 ``` ```r x %>% summary()#all summary output. ``` ``` ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 27.63 47.28 51.42 51.36 56.51 75.38 ``` --- ### Descriptive plots ```r stem(x)#stem and leaf plot ``` ``` ## ## The decimal point is 1 digit(s) to the right of the | ## ## 2 | 89 ## 3 | 112234 ## 3 | 56778999 ## 4 | 00123 ## 4 |<PHONE_NUMBER>999999 ## 5 |<PHONE_NUMBER>11112222333344444 ## 5 |<PHONE_NUMBER>677889 ## 6 | 011134444 ## 6 | 5557789 ## 7 | 003 ## 7 | 5 ``` --- ### Descriptive plots cont ```r qplot(x,geom = "histogram") #could also use hist(x) ``` ![](week1_files/figure-html/unnamed-chunk-15-1.png)<!-- -->


The most recent understanding of the evolution of insects is based on studies of the following branches of science: molecular biology, insect morphology, paleontology, insect taxonomy, evolution, embryology, bioinformatics and scientific computing. It is estimated that the cl...


Localization In Ember
How to effectivly globalize and localize an ember application
(and web apps in general)
Created by Chris Rice / Github: Kilowhisky
What we are after
Whats the difference?
Globalization is the process of designing and developing applications that function for multiple cultures.
Localization is the process of customizing your application for a given culture and locale.
Source
What things need globalization?
- Number parsing
- Date parsing
- Regex
- Currency
- Non-Latin Characters
123.43 -> 123,43
10/01/2016 -> 2016/10/01
Mitigation is in the API and platform specific
Globalization basics
Here are some quick tips for API communication.
- Never pass a string formatted date. Always .toJSON()!
- Never pass a string formatted number.
- Always use and store in UTF-8!
- Be flexible in validation. Try not to apply your locale's conventions. (phone numbers,etc..)
- Be sure to localize error messages!
- Decide early on if you want to support right-to-left languages or other alphabets.
What needs localization?
- Numbers
- Dates
- Text
- Plugins
- API Responses
Basic Premise of localizing a web app
- Detect the users localization automatically
- Tell the browser we want to localize
- Tell our API that we want to localize
- Manipulate our application into awesomeness
What will we need?
- ember-i18n addon that is the de facto standard localizing an ember application
- ember-moment addon that helps with date localization
- ember-cli-moment-shim if you don't like ember-moment you use this instead
- ember-i18n-csv for exporting translations to csv so you can send them to a translator


Indicates the progress of the relative index of each panel.
panel.getOutsetProgress()
When panel is completely invisible, outsetProgress becomes -1 at left(up), 1 at right(down) direction, and 0 when panel's anchor and hanger is overlapped.
panel.getVisibleRatio()
Indicates the percentage of areas within the viewport that the panel occupies.


News
The Best Features
Rocket League is in the process of receiving one of its biggest updates, and we run down the best of what it includes. comes new content ranging from arenas to cars to a tidal wave of cosmetic options and more.
Read MoreRocket League is in the process of receiving one of its biggest updates, and we run down the best of what it includes. comes new content ranging from arenas to cars to a tidal wave of cosmetic options and more.
Read More


Hello! I'm Agnibho Roy, a third-year undergraduate student studying EECS and Applied Mathematics at UC Berkeley. My primary interests lie in stochastic processes, quantitative research, and theoretical machine learning. Download my resume here.
Last summer, I worked on a compressed backtesting environment for a portfolio algorithm as part of the LOGAN algorithm development team on the global equities desk at RBC. This upcoming summer, I am going to be a trading intern on the semi-systemic options desk at Citadel Securities. Read more about my industry experience here.
Currently, I am part of the RISE lab at UC Berkeley, working with postdoc Matthew Wright on analyzing benefits of Hinge Loss Training for Deep Neural Networks. Apart from career and research interests, I enjoy teaching. I am a head content GSI for Data Science Principles and Techniques, and have taught other classes in the past. Ive been taking the time this past year to write content ranging from class notes to interview preparation, which you can check out here.
-
Citadel SecuritiesIncoming Quant Trading Intern - Summer 2021
-
Royal Bank of CanadaQuant Trading and Resesarch Intern - Summer 2020
-
Fidelity InvestmentsSoftware Engineering Intern - Summer 2019
-
MIT Francis Bitter LaboratoryResearch Intern - Summer 2017


This provides a framework for R packages developed for a regulatory environment. It is based on the 'testthat' unit testing system and provides the adapter functionalities for XML-based test case definition as well as for standardized reporting of the test results.
| Version: | 1.2.2 |
| Depends: | R (≥ 3.1.3), testthat (≥ 1.0.0), magick (≥ 1.3), methods, XML, stringr, magrittr |
| Imports: | base64, jsonlite |
| Suggests: | knitr, rmarkdown |
| Published: | 2018-12-14 |
| Author: | Sebastian Wolf [aut, cre], Matthias Pfeifer [aut, ctb], Sergej Potapov [ctb], Roche [cph, fnd] |
| Maintainer: | Sebastian Wolf <sebastian at mail-wolf.de> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| SystemRequirements: | ImageMagick++: ImageMagick-c++-devel (rpm) or libmagick++-dev (deb) |
| CRAN checks: | RTest results |
| Reference manual: | RTest.pdf |
| Vignettes: |
RTest Vignette RTest Vignette |
| Package source: | RTest_1.2.2.tar.gz |
| Windows binaries: | r-devel: RTest_1.2.2.zip, r-release: RTest_1.2.2.zip, r-oldrel: RTest_1.2.2.zip |
| OS X binaries: | r-release: RTest_1.2.2.tgz, r-oldrel: RTest_1.2.2.tgz |
| Old sources: | RTest archive |
Please use the canonical form https://CRAN.R-project.org/package=RTest to link to this page.


Reproducing an example
The beta distribution
Beta distribution function is “conjugate prior” for Bernoulli distribution (and others). It means that the “form” of posterior distribution is the same as the prior distribution.
The Bernoulli distribution:
p (y | θ) =
This “feature” of beta distribution allows us to keep using the same methods over and over because the posterior distribution’s form does not change. We can apply Bayesian steps in repetition.
There is a potential matter of confusion here:
Beta Distribution is different from the Beta function.
Following is the beta distribution:
p (θ | a, b) = beta(θ | a, b)
=
Where,
B(a, b) =
is a normalizing constant or beta function.
One of the most useful figures to understand what a beta distribution does, is Figure 6.1. It shows how the values of α and β change relative to each other. Let’s try to reproduce it.
Mathematica, of course, has the functions: BetaDistribution and Beta.
The image above has too much information. Let’s make it exactly like the Figure 6.1:
Exercises
Exercise 6.1
(A) Start with a prior distribution that expresses some uncertainty that a coin is fair: beta(θ|4,4).  What is the posterior distribution?
(B) Use the posterior from the previous flip as the prior for the next flip.  Now what is the new posterior?
(C) Using that posterior as the prior for the next flip, flip a third time and get a tail. Now what is the new posterior?
(D) Do the same three updates, but in the order T, H, H instead of H, H, T. Is the final posterior distribution the same for both orderings of the flip results?
Exploration
For (A) (B) and (C), we just have to increase α and β values as flip’s results come in. Plotting the results is simple, the same as shown in “Reproducing an example” section above.
Now for (D), the approach is exactly the same, the order of updating α and β changes:
Resulting distributions are the same, showing data order invariance.
Exercise 6.2
Suppose an election is approaching, and you are interested in knowing whether the general population prefers candidate A or candidate B. There is a just-published poll in the newspaper, which states that of 100 randomly sampled people, 58 preferred candidate A and the remainder preferred candidate B.
(A) Suppose that before the newspaper poll, your prior belief was a uniform distribution. What is the 95% HDI on your beliefs after learning of the newspaper poll results?
(B) You want to conduct a follow-up poll to narrow down your estimate of the population’s preference. In your follow-up poll, you randomly sample 100 other people and find that 57 prefer candidate A and the remainder prefer candidate B. Assuming peoples’ opinions have not changed between polls, what is the 95% HDI on the posterior?
Exploration
Since our prior beliefs about the matter is a uniform distribution, we don’t have to come up with our own values of α and β.
Let’ s plot the distribution of the original data to see what it looks like:
Let’s see where the peak lies, which tells us “Mode”:
To calculate 95% HDI, some finicky things are involved. They are finicky to me at least:
Thus, 95% HDI lies within the range of 0.482444 - 0.674524.
Next, we update our beliefs given new data we collect ourselves. The results of (A) will become our prior distribution.
We replicate the same process, but now with second set of samples included:
The mode has changed from 0.5816 to 0.5757.
Notice that the initial 95% HDI was {0.4824, 0.6745}, which changed to {0.5060, 0.6425} - it got narrower:
Exercises 6.3, 6.4, 6.5
These exercises are practically the same as 6.2. As results, they’re interesting. But implementation in Mathematica is just plugging in values of α and β and seeing the plots.
IOW, I am lazy.


The game startup Komodore64 from The Hague, which announced an investment of 78 million euros earlier this year with a lot of drumming, is struggling with serious money problems. This is evident from the story of duped suppliers, one of which takes the company to court.