| Alabama A&M University |
Normal |
Alabama |
1875 |
Public |
|
Founded as "Colored Normal School at Huntsville" |
Yes
|
| Alabama State University |
Montgomery |
Alabama |
1867 |
Public |
|
Founded as "Lincoln Normal School of Marion" |
Yes
|
| Albany State University |
Albany |
Georgia |
1903 |
Public |
|
Founded as "Albany Bible and Manual Training Institute" |
Yes
|
| Alcorn State University |
Lorman |
Mississippi |
1871 |
Public |
|
Founded as "Alcorn University" in honor of James L. Alcorn |
Yes
|
| Allen University |
Columbia |
South Carolina |
1870 |
Private |
African Methodist Episcopal |
Founded as "Payne Institute" |
Yes
|
| American Baptist College |
Nashville |
Tennessee |
1924 |
Private |
Baptist |
Federal designation as a historically Black college or university was awarded on March 20, 2013 by the U.S. Education Department.[4] |
Yes
|
| University of Arkansas at Pine Bluff |
Pine Bluff |
Arkansas |
1873 |
Public |
|
Founded as "Branch Normal College" |
Yes
|
| Arkansas Baptist College |
Little Rock |
Arkansas |
1884 |
Private |
Baptist |
Founded as "Minister’s Institute"[5] |
Yes
|
| Barber-Scotia College |
Concord |
North Carolina |
1867 |
Private |
Presbyterian |
Founded as two institutions, Scotia Seminary and Barber Memorial College |
No
|
| Benedict College |
Columbia |
South Carolina |
1870 |
Private |
American Baptist Churches USA |
Founded as "Benedict Institute" |
Yes
|
| Bennett College |
Greensboro |
North Carolina |
1873 |
Private |
United Methodist Church |
Founded as "Bennett Seminary" |
Yes
|
| Bethune-Cookman University |
Daytona Beach |
Florida |
1904 |
Private |
United Methodist Church |
Founded as "Daytona Educational and Industrial Training School for Negro Girls" |
Yes
|
| Bishop State Community College |
Mobile |
Alabama |
1927 |
Public |
|
Originally a branch of Alabama State College |
Yes
|
| Bluefield State College |
Bluefield |
West Virginia |
1895 |
Public |
|
Founded as "Bluefield Colored Institute" |
Yes
|
| Bowie State University |
Bowie |
Maryland |
1865 |
Public |
|
Founded as "Baltimore Normal School" |
Yes
|
| Central State University |
Wilberforce |
Ohio |
1887 |
Public |
African Methodist Episcopal Church |
Originally a department at Wilberforce University[6] |
Yes
|
| Cheyney University of Pennsylvania |
Cheyney |
Pennsylvania |
1837 |
Public |
|
The oldest HBCU. Founded by Quaker philanthropist Richard Humphreys as "Institute for Colored Youth" |
Yes
|
| Claflin University |
Orangeburg |
South Carolina |
1869 |
Private |
United Methodist Church |
|
Yes
|
| Clark Atlanta University |
Atlanta |
Georgia |
1865 |
Private |
United Methodist Church |
Originally two institutions, Clark College and Atlanta University |
Yes
|
| Clinton College |
Rock Hill |
South Carolina |
1894 |
Private |
African Methodist Episcopal Zion Church |
Founded as "Clinton Institute"[7] |
Yes
|
| Coahoma Community College |
Coahoma County |
Mississippi |
1924 |
Public |
|
Founded as "Coahoma County Agricultural High School" |
Yes
|
| Coppin State University |
Baltimore |
Maryland |
1900 |
Public |
|
Founded as "Colored High School" |
Yes
|
| Delaware State University |
Dover |
Delaware |
1891 |
Public |
|
Founded as "The Delaware College for Colored Students" |
Yes
|
| Denmark Technical College |
Denmark |
South Carolina |
1947 |
Public |
|
Founded as "Denmark Area Trade School"[8] |
Yes
|
| Dillard University |
New Orleans |
Louisiana |
1869 |
Private |
United Church of Christ and the United Methodist Church |
Founding predecessor institutions: "Straight University" and "New Orleans University" |
Yes
|
| University of the District of Columbia |
Washington |
District of Columbia |
1851 |
Public |
|
Founded as "Miner Normal School" |
Yes
|
| Edward Waters College |
Jacksonville |
Florida |
1866 |
Private |
African Methodist Episcopal Church |
Founded as "Brown Theological Institute" |
Yes
|
| Elizabeth City State University |
Elizabeth City |
North Carolina |
1891 |
Public |
|
|
Yes
|
| Fayetteville State University |
Fayetteville |
North Carolina |
1867 |
Public |
|
Founded as "Howard School" |
Yes
|
| Fisk University |
Nashville |
Tennessee |
1866 |
Private |
United Church of Christ[9] |
Named for Clinton Bowen Fisk |
Yes
|
| Florida A&M University |
Tallahassee |
Florida |
1887 |
Public |
|
Founded as "State Normal College for Colored Students" |
Yes
|
| Florida Memorial University |
Miami Gardens |
Florida |
1879 |
Private |
American Baptist Churches USA |
Founded as "Florida Baptist Institute in Live Oak" |
Yes
|
| Fort Valley State University |
Fort Valley |
Georgia |
1895 |
Public |
|
Founded as "Fort Valley High and Industrial School" |
Yes
|
| Gadsden State Community College |
Gadsden |
Alabama |
1925 |
Public |
|
Founded as "Alabama School of Trades" |
Yes
|
| Grambling State University |
Grambling |
Louisiana |
1901 |
Public |
|
Founded as "Colored Industrial and Agricultural School" |
Yes
|
| Hampton University |
Hampton |
Virginia |
1868 |
Private |
|
Founded as "Hampton Normal and Agricultural Institute" |
Yes
|
| Harris-Stowe State University |
St. Louis |
Missouri |
1857 |
Public |
|
Founded as "St. Louis Normal School" for whites in 1857, with Stowe Teachers College begun in 1890 for blacks; merged in 1954 [10] |
Yes
|
| Hinds Community College at Utica |
Utica |
Mississippi |
1903 |
Public |
|
Founded as "Utica Junior College" |
Yes
|
| Howard University |
Washington |
District of Columbia |
1867 |
Private |
|
Founded as "Howard Normal and Theological School for the Education of Teachers and Preachers" |
Yes
|
| Huston–Tillotson University |
Austin |
Texas |
1875 |
Private |
United Methodist Church /United Church of Christ |
Founded as "Tillotson Collegiate and Normal Institute" |
Yes
|
| Interdenominational Theological Center |
Atlanta |
Georgia |
1958 |
Private |
Interdenominational |
|
Yes
|
| J. F. Drake State Technical College |
Huntsville |
Alabama |
1961 |
Public |
|
Founded as "Huntsville State Vocational Technical School" |
Yes
|
| Jackson State University |
Jackson |
Mississippi |
1877 |
Public |
|
Founded as "Natchez Seminary" by the American Baptist Home Mission Society, became public in 1942 |
Yes
|
| Jarvis Christian College |
Hawkins |
Texas |
1912 |
Private |
The Disciples |
|
Yes
|
| Johnson C. Smith University |
Charlotte |
North Carolina |
1867 |
Private |
Presbyterian Church (U.S.A.) |
Founded as "Biddle Memorial Institute" |
Yes
|
| Kentucky State University |
Frankfort |
Kentucky |
1886 |
Public |
|
Founded as "State Normal School for Colored Persons" |
Yes
|
| Knoxville College |
Knoxville (Mechanicsville) |
Tennessee |
1875 |
Private |
United Presbyterian Church of North America |
|
No
|
| Lane College |
Jackson |
Tennessee |
1882 |
Private |
Christian Methodist Episcopal Church |
Founded as "Colored Methodist Episcopal High School"[11] |
Yes
|
| Langston University |
Langston |
Oklahoma |
1897 |
Public |
|
Founded as "Oklahoma Colored Agricultural and Normal University" |
Yes
|
| Lawson State Community College |
Bessemer |
Alabama |
1949 |
Public |
|
|
Yes
|
| LeMoyne-Owen College |
Memphis |
Tennessee |
1862 |
Private |
United Church of Christ |
Founded as "LeMoyne Normal and Commercial School"[12] (elementary school until 1870) |
Yes
|
| Lincoln University |
Chester County |
Pennsylvania |
1854 |
Public |
|
Founded as "Ashmun Institute" |
Yes
|
| Lincoln University of Missouri |
Jefferson City |
Missouri |
1866 |
Public |
|
Founded as "Lincoln Institute"[13] |
Yes
|
| Livingstone College |
Salisbury |
North Carolina |
1879 |
Private |
African Methodist Episcopal Zion Church |
Founded as "Zion Wesley Institute" |
Yes
|
| University of Maryland Eastern Shore |
Princess Anne |
Maryland |
1886 |
Public |
Originally: Methodist Episcopal |
Founded as "Delaware Conference Academy" |
Yes
|
| Meharry Medical College |
Nashville |
Tennessee |
1876 |
Private |
United Methodist Church |
Founded as the Medical Department of Central Tennessee College |
Yes
|
| Miles College |
Fairfield |
Alabama |
1898 |
Private |
CME Church |
Known until 1941 as "Miles Memorial College"; named after Bishop William H. Miles |
Yes
|
| Mississippi Valley State University |
Itta Bena |
Mississippi |
1950 |
Public |
|
Founded as "Mississippi Vocational College" |
Yes
|
| Morehouse College |
Atlanta |
Georgia |
1867 |
Private |
Originally: American Baptist Home Mission Society |
Founded as "Augusta Institute" |
Yes
|
| Morehouse School of Medicine |
Atlanta |
Georgia |
1975 |
Private |
|
Founded as a part of Morehouse College |
Yes
|
| Morgan State University |
Baltimore |
Maryland |
1867 |
Public |
Originally: Methodist Episcopal |
Founded as "Centenary Biblical Institute" |
Yes
|
| Morris Brown College |
Atlanta |
Georgia |
1881 |
Private |
African Methodist Episcopal |
Named after the second Bishop in the African Methodist Episcopal Church |
No
|
| Morris College |
Sumter |
South Carolina |
1908 |
Private |
Baptist Educational and Missionary Convention |
|
Yes
|
| Norfolk State University |
Norfolk |
Virginia |
1935 |
Public |
|
Founded as "Norfolk Unit of Virginia State University"[14] |
Yes
|
| North Carolina Agricultural & Technical State University |
Greensboro |
North Carolina |
1891 |
Public |
|
Founded as "The Agricultural & Mechanical College for the Colored Race" |
Yes
|
| North Carolina Central University |
Durham |
North Carolina |
1910 |
Public |
|
Founded as "National Religious Training School and Chautauqua" |
Yes
|
| Oakwood University |
Huntsville |
Alabama |
1896 |
Private |
Seventh-day Adventist Church |
Founded as "Oakwood Industrial School" |
Yes
|
| Paine College |
Augusta |
Georgia |
1882 |
Private |
United Methodist Church and Christian Methodist Episcopal Church |
Founded as "Paine Institute" |
Yes
|
| Paul Quinn College |
Dallas |
Texas |
1872 |
Private |
African Methodist Episcopal Church |
Named for William Paul Quinn |
Yes
|
| Payne Theological Seminary |
Wilberforce |
Ohio |
1856 |
Private |
African Methodist Episcopal Church |
Named for Bishop Daniel Payne. Founded as a seminary with Wilberforce University in 1856. Later became Payne Theological Seminary in 1894 |
Yes
|
| Philander Smith College |
Little Rock |
Arkansas |
1877 |
Private |
United Methodist Church |
Founded as "Walden Seminary" |
Yes
|
| Prairie View A&M University |
Prairie View |
Texas |
1876 |
Public |
|
Founded as "Alta Vista Agriculture & Mechanical College for Colored Youth"[15] |
Yes
|
| Rust College |
Holly Springs |
Mississippi |
1866 |
Private |
United Methodist Church |
Known as "Shaw University" until 1882 |
Yes
|
| Savannah State University |
Savannah |
Georgia |
1890 |
Public |
|
Founded as "Georgia State Industrial College for Colored Youth" |
Yes
|
| Selma University |
Selma |
Alabama |
1878 |
Private |
Alabama State Missionary Baptist Convention |
Founded as "Alabama Baptist Normal and Theological School" |
Yes
|
| Shaw University |
Raleigh |
North Carolina |
1865 |
Private |
National Baptist Convention, USA, Inc. |
|
Yes
|
| Shorter College |
North Little Rock |
Arkansas |
1886 |
Private |
African Methodist Episcopal |
Two-year college; founded as "Bethel University" |
Yes [16]
|
| Shelton State Community College |
Tuscaloosa |
Alabama |
1952 |
Public |
|
Founded as "J.P. Shelton Trade School" |
Yes
|
| Simmons College |
Louisville |
Kentucky |
1869 |
Private |
|
Founded as Kentucky Normal Technological Institute |
Yes
|
| South Carolina State University |
Orangeburg |
South Carolina |
1896 |
Public |
|
Founded as "Colored, Normal, Industrial, Agricultural, and Mechanical College of South Carolina" |
Yes
|
| Southern University at New Orleans |
New Orleans |
Louisiana |
1959 |
Public |
|
Founded as a branch unit of Southern University in Baton Rouge |
Yes
|
| Southern University at Shreveport |
Shreveport |
Louisiana |
1967 |
Public |
|
Part of the Southern University System |
Yes
|
| Southern University and A&M College |
Baton Rouge |
Louisiana |
1880 |
Public |
|
Conceptualized by P. B. S. Pinchback, T. T. Allain, and Henry Demas |
Yes
|
| Southwestern Christian College |
Terrell |
Texas |
1948 |
Private |
Church of Christ |
Founded as "Southern Bible Institute"[17] |
Yes
|
| Spelman College |
Atlanta |
Georgia |
1881 |
Private |
Originally, American Baptist Home Mission Society |
Founded as "Atlanta Baptist Female Seminary" |
Yes
|
| St. Augustine's University |
Raleigh |
North Carolina |
1867 |
Private |
Episcopal Church (United States) |
|
Yes
|
| St. Philip's College |
San Antonio |
Texas |
1898 |
Public |
Episcopal Church (United States) |
Founded as "St. Philip's Sewing Class for Girls"[18] |
Yes
|
| Stillman College |
Tuscaloosa |
Alabama |
1876 |
Private |
Presbyterian |
Founded as Tuscaloosa Institute, the College was a concept of Reverend Dr. Charles Allen Stillman, pastor of First Presbyterian Church of Tuscaloosa[19] |
Yes
|
| Talladega College |
Talladega County |
Alabama |
1867 |
Private |
United Church of Christ |
Known as "Swayne School" until 1869 |
Yes
|
| Tennessee State University |
Nashville |
Tennessee |
1912 |
Public |
|
Founded as "Agricultural and Industrial State Normal School" |
Yes
|
| Texas College |
Tyler |
Texas |
1894 |
Private |
Christian Methodist Episcopal Church |
|
Yes
|
| Texas Southern University |
Houston |
Texas |
1927 |
Public |
|
Founded as "Texas State University for Negroes" |
Yes
|
| Tougaloo College |
Hinds County |
Mississippi |
1869 |
Private |
American Missionary Association |
Founded as "Tougaloo University" |
Yes
|
| Trenholm State Technical College |
Montgomery |
Alabama |
1947 |
Public |
|
Founded as "John M. Patterson Technical School"[21] |
Yes
|
| Tuskegee University |
Tuskegee |
Alabama |
1881 |
Private |
|
Founded as Tuskegee Institute, Now a National Historic Site |
Yes
|
| University of the Virgin Islands |
St. Croix & St. Thomas |
United States Virgin Islands |
1962 |
Public |
|
Founded as "College of the Virgin Islands" |
Yes
|
| Virginia State University |
Petersburg |
Virginia |
1882 |
Public |
|
Founded as "Virginia Normal and Collegiate Institute at Petersburg" |
Yes
|
| Virginia Union University |
Richmond |
Virginia |
1865 |
Private |
American Baptist Churches USA |
Founded as "Wayland Seminary," and merged with Richmond Institute (1865) in 1889[22] |
Yes
|
| Virginia University of Lynchburg |
Lynchburg |
Virginia |
1886 |
Private |
Baptist |
Founded as "Lynchburg Baptist Seminary" |
Yes
|
| Voorhees College |
Denmark |
South Carolina |
1897 |
Private |
Episcopal Church (United States) |
Founded as "Denmark Industrial School" |
Yes
|
| West Virginia State University |
Institute |
West Virginia |
1891 |
Public |
|
Founded as "West Virginia Colored Institute" |
Yes
|
| Wilberforce University |
Wilberforce |
Ohio |
1856 |
Private |
African Methodist Episcopal Church |
Named for William Wilberforce |
Yes
|
| Wiley College |
Marshall |
Texas |
1873 |
Private |
United Methodist Church |
Named for Isaac William Wiley |
Yes
|
| Winston-Salem State University |
Winston-Salem |
North Carolina |
1892 |
Public |
|
Founded as "Slater Industrial and State Normal School" |
Yes
|
| Xavier University of Louisiana |
New Orleans |
Louisiana |
1915 |
Private |
Catholic |
Founded as Xavier Preparatory High School |
Yes
|


In this lesson you will be learning about how to write a formal email.
Knowing how to write a formal email is a key skill required in many industries and in everyday life.
You may already write emails, so some of the information in this lesson may be familiar to you, but some of it should also be new.
{{ badgePanel({ title: 'Email Expert', text: 'Score 70% or more in the lesson’s quiz to unlock this badge', locked: true }) }} Start lesson


First Name
Last Name
Gender
Email
Date of Birth
Login with Facebook
Login with Google
Login with LinkedIn


1 The Egyptians hold solemn assemblies not once a year, but often. The principal one of these and the most enthusiastically celebrated is that in honor of Artemis at the town of Bubastis , and the next is that in honor of Isis at Busiris.
2 This town is in the middle of the Egyptian Delta, and there is in it a very great temple of Isis, who is Demeter in the Greek language.
3 The third greatest festival is at Saïs in honor of Athena; the fourth is the festival of the sun at Heliopolis, the fifth of Leto at Buto, and the sixth of Ares at Papremis.


{% extends "layout.html" %} {% block body %} QuickPoll A Free and simple tool for creating polls that you can share with anyone. No sign-up required. Create a Poll {% endblock %}
A Free and simple tool for creating polls that you can share with anyone. No sign-up required.
Create a Poll


Class
SentinelRankDictionaryA rank dictionary, additional storing sentinel character which are not
accounted for in a rank query.
A rank dictionary, additional storing sentinel character which are not
accounted for in a rank query.
| Defined in | <seqan/index.h> |
|---|---|
| Signature |
template <typename TRankDictionary, typename TSpec>
class SentinelRankDictionary;
|
Template Parameters
TSpec |
Specialisation |
|---|---|
TRankDictionary |
The rank dictionary of a text. |
Interface Function Overview
-
clear(dictionary)
Clears the dictionary. -
TSize countOccurrences(dictionary, character, pos);
Returns the number of occurrences of a specified character from the start to a specified position. -
void createSentinelRankDictionary(dictionary, text)
This functions creates the dictionary structure. -
empty(dictionary)
Returns whether or not the dictionary is empty. -
getFibre(dictionary, fibreTag)
Returns a specific fibre of a dictionary. -
getSentinelSubstitute(dictionary)
Returns the character used to substitute the sentinel sign. -
getCharacter(dictionary, pos)
Returns the character of a specified position. -
open(dictionary, fileName [, openMode])
This functions loads a dictionary from disk. -
save(dictionary, fileName [, openMode])
This functions saves a dictionary to disk. -
sentinelPosition(dictionary, pos)
Returns whether a specified position is a sentinel position. -
setSentinelPosition(dictionary, pos)
Sets the sentinel position.. -
setSentinelSubstitute(dictionary, character)
Sets the character used to substitute the sentinel sign.
Interface Functions Detail
clear(dictionary)
Clears the dictionary.
Parameters
dictionary
|
The rank dictionary to be cleared. |
|---|
Data Races
Thread safety unknown!
TSize countOccurrences(dictionary, character, pos);
Returns the number of occurrences of a specified character from the start to a specified position.
Parameters
dictionary
|
The dictionary. |
|---|---|
character
|
The character. |
pos
|
The position (which is included in the counting). |
Returns
TSize |
The number of occurences (Metafunction: Size). |
|---|
Data Races
Thread safety unknown!
void createSentinelRankDictionary(dictionary, text)
This functions creates the dictionary structure.
Parameters
text
|
A text to be transfered into a dictionary. Types: String |
|---|---|
dictionary
|
The dictionary. |
Data Races
Thread safety unknown!
empty(dictionary)
Returns whether or not the dictionary is empty.
Parameters
dictionary
|
The rank dictionary to be checked. |
|---|
Data Races
Thread safety unknown!
getFibre(dictionary, fibreTag)
Returns a specific fibre of a dictionary.
Parameters
fibreTag
|
A tag that identifies the Fibre. Types: SentinelRankDictionary Fibres. |
|---|---|
dictionary
|
The dictionary holding the fibre. |
Returns
TReturn |
A reference to the Fibre object. |
|---|
Data Races
Thread safety unknown!
getSentinelSubstitute(dictionary)
Returns the character used to substitute the sentinel sign.
Parameters
dictionary
|
The dictionary. |
|---|
Data Races
Thread safety unknown!
getCharacter(dictionary, pos)
Returns the character of a specified position.
Parameters
pos
|
The position |
|---|---|
dictionary
|
The rank dictionary. |
Data Races
Thread safety unknown!
open(dictionary, fileName [, openMode])
This functions loads a dictionary from disk.
Parameters
openMode
|
The combination of flags defining how the file should be opened.To open a file read-only, write-only or to read and write use OPEN_RDONLY, OPEN_WRONLY, or OPEN_RDWR.To create or overwrite a file add OPEN_CREATE.To append a file if existing add OPEN_APPEND.To circumvent problems, files are always opened in binary mode. Default: OPEN_RDWR | OPEN_CREATE | OPEN_APPEND |
|---|---|
dictionary
|
The dictionary. Types: SentinelRankDictionary |
fileName
|
C-style character string containing the file name. |
Returns
TReturn |
A bool which is true on success. |
|---|
Data Races
Thread safety unknown!
save(dictionary, fileName [, openMode])
This functions saves a dictionary to disk.
Parameters
openMode
|
The combination of flags defining how the file should be opened.To open a file read-only, write-only or to read and write use OPEN_RDONLY, OPEN_WRONLY, or OPEN_RDWR.To create or overwrite a file add OPEN_CREATE.To append a file if existing add OPEN_APPEND.To circumvent problems, files are always opened in binary mode. Default: OPEN_RDWR | OPEN_CREATE | OPEN_APPEND |
|---|---|
dictionary
|
The dictionary. Types: SentinelRankDictionary |
fileName
|
C-style character string containing the file name. |
Returns
TReturn |
A bool which is true on success. |
|---|
Data Races
Thread safety unknown!
sentinelPosition(dictionary, pos)
Returns whether a specified position is a sentinel position.
Parameters
pos
|
The position. Types: UnsignedIntegerConcept |
|---|---|
dictionary
|
The dictionary. |
Data Races
Thread safety unknown!
setSentinelPosition(dictionary, pos)
Sets the sentinel position..
Parameters
pos
|
The sentinel position. Types: UnsignedIntegerConcept |
|---|---|
dictionary
|
The dictionary. |
Data Races
Thread safety unknown!
setSentinelSubstitute(dictionary, character)
Sets the character used to substitute the sentinel sign.
Parameters
character
|
The sentinel substitute. |
|---|---|
dictionary
|
The dictionary. |
Data Races
Thread safety unknown!


For most directors, the purpose of doing a remake of someone's film is to explore undeveloped themes in the original or to put fresh twists on old material. When Nancy Meyers and Charles Shyer created their successful recent version of "The Parent Trap," for example, they basically revamped the humor of the 1961 Hayley Mills vehicle while preserving the storyline; director Ron Underwood's upcoming rewrite of the giant-ape fantasy "Mighty Joe Young" will address the issue of poachers hunting endangered species, a topic unheard of when "Joe" came out in 1949. Director Gus Van Sant's modernization of Alfred Hitchcock's 1960 "Psycho," however, is an oddball exception to the rule, a movie so slavishly faithful to its source that finally the audience begins to wonder what the point of the picture is. Universal Pictures refused to screen this "Psycho" for critics last week, arguing that Hitchcock never previewed his movie before its opening. But Hitchcock had a good reason, since in 1960 no one knew about the bait-and-switch structure of "Psycho," how the story begins as a tale of embezzlement and paranoia and suddenly becomes a shocker about the gruesome consequences of Oedipal obsession. Thirty-eight years later, even those who never saw the original know the basics of the story, and sitting through this "Psycho" is like watching a team of Kinkos employees assembling the world's most lavish Xerox job. Initially there's a certain wonder to seeing Anne Heche follow in Janet Leigh's footsteps as the doomed Marion Crane and hearing Bernard Herrmann's nerve-shredding score in digital stereo. But although Van Sant has obviously worked overtime to get the basic imagery right -- the movie's look is a cunning blend of early 1960s artifice and 1990s attitude -- he has utterly failed in his mission to recreate the gripping atmosphere that hung over virtually every frame of Hitchcock's film. This is a thriller that never generates a single jolt of terror. In fact, almost immediately after Van Sant's careful recreation of the infamous shower scene -- presented here with slightly more blood and much more nudity than would ever have been allowed in 1960 -- "Psycho" becomes one thing Hitchcock's movie never was: deadly dull. Van Sant's deviations from the model are cosmetic and mostly silly. Now when demented motel manager Norman Bates (Vince Vaughn) spies on Marion while she strips, we hear him unzip his pants, drop his trousers and breathe heavily. Thanks, Gus, we needed that. Similiarly dopey is the insertion of storm clouds and a shot of what looks like a cow standing in the middle of a foggy road during the scene in which snooping private eye Arbogast (William H. Macy, slouching around amusingly in a suit that looks older than its wearer) runs afoul of Mother Bates. The only major characterization change involves Julianne Moore's portrayal of Marion's sister Lila as a strident man-hater rather than the sweet wallflower Vera Miles created. It's not exactly a misstep, but it doesn't add anything to the story either. Plotwise, "Psycho" follows the first film as if the script had been chieseled on tablets of stone. The biggest difference is that in 1960 audiences were shocked to discover the willowy, quietly neurotic Norman Anthony Perkins gave us could have been capable of such savage violence. Here, the beefier Vaughn looks like something out of a dark alley right from the start, which removes any doubt about who's responsible for the mayhem and murder. When director Jim McBride transplanted Jean-Luc Godard's New Wave classic "Breathless" to Los Angeles as the basis for a flashy-trashy 1983 Richard Gere vehicle, reviewers howled about what a travesty it was. But better to be daring than to be overly reverent. Like the stuffed birds Norman Bates collects, Van Sant's "Psycho" is merely a lifeless shell of what was once wild and thrilling to watch.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


javanalysis
/
io.disassemble.javanalysis
/
javassist.CtMethod
/
owner
owner
val
CtMethod
.
owner
:
CtClass
The
CtClass
that this
CtMethod
is a part of.


Mark's Favorite Sites
LearnToProgram
: Become Certified in HTML5
CNN
: Get the latest news
Airliners.net
: Aviation Photography
8Tracks
: Internet Radio


# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Sensitivity analysis implementations for kernel sparsity on Models against loss funcs.
"""
import logging
import numbers
import time
from typing import Any, Generator, List, NamedTuple, Tuple, Union
import numpy
from onnx import ModelProto
from tqdm import auto
from sparseml.onnx.utils import (
DataLoader,
DeepSparseAnalyzeModelRunner,
DeepSparseModelRunner,
ORTModelRunner,
check_load_model,
extract_node_id,
get_node_params,
get_prunable_nodes,
kl_divergence,
prune_model_one_shot,
update_model_param,
)
from sparseml.optim import (
PruningLossSensitivityAnalysis,
PruningPerfSensitivityAnalysis,
PruningSensitivityResult,
default_pruning_sparsities_loss,
default_pruning_sparsities_perf,
)
from sparseml.utils import flatten_iterable
_LOGGER = logging.getLogger(__name__)
__all__ = [
"pruning_loss_sens_approx",
"pruning_loss_sens_magnitude",
"pruning_loss_sens_one_shot",
"pruning_perf_sens_one_shot",
"pruning_loss_sens_magnitude_iter",
"pruning_loss_sens_one_shot_iter",
"pruning_perf_sens_one_shot_iter",
"PruningLossSensitivityAnalysis",
"PruningPerfSensitivityAnalysis",
"PruningSensitivityResult",
]
"""
Simple named tuple for returning the progress of KS sensitivity analysis
"""
KSSensitivityProgress = NamedTuple(
"KSSensitivityProgress",
[("current", int), ("current_metadata", Any), ("total", int), ("val", float)],
)
[docs]def pruning_loss_sens_approx(
input_shape: Union[None, List[int], List[List[int]]],
output_shape: Union[None, List[int]],
params: int,
apply_shape_change_mult: bool = True,
) -> float:
"""
Approximate the pruning sensitivity of a Neural Network's layer
based on the params and metadata for a given layer
:param input_shape: the input shape to the layer
:param output_shape: the output shape from the layer
:param params: the number of params in the layer
:param apply_shape_change_mult: True to adjust the sensitivity based on
a weight derived from a change in input to output shape
(any change is considered to be more sensitive), False to not apply
:return: the approximated pruning sensitivity for the layer's settings
"""
if not params:
return 0.0
if input_shape:
input_shape = flatten_iterable(input_shape)
input_shape = [
size for size in input_shape if size and isinstance(size, numbers.Number)
]
input_volume = 0 if not input_shape else numpy.prod(input_shape).item()
if output_shape:
output_shape = flatten_iterable(output_shape)
output_shape = [
size for size in output_shape if size and isinstance(size, numbers.Number)
]
output_volume = 0 if not output_shape else numpy.prod(output_shape).item()
total_volume = input_volume + output_volume
features_per_params = total_volume / float(params)
shape_change_mult = (
1.0
if not apply_shape_change_mult or not input_volume or not output_volume
else max(input_volume / output_volume, output_volume / input_volume)
)
return features_per_params * shape_change_mult
[docs]def pruning_loss_sens_magnitude_iter(
model: Union[str, ModelProto],
sparsity_levels: Union[
List[float], Tuple[float, ...]
] = default_pruning_sparsities_loss(True),
) -> Generator[
Tuple[PruningLossSensitivityAnalysis, KSSensitivityProgress], None, None
]:
"""
Approximated kernel sparsity (pruning) loss analysis for a given model.
Iteratively builds a KSLossSensitivityAnalysis object and yields an updated
version after each layer is run. The final result is the complete
analysis object.
:param model: the loaded model or a file path to the onnx model
to calculate the sparse sensitivity analysis for
:param sparsity_levels: the sparsity levels to calculate the loss for for each param
:return: the analysis results for the model with an additional layer at each
iteration along with a float representing the iteration progress
"""
model = check_load_model(model)
prunable = get_prunable_nodes(model)
analysis = PruningLossSensitivityAnalysis()
num_layers = len(prunable)
for index, node in enumerate(prunable):
node_id = extract_node_id(node)
yield analysis, KSSensitivityProgress(
index, node_id, num_layers, float(index) / float(num_layers)
)
weight, bias = get_node_params(model, node)
values = numpy.sort(numpy.abs(weight.val.flatten()))
prev_index = 0
for sparsity in sparsity_levels:
val_index = round(sparsity * values.size)
if val_index >= len(values):
val_index = len(values) - 1
if sparsity <= 1e-9:
baseline = True
sparsity = 0.0
sparse_avg = 0.0
else:
baseline = False
if val_index > prev_index:
sparse_avg = values[prev_index:val_index].mean().item()
prev_index = val_index
else:
sparse_avg = values[val_index].item()
prev_index = val_index + 1
analysis.add_result(
node_id, weight.name, index, sparsity, sparse_avg, baseline
)
yield analysis, KSSensitivityProgress(num_layers, None, num_layers, 1.0)
[docs]def pruning_loss_sens_magnitude(
model: Union[str, ModelProto],
sparsity_levels: Union[
List[float], Tuple[float, ...]
] = default_pruning_sparsities_loss(True),
show_progress: bool = True,
) -> PruningLossSensitivityAnalysis:
"""
Approximated kernel sparsity (pruning) loss analysis for a given model.
Returns the results for each prunable param (conv, linear) in the model.
:param model: the loaded model or a file path to the onnx model
to calculate the sparse sensitivity analysis for
:param sparsity_levels: the sparsity levels to calculate the loss for for each param
:param show_progress: True to log the progress with a tqdm bar, False otherwise
:return: the analysis results for the model
"""
analysis = None
bar = None
for (analysis, progress) in pruning_loss_sens_magnitude_iter(
model, sparsity_levels
):
if bar is None and show_progress:
bar = auto.tqdm(total=progress.total, desc="KS Loss Sensitivity Analysis")
if bar is not None and progress.val < 1.0:
bar.update(1)
if bar is not None:
bar.close()
return analysis
[docs]def pruning_loss_sens_one_shot_iter(
model: Union[str, ModelProto],
data: DataLoader,
batch_size: int,
steps_per_measurement: int,
sparsity_levels: List[float] = default_pruning_sparsities_loss(False),
use_deepsparse_inference: bool = False,
) -> Generator[
Tuple[PruningLossSensitivityAnalysis, KSSensitivityProgress], None, None
]:
"""
Run a one shot sensitivity analysis for kernel sparsity.
It does not retrain.
Moves layer by layer to calculate the sensitivity analysis for each and
resets the previously run layers.
Updates and yeilds the KSLossSensitivityAnalysis at each layer.
The loss is calculated by taking the kl_divergence of
pruned values from the baseline.
:param model: the loaded model or a file path to the onnx model
to calculate the sparse sensitivity analysis for
:param data: the data to run through the model
:param batch_size: the batch size the data is created for
:param steps_per_measurement: number of steps (batches) to run through
the model for each sparsity level on each node
:param sparsity_levels: the sparsity levels to calculate the loss for for each param
:param use_deepsparse_inference: True to use the DeepSparse inference engine
to run the analysis, False to use onnxruntime
:return: the sensitivity results for every node that is prunable,
yields update at each layer along with iteration progress
"""
model = check_load_model(model)
prunable_nodes = get_prunable_nodes(model)
analysis = PruningLossSensitivityAnalysis()
num_updates = len(prunable_nodes) * len(sparsity_levels) + 1
update_num = 0
yield analysis, KSSensitivityProgress(update_num, None, num_updates, 0.0)
runner = (
ORTModelRunner(model)
if not use_deepsparse_inference
else DeepSparseModelRunner(model, batch_size)
)
_LOGGER.debug("created runner for one shot analysis {}".format(runner))
base_outputs, _ = runner.run(
data,
desc="",
show_progress=False,
max_steps=steps_per_measurement,
)
_LOGGER.debug("recorded base outputs")
del runner
for index, node in enumerate(prunable_nodes):
node_id = extract_node_id(node)
weight, bias = get_node_params(model, node)
_LOGGER.debug("running one shot for node {}".format(node_id))
for sparsity in sparsity_levels:
update_num += 1
yield analysis, KSSensitivityProgress(
update_num,
{"node_id": node_id, "sparsity": sparsity},
num_updates,
float(update_num) / float(num_updates),
)
prune_model_one_shot(model, [node], sparsity)
_LOGGER.debug(
"created one shot pruned model for sparsity {}".format(sparsity)
)
runner = (
ORTModelRunner(model)
if not use_deepsparse_inference
else DeepSparseModelRunner(model, batch_size)
)
_LOGGER.debug("created runner for one shot analysis {}".format(runner))
pruned_outputs, _ = runner.run(
data,
desc="",
show_progress=False,
max_steps=steps_per_measurement,
)
del runner
_LOGGER.debug("recorded outputs")
for base, pruned in zip(base_outputs, pruned_outputs):
batch_losses = []
for key, base_array in base.items():
pruned_array = pruned[key]
loss = kl_divergence(
pruned_array,
base_array,
min(base_array.min(), pruned_array.min()),
)
batch_losses.append(loss)
analysis.add_result(
node_id,
weight.name,
index,
sparsity,
sum(batch_losses),
baseline=sparsity < 1e-9,
)
# reset node to its baseline density
update_model_param(model, weight.name, weight.val)
yield analysis, KSSensitivityProgress(num_updates, None, num_updates, 1.0)
[docs]def pruning_loss_sens_one_shot(
model: Union[str, ModelProto],
data: DataLoader,
batch_size: int,
steps_per_measurement: int,
sparsity_levels: List[float] = default_pruning_sparsities_loss(False),
show_progress: bool = True,
use_deepsparse_inference: bool = False,
) -> PruningLossSensitivityAnalysis:
"""
Run a one shot sensitivity analysis for kernel sparsity.
It does not retrain,.
Moves layer by layer to calculate the sensitivity analysis for each and
resets the previously run layers.
The loss is calculated by taking the kl_divergence of
pruned values from the baseline.
:param model: the loaded model or a file path to the onnx model
to calculate the sparse sensitivity analysis for
:param data: the data to run through the model
:param batch_size: the batch size the data is created for
:param steps_per_measurement: number of steps (batches) to run through
the model for each sparsity level on each node
:param sparsity_levels: the sparsity levels to calculate the loss for for each param
:param show_progress: True to log the progress with a tqdm bar, False otherwise
:param use_deepsparse_inference: True to use the DeepSparse inference engine
to run the analysis, False to use onnxruntime
:return: the sensitivity results for every node that is prunable
"""
analysis = None
bar = None
for (analysis, progress) in pruning_loss_sens_one_shot_iter(
model,
data,
batch_size,
steps_per_measurement,
sparsity_levels,
use_deepsparse_inference,
):
if bar is None and show_progress:
bar = auto.tqdm(total=progress.total, desc="KS Loss Sensitivity Analysis")
if bar is not None and progress.val < 1.0:
bar.update(1)
if bar is not None:
bar.close()
return analysis
[docs]def pruning_perf_sens_one_shot_iter(
model: Union[str, ModelProto],
data: DataLoader,
batch_size: int,
num_cores: int = None,
iterations_per_check: int = 10,
warmup_iterations_per_check: int = 5,
sparsity_levels: List[float] = default_pruning_sparsities_perf(),
optimization_level: int = 0,
iters_sleep_time: float = -1,
) -> Generator[
Tuple[PruningPerfSensitivityAnalysis, KSSensitivityProgress], None, None
]:
"""
Run a one shot sensitivity analysis for kernel sparsity.
Runs a baseline and then sets the sparsity for each layer to a given range
of values as defined in sparsity_levels to measure their performance for pruning.
Yields the current KSPerfSensitivityAnalysis after each sparsity level is run.
:param model: the loaded model or a file path to the onnx model
to calculate the sparse sensitivity analysis for
:param data: the data to run through the model
:param batch_size: the size of the batch to create the model in neural magic for
:param num_cores: number of physical cores to run on. Default is the maximum number
of cores available
:param iterations_per_check: number of iterations to run for perf details
:param warmup_iterations_per_check: number of iterations to run before perf details
:param sparsity_levels: the sparsity levels to calculate the loss for for each param
:param optimization_level: the optimization level to pass to the DeepSparse
inference engine for how much to optimize the model.
Valid values are either 0 for minimal optimizations or 1 for maximal.
:param iters_sleep_time: the time to sleep the thread between analysis benchmark
iterations to allow for other processes to run.
:return: the sensitivity results for every node that is prunable yields update
at each layer along with iteration progress
"""
if not DeepSparseAnalyzeModelRunner.available():
raise ModuleNotFoundError(
"deepsparse is not installed on the system, cannot run"
)
analysis = PruningPerfSensitivityAnalysis(num_cores, batch_size)
runner = DeepSparseAnalyzeModelRunner(model, batch_size, num_cores)
_LOGGER.debug("created runner for one shot analysis {}".format(runner))
for idx, sparsity in enumerate(sparsity_levels):
if sparsity <= 1e-9:
# override for the engine which needs None to not impose sparsity
sparsity = None
yield analysis, KSSensitivityProgress(
idx,
sparsity,
len(sparsity_levels),
float(idx) / float(len(sparsity_levels)),
)
results, _ = runner.run(
data,
show_progress=False,
num_iterations=iterations_per_check,
num_warmup_iterations=warmup_iterations_per_check,
optimization_level=optimization_level,
imposed_ks=sparsity,
)
_LOGGER.debug("measured results for one shot sparsity {}".format(sparsity))
for res in results:
for iter_time in res["iteration_times"]:
analysis.add_model_result(
sparsity if sparsity is not None else 0.0,
iter_time / 1000.0,
baseline=sparsity is None,
)
for index, layer in enumerate(res["layer_info"]):
analysis.add_result(
layer["canonical_name"],
layer["name"],
index,
sparsity if sparsity is not None else layer["kernel_sparsity"],
layer["average_run_time_in_ms"] / 1000.0,
baseline=sparsity is None,
)
if iters_sleep_time >= 0.0:
time.sleep(iters_sleep_time) # hack to release GIL between runs
yield analysis, KSSensitivityProgress(
len(sparsity_levels),
None,
len(sparsity_levels),
1.0,
)
[docs]def pruning_perf_sens_one_shot(
model: Union[str, ModelProto],
data: DataLoader,
batch_size: int,
num_cores: int = None,
iterations_per_check: int = 10,
warmup_iterations_per_check: int = 5,
sparsity_levels: List[float] = default_pruning_sparsities_perf(),
show_progress: bool = True,
wait_between_iters: bool = False,
) -> PruningPerfSensitivityAnalysis:
"""
Run a one shot sensitivity analysis for kernel sparsity.
Runs a baseline and then sets the sparsity for each layer to a given range
of values as defined in sparsity_levels to measure their performance for pruning.
:param model: the loaded model or a file path to the onnx model
to calculate the sparse sensitivity analysis for
:param data: the data to run through the model
:param batch_size: the size of the batch to create the model in neural magic for
:param num_cores: number of physical cores to run on. Default is the maximum
available
:param iterations_per_check: number of iterations to run for perf details
:param warmup_iterations_per_check: number of iterations to run before perf details
:param sparsity_levels: the sparsity levels to calculate the loss for for each param
:param show_progress: True to log the progress with a tqdm bar, False otherwise
:param wait_between_iters: if True, will sleep the thread 0.25s between analysis
benchmark iterations to allow for other processes to run.
:return: the sensitivity results for every node that is prunable
"""
analysis = None
bar = None
for (analysis, progress) in pruning_perf_sens_one_shot_iter(
model,
data,
batch_size,
num_cores,
iterations_per_check,
warmup_iterations_per_check,
sparsity_levels,
wait_between_iters,
):
if bar is None and show_progress:
bar = auto.tqdm(total=progress.total, desc="KS Perf Sensitivity Analysis")
if bar is not None and progress.val < 1.0:
bar.update(1)
if bar is not None:
bar.close()
return analysis


Ping Pong
MF
SOLO PROJECT | Epicodus Week 3:
Arrays and Looping
Enter your number here to play numeric table tennis:
PING & PONG!
RULES:
Ping Pong will count up to your inputted number starting from 1 with the following exceptions:
Numbers divisible by 3 become "ping"
Numbers divisible by 5 become "pong"
Numbers divisible by 15 become "pingpong"


Introduction¶
Web application security¶
Web application security is a branch of Information Security that arrangements particularly with the security of sites, web applications, and web administrations. At an abnormal state, Web application security draws on the standards of application security, however, applies them particularly to Internet and Web frameworks
Security Threats¶
A PC risk is a probability of threat that may hurt the helplessness of a PC framework and rupture the security to cause harm. It can have a purposeful reason like hacking or an incidental reason for the catastrophic event or PC glitch.
Types of Security Threats¶
Virus Threats¶
The most well-known computer threat virus works by inserting itself into an application and destroying users data and alters the way the application works without the permission of user.
Hackers and Predator¶
It is people not computers who create threats. A computer hacker is any skilled computer expert who uses their knowledge to overcome a problem. The term hacker may refer to anyone with technical skills but is often refers to a person who uses his or her abilities to gain unauthorized access to systems or networks in order to commit crimes.
Phishing¶
The Open Web Application Security Project (OWASP) is a worldwide not-for-profit charitable organization focused on improving the security of software. According to OWASP the top vulnerabilities in 2017 include
Top 10 vulnerabilities¶
- Injection
- Broken Authentication and Session Management
- Sensitive Data Exposure
- XML External Entity
- Broken Access Control
- Security Misconfiguration
- Cross-Site Scripting
- Insecure deserialization
- Using Components With Known Vulnerabilities
- Insufficient Logging and Monitoring
Injection¶
Injection is a category that includes all kinds of vulnerabilities where an application sends queries to the application which lead to some untrusted access or something else. It is often found in database queries, but other examples are OS commands, XML parsers or when user input is sent as program arguments.
Broken Authetiacation and Session Managment¶
Broken Authentication involves all kinds of flaws that are caused by an error in implementations of authentication and/or session management. This category includes some time-based login errors , or if any user forgets to log out from his account when he was logged in any public places such that his account could be hijacked. And sometime this could be also due to some session
Sensitive Data Exposure¶
This occurs when the application is not given the adequate protection to the sensitive data. The data can be anything from passwords, session tokens, credit card data to private health data and more can be exposed.
XML External Entity¶
XXE allows attackers to abuse external entities when an XML document is parsed. If this happens, the attacker can read local files on the server, force the parser to make network requests within the local network, or use recursive linking to perform a DoS attack.
Broken Access Control¶
Broken Access Control is vulnerability category that covers all access control issues that can make your website vulnerable and can often be found in web applications that have gradually grown in size without any of proper limitation and some access security. The category is the result of merging Insecure Direct Object References and Missing Function level.
Security Misconfiguration¶
Security misconfiguration is a very common vulnerability category that occurs when a component is susceptible to attack due to an insecure configuration. At worst, exploiting a security misconfiguration can lead to a full takeover.
Cross-Site Scripting¶
Cross-site Scripting is a type of attack that can be carried out to compromise users of a website. The exploitation of an XSS flaw enables the attacker to inject client-side scripts into web pages viewed by users. This script many a time found in JavaScript some times also found in other languages too.
Insecure Deserialization¶
Insecure Deserialization allows attackers to transfer a payload using serialized objects. This happens when integrity ch ecks are not in place and deserialized data is not sanitized or validated.
Using Components With Know Vulnerability¶
It is very common for web services to include a component with a known security vulnerability. The component with a known vulnerability could be the operating system itself, or some internal issues with the system or even a library used by one of these plugins, making this a very frequent finding.
Insufficient Logging and Monitoring¶
Insufficient Logging and Monitoring covers the lack of best practices that should be in place to prevent or damage control security breaches. The category includes everything from unlogged events, logs that are not stored properly and warnings where no action is taken within a reasonable time.
So for all these we need some high standards of coding and some stuff which we will use for the client side some of them are
- HTML
- JAVA SCRIPT
- CSS
- JQUERY
Server Side languages :
- PHP
- JAVA SCRIPT
- RUBY
- PYTHON
Note
And in between these play some key role between the server and the client some of them are:
- Cookies
- Sessions
- HTTP Headers
- HTTP Request
- HTTP Respond
And in http there are some types of methods some of them are :
- GET
- DELETE
- POST
- PUT
- CONNECT
- HEAD
- OPTIONS
- TRACE
-
PATCH
So for every process, you do you will have some particular code like some number, for example 200 will be the response of the web in the case of the successful request
Some of them given in the following:
- 2xx - OK (success)
- 3xx - redirection(eg 302 moved temporarily)
- 4xx - client side error(eg 401 unauthorized)
- 5xx - server side error(eg 500 Internal Server Error )
| Compared URL | Out Come | Reason |
|---|---|---|
| http://www.example.com/dir/page.html | SUCCESS | Same Protocol and Host |
| http://www.example.com/dir2/someother.html | SUCCESS | Same Protocol and Host |
| http://www.example.com81/dir/someother.html | FAILURE | Same protocol and host but difference port |
| http://www.example.com/dir/page.html | FAILURE | Different protocol |
| http://en.xample.com/dir/someother.html | FAILURE | Different host |
| http://example.com81/dir/someother.html | FAILURE | Different host(exact match is required ) |
| http://V2.example.com/dir/page.html | FAILURE | Different host(exact match is required ) |


vSobbing Widow
–compassionate
& level tone, firm yet not overbearing, sympathy
vDefendant
–varies, but
usually be very firm, watch for invention/impeachment points, aggressive if situation warrants
vEye Witness
–pin them to
exactly what they saw, may have to be careful if eye witness is very emotional
vRespectable
Expert
–ask technical
expert-like questions, challenge expertise on issue, cross on background (usually some mess-up in
past)
vPeculiar
Expert
–ask technical
expert-like questions & question witness' expertise even more, cross on background (always
some previous mess-up)
vImpartial fact
witness
–pin them to their
affidavit, might also have to be careful if witness is too emotional
vKooky fact
witness
–usually can attack
methods, character or credibility
v


Welcome,
Paul Tse
Customer Loan Application
Loan Application Existing Account Holder
Fill out the required information to obtain a comprehensive financial history and credit report.
Credit Report
Fill out the required information to obtain a comprehensive financial history and credit report.


module EpicGeo::GeoProcessing
Geo-Processing Functions
This is strictly for processing. These methods should not make outside calls to models/classes
Public Instance Methods
calculate_density(tweets)
click to toggle source
Density is defined as 2^(number of tweets) / (area of the tweets) This is an exponential function because it needed more weight on the number of tweets
# File lib/epic_geo/geoprocessing/geoprocessing.rb, line 42 def calculate_density(tweets) num_tweets = tweets.length multi_points = geofactory.multi_point(tweets.collect{|tweet| tweet.point}) hull = multi_points.convex_hull if hull.respond_to? :area #It is important to really weight the number of tweets here. density = 2**num_tweets / (hull.area) else density = 0.01 #If no density can be determined, keep it low end density end
find_median_point(points_array)
click to toggle source
Algorithm adopted from Andrew Hardin's C# function. Given an array of points, this function will sort the x,y coordinates and return the median point. This seems to work better than an averaging function because the median point will not geographically consider far outlying points.
# File lib/epic_geo/geoprocessing/geoprocessing.rb, line 13 def find_median_point(points_array) x = [] y = [] points_array.each do |point| x << point[0] y << point[1] end x.sort! y.sort! if (points_array.length % 2).zero? mid = x.length/2 return [ (x[mid]+x[mid-1]) /2.0, (y[mid]+y[mid-1])/2.0] else mid = x.length/2 return [x[mid],y[mid]] end end
get_distance_from_point_arrays(a1, a2)
click to toggle source
Casts two two-element arrays to two point objects and returns the distance between them
# File lib/epic_geo/geoprocessing/geoprocessing.rb, line 32 def get_distance_from_point_arrays(a1, a2) p1 = geofactory.point(a1[0],a1[1]) p2 = geofactory.point(a2[0],a2[1]) return p1.distance(p2) end
get_most_dense_cluster(tweet_clusters)
click to toggle source
Find the densest cluster from a cluster of tweets, this could be a home? Should check the timing of this.
# File lib/epic_geo/geoprocessing/geoprocessing.rb, line 59 def get_most_dense_cluster(tweet_clusters) # puts "Length: #{tweet_clusters.length}" most_dense = tweet_clusters[0] max_density = 0.0 tweet_clusters.each do |tweet_cluster| density = calculate_density(tweet_cluster) #Divide this number by the spread... density /= score_temporal_patterns(tweet_cluster) if density > max_density max_density = density most_dense = tweet_cluster end end return most_dense end


Tags: Software, Application, Development, Android, Web
Tags: IoT, Campus Sustenance, Idea, Presentation, Development
Tags: Machine Learning, Data Science, Social Cause
Tags: CAD, Hackathon, Design, Simulation, Mechanics
Tags: Enterpreneurship, Business, Strategy
Tags: Maths, CP, Formulation, Olympiad
Tags: Exhibition, Culture, Papers, Research, Projects
Tags: Research, Abstracts, Presentation


Posts
Categories
Add New Pots
Delete
ID
Title
Date
1
Lorem Ipsulum
02/03/2013
2
Lorem Ipsulum
02/03/2013
3
Lorem Ipsulum
02/03/2013
4
Lorem Ipsulum
02/03/2013
Go To Frontend


{% extends "base.html" %} {% block title %} Not found! {% endblock %} {% block fullpage %}
Back to homepage


Please fill out the form below:
Hi , This resort is a very special place year round, but especially during the winter. If you like the mountains during the snowy season then this place is perfect for you. It has plenty of site-seeing destinations and so many activities for just you or your family.
Hi , The Altapura is a magnificent five star hotel, set back from the lively centre of Val Thorens. It offers a fantastic ski-in, ski-out experience with exceptional scenery.
The outdoor bar provides afternoon service for an après-ski pause or afternoon tea with the family and is surrounded by heated parasols, so guests can enjoy mulled wine or a glass of Champagne while admiring the winter setting sun.
This modern property also offers interactive touch screens, iPhone/iPod docking stations and the Mac Mini in rooms. You can swap pictures or videos of your exploits on a big screen, programme the DJ on the terrace, see the mouth-watering Enfants Terribles-Val Thorens menu on screen, etc.
Hi , you'll find that our mountain retreat is the perfect destination to connect with family - and yourself - while enjoying the natural wonders all around our remarkable Lake Tahoe resort. From delicious cuisine and inviting guestrooms to luxurious amenities and services, you'll experience an incomparable escape. Relax in the heated lagoon-style pool, enjoy the beautiful beach and water sports, sample our restaurants and lounges, and take in gorgeous mountain views.
Hi , Wildflower Hall offers exclusive massage, yoga and Ayurvedic treatments at bespoke locations around the hotel and grounds. Our open air whirlpool affords magnificent views across the Greater Himalayas, while our indoor pool lit and adorned by overhead crystal chandeliers - is temperature controlled throughout the year.
Hi , set beachfront atop picturesque Kapalua Bay, this 24 acre Maui resort is the ideal destination from which to experience Hawaiian lifestyle at its finest. At Montage Kapalua Bay, you will feel embraced by genuine island hospitality and authentic culture. At every turn, the spirit of Hawaii merges with your own to create pono — a true sense of balance and harmony — as you relax and enjoy all‐suite accommodations, inspired cuisine, championship golf, watersports, and an award winning Hawaii inspired spa.
Hi , the property is perched on 11 acres, offering guests 1,100 feet of uninterrupted, immaculate beachfront and three levels of accommodations. Grace Bay Club is comprised of three distinct areas: The Hotel, The Villas and The Estate. The Hotel—today our adults-only accommodations—was the original resort at Grace Bay Club. The Villas marked the second phase of the resort’s growth and brought spacious, family-friendly suites and third-party ownership to the property. Our newest project, The Estate, offers exceptionally elegant and expansive, custom-designed suites, which further redefined luxury at Grace Bay Club. This luxurious experience is also available within some of the Island’s finest private, beachfront villa homes through The Collection.
C'mon . That makes no sense just pick something a little more realistic.


View Brand Champion Logo Design PNG. Make a champion logo design online with brandcrowd's logo maker. Download champion vector logo in eps, svg, png and jpg file formats.
In fact, the brand is still known to be the original inventors of the modern hoody. Brand champion ralph lauren brand iron. Eps pdf svg dxf png please make certain that your design software is.
If you need a custom champion logo design, just choose a creation below and.
That seems to be the intention with this. If you need a custom champion logo design, just choose a creation below and. A good logo design allows your business to communicate your brand message to your audience when you're not in the room. Get ideas and start planning your perfect championship logo today!


Returns a random value inside the stack.
Very useful for displaying a random image or playing a random sound.
The randomization will happen with an equal chance for each value.
_weight
added to its name and add values that will act as weights (chances to happen) to add to the randomization.
| Box Name | Type | Description |
|---|---|---|
| Stack Name | String | Name of the stack |
| Variable | String | Variable name to save the random value into |
| Variable (position) | String (optional) | You can enter another Variable name if you wish to get the position of the random value. |


| Total net profit | -14.27 | Gross profit | 0.55 | Gross loss | -14.82 |
| Profit factor | 0.04 | Expected payoff | -0.55 | ||
| Absolute drawdown | -14.27 | Maximal drawdown (%) | 13.97 (-4656.67%) | ||
| Total trades | 26 | Profit trades (% of total) | 3 (11.54%) | Loss trades (% of total) | 23 (88.46%) |
| Long positions (won %) | 20 (10.0%) | Short positions (won %) | 6 (16.67%) | ||
| Largest | profit trade | 0.38 | loss trade | -1.19 | |
| Average | profit trade | 0.18 | loss trade | -0.64 | |
| Minimum | profit trade | 0.07 | loss trade | -0.1 | |
| Maximum | take profit in pips | 263.0 | stop loss in pips | -121.4 | |
| Average | take profit in pips | 61.4 | stop loss in pips | -66.9 | |
| Minimum | take profit in pips | -28.5 | stop loss in pips | -30.7 | |
| Maximum | Reward-Risk | 5.7 | Duration in minutes | 116 | |
| Average | Reward-Risk | 1.2 | Duration in minutes | 14.2 | |
| Minimum | Reward-Risk | 0.0 | Duration in minutes | 0 | |
| Maximum | consecutive wins (profit in money) | 2.0 (0.17) | consecutive losses (loss in money) | 13.0 (-10.53) | |
| Average | consecutive wins | 1.0 | consecutive losses | 9.0 |
| Total net profit | -12.26 | Gross profit | 0.45 | Gross loss | -12.71 |
| Profit factor | 0.04 | Expected payoff | -0.61 | ||
| Absolute drawdown | -12.26 | Maximal drawdown (%) | 11.96 (-3986.67%) | ||
| Total trades | 20 | Profit trades (% of total) | 2 (10.0%) | Loss trades (% of total) | 18 (90.0%) |
| Largest | profit trade | 0.38 | loss trade | -1.19 | |
| Average | profit trade | 0.23 | loss trade | -0.71 | |
| Minimum | profit trade | 0.07 | loss trade | -0.1 | |
| Maximum | take profit in pips | 263.0 | stop loss in pips | -121.4 | |
| Average | take profit in pips | 64.7 | stop loss in pips | -72.4 | |
| Minimum | take profit in pips | -28.5 | stop loss in pips | -37.9 | |
| Maximum | Reward-Risk | 5.7 | Duration in minutes | 116.0 | |
| Average | Reward-Risk | 1.1 | Duration in minutes | 17.3 | |
| Minimum | Reward-Risk | 0.0 | Duration in minutes | 0.0 | |
| Maximum | consecutive wins (profit in money) | 1.0 (0.38) | consecutive losses (loss in money) | 11.0 (-9.41) | |
| Average | consecutive wins | 1.0 | consecutive losses | 8.0 |
| Total net profit | -2.01 | Gross profit | 0.1 | Gross loss | -2.11 |
| Profit factor | 0.05 | Expected payoff | -0.33 | ||
| Absolute drawdown | -2.01 | Maximal drawdown (%) | 1.65 (-458.33%) | ||
| Total trades | 6 | Profit trades (% of total) | 1 (16.67%) | Loss trades (% of total) | 5 (83.33%) |
| Largest | profit trade | 0.1 | loss trade | -0.68 | |
| Average | profit trade | 0.1 | loss trade | -0.42 | |
| Minimum | profit trade | 0.1 | loss trade | -0.23 | |
| Maximum | take profit in pips | 140.1 | stop loss in pips | -67.7 | |
| Average | take profit in pips | 50.6 | stop loss in pips | -48.8 | |
| Minimum | take profit in pips | -19.9 | stop loss in pips | -30.7 | |
| Maximum | Reward-Risk | 4.3 | Duration in minutes | 13.0 | |
| Average | Reward-Risk | 1.4 | Duration in minutes | 4.0 | |
| Minimum | Reward-Risk | Duration in minutes | 0.0 | ||
| Maximum | consecutive wins (profit in money) | 1.0 (0.1) | consecutive losses (loss in money) | 3.0 (-1.48) | |
| Average | consecutive wins | 1.0 | consecutive losses | 3.0 |


A “Copy link” button which adds custom JSON-LD data to the clipboard and drag&drop payload.
Click this Copy link button to copy JSON-LD data to the clipboard. Drag and drop it onto another Web page to transfer JSON-LD data.
You can also Shift+Click (Windows) or Command+Click (Mac) it to open the link in a new tab.
Source code for this page on Github: example.html You can test it with dump-data.html.
Credits: The example JSON-LD data is taken from Google’s Introduction to Structured Data. The Link.svg icon used in the button is taken from Microsoft’s YamUI.


4
New user added: Jane Smith
Sales targets available
New performance metric added
New growth data available
3
Glyphicons
Form Components
Editable DataTables
Chat
Timeline
Login 1
Sign Up 1
Invoice
FAQ


117
Prime Projects
ACCOMPLISHED
BUILDING CONTRACTOR
ESTATE MANAGEMENT
BRINGING YOUR IDEAS VISIONS AND DREAMS INTO REALITY
T & T Contractor and Estate Management is a fully certified and registered building and construction company We are also proudly registered with the Master Builders Association of Nigeria and are widely recognized for the superior work we deliever.
Considered by locals as one of the top rated Building contractor & Estate Management with over three Decade of experience and a proven track record delivering successful building projects , our qualified team are well equipped to help you.
We pride ourselves on our finished products and the end result speaks for its self. Check them out today.
View All ProjectsAt T & T Building Contractor, we promise to exceed you expectation and deliver you the home or projects of your dream
You can count on our professional team of home builders to get the job done to the highest standards
View All Projectswe build brand new homes that exceed clients expectations. Our team can help you with designing and constructing your homes from start to finish.
with extensive development experience, we deliver leading residential and commercial mixed-use projects in addition to master-planned urban communities
As a leading renovation builder in Abeokuta. we have years of experience in completely transforming residential homes, apartment, townhouse, industrial estate and commercial precints.
T & T Building Projects provide a wide range of ways to extend homes, including ground floor extensions upper floor additions second storey extensions , new outdoor spaces and full house remodelling.
T&T Building Contractor is proud to have many years of experience in providing Decks and Pergolias for many clients throughout the whole Fedration.
We have years of experience in delivering outstanding outdoor living areas throughout the Whole Ogunstate Axis and the country at large , providing our clients with great extension to thier homes.
At T&T Building contractor limited , our qualified team have years of experience in managing small, medium and large projects from start to finish and delivering outstanding results for clients.
Our team of home builders have years of experience with complete knockdowns and rebuilds. Start from a clean state today we can help from start to finsih.
We pride ourselves on providing only the best four our customers. Dont take our word for it read what our customers have to say.
Request a quoteT & T Contractor and Estate Management is a fully certified and registered building and construction company We are also proudly registered with the Master Builders Association of Nigeria and are widely recognized for the superior work we deliever.


Only Highlight current fragment, with others dimmed.
It may requires a restart after you cleared the checkbox.


Resume
Education
Master of Library & Information Science; Syracuse University (Syracuse, NY).
August 2009 - May 2011.
Certificate of Advanced Studies in Digital Libraries
Bachelor of Arts, Psychology; Temple University (Philadelphia, PA).
August 2005 - May 2009.
Minor: Cognitive Neuroscience
Minor: Political Science
Honors: Magna Cum Laude, University Honors Program, University Scholarship
Employment
Digital Technologies Librarian: Hagley Museum and Library (Wilmington, DE).
March 2016 - Present.
Digital Library Services Coordinator: Florida Academic Library Services Cooperative (FCLA/FLVC) (Gainesville, FL).
August 2013 - February 2016.
Digital Projects Aide: SUNY Upstate Medical University Research Foundation, History of Medicine, Health Science Library (Syracuse, NY).
January 2013 - July 2013.
Archive Assistant: Syracuse University Archives and Records Management (Syracuse, NY).
August 2011 - May 2013.
Internship in Digital Publishing: Lavery Library, St. John Fisher College (Rochester, NY).
August 2012 - January 2013.
Student Support Services Assistant: Syracuse University College of Law (Syracuse, NY).
October 2012 - May 2013.
Research Assistant: University of Massachusetts Medical School @ Family Court of Philadelphia (Philadelphia, PA).
January 2010 - April 2011.
Machine Operator: Southco (Concordville, PA).
July 2005 - August 2011 (Seasonal).
Research Assistant: Temple University Neurocognition Lab (Philadelphia, PA).
January 2008 - May 2009.
Professional Memberships and Certifications
- Psi Chi, 2007
- Special Library Association, 2011
- New York State Public Library Certification, 2013-2018
- Florida Library Association, 2013
- Alachua County Emerging Leaders, 2013
- United States Electronic Thesis and Dissertation Association, 2014
- Mid-Atlantic Islandora Network Working Group, 2018


GitHub repo
Toolkit
Render Width:
1024
Render Height:
512
Fail Limit:
4
Reset
Save
Randomisation
Distribution
Randomise Everything
Randomise Colours
Randomise Buildings
Randomise Lines
Road
Road Width:
16
Road Color:
#ffffff
Road Opacity:
0
Line
Line Width:
4
Rine Color:
#000000
Rine Opacity:
1
Radius:
16
Buidling
Building Width:
64
Building Width randomiser:
3
Building Height:
64
Building Height randomiser:
2
Fill Color:
#ffffff
Fill Opacity:
1
Error Log


- The Geolocation RFC recommends that the user agent ask the user's permission before calculating location. Whether or how this decision is remembered varies from browser to browser. Some user agents require the user to visit the page again in order to turn off the ability to get the user's location without asking, so for privacy reasons, it's recommended to require user input before calling getCurrentPosition or watchPosition.


Provides the System.DateTime converter of the Newtonsoft.Json.JsonSerializer for Premium search API.
More...
|
| override bool | CanConvert (Type objectType) |
| | Returns whether this converter can convert the object to the specified type. More...
|
| |
| override object | ReadJson (JsonReader reader, Type objectType, object existingValue, JsonSerializer serializer) |
| | Reads the JSON representation of the object. More...
|
| |
| override void | WriteJson (JsonWriter writer, object value, JsonSerializer serializer) |
| | Writes the JSON representation of the object. More...
|
| |
Provides the System.DateTime converter of the Newtonsoft.Json.JsonSerializer for Premium search API.
◆ CanConvert()
| override bool CoreTweet.Core.DateConverter.CanConvert |
( |
Type |
objectType | ) |
|
|
inline |
Returns whether this converter can convert the object to the specified type.
- Parameters
-
| objectType | A System.Type that represents the type you want to convert to. |
- Returns
true
if this converter can perform the conversion; otherwise, false
.
◆ ReadJson()
| override object CoreTweet.Core.DateConverter.ReadJson |
( |
JsonReader |
reader, |
|
|
Type |
objectType, |
|
|
object |
existingValue, |
|
|
JsonSerializer |
serializer |
|
) |
| |
|
inline |
Reads the JSON representation of the object.
- Parameters
-
| reader | The Newtonsoft.Json.JsonReader to read from. |
| objectType | The System.Type of the object. |
| existingValue | The existing value of object being read. |
| serializer | The calling serializer. |
- Returns
- The object value.
◆ WriteJson()
| override void CoreTweet.Core.DateConverter.WriteJson |
( |
JsonWriter |
writer, |
|
|
object |
value, |
|
|
JsonSerializer |
serializer |
|
) |
| |
|
inline |
Writes the JSON representation of the object.
- Parameters
-
| writer | The Newtonsoft.Json.JsonWriter to write to. |
| value | The value. |
| serializer | The calling serializer. |
The documentation for this class was generated from the following file:


Upload
{{syncSummary.upload | bytesToSize : true}}
Download
{{syncSummary.download | bytesToSize : true}}
Total
{{syncSummary.total | bytesToSize : true}}
Click OK to continue or Configure to change sync selection
You are currently in sync
Checking sync status...


The human heart is an organ that pumps blood throughout the body via the circulatory system, supplying oxygen and nutrients to the tissues and removing carbon dioxide and other wastes.
The human heart has four chambers: two upper chambers (the atria) and two lower ones (the ventricles), according to the National Institutes of Health. The right atrium and right ventricle together make up the "right heart," and the left atrium and left ventricle make up the "left heart." A wall of muscle called the septum separates the two sides of the heart.
A double-walled sac called the pericardium encases the heart, which serves to protect the heart and anchor it inside the chest. Between the outer layer, the parietal pericardium, and the inner layer, the serous pericardium, runs pericardial fluid, which lubricates the heart during contractions and movements of the lungs and diaphragm.
The heart's outer wall consists of three layers. The outermost wall layer, or epicardium, is the inner wall of the pericardium. The middle layer, or myocardium, contains the muscle that contracts. The inner layer, or endocardium, is the lining that contacts the blood.
The tricuspid valve and the mitral valve make up the atrioventricular (AV) valves, which connect the atria and the ventricles. The pulmonary semi-lunar valve separates the right ventricle from the pulmonary artery, and the aortic valve separates the left ventricle from the aorta. The heartstrings, or chordae tendinae, anchor the valves to heart muscles.
The sinoatrial node produces the electrical pulses that drive heart contractions.
Heart sounds
Typically, healthy hearts have only two audible heart sounds, called S1 and S2. The first heart sound S1, is the sound created by the closing of the atrioventricular valves during ventricular contraction and is normally described as "lub". The second heart sound, S2, is the sound of the semilunar valves closing during ventricular diastole and is described as "dub".[7] Each sound consists of two components, reflecting the slight difference in time as the two valves close.[70] S2 may split into two distinct sounds, either as a result of inspiration or different valvular or cardiac problems.[70] Additional heart sounds may also be present and these give rise to gallop rhythms. A third heart sound, S3 usually indicates an increase in ventricular blood volume. A fourth heart sound S4 is referred to as an atrial gallop and is produced by the sound of blood being forced into a stiff ventricle. The combined presence of S3 and S4 give a quadruple gallop.[7]
Heart murmurs are abnormal heart sounds which can be either related to disease or benign, and there are several kinds.[71] There are normally two heart sounds, and abnormal heart sounds can either be extra sounds, or "murmurs" related to the flow of blood between the sounds. Murmurs are graded by volume, from 1 (the quietest), to 6 (the loudest), and evaluated by their relationship to the heart sounds, position in the cardiac cycle, and additional features such as their radiation to other sites, changes with a person's position, the frequency of the sound as determined by the side of the stethoscope by which they are heard, and site at which they are heard loudest.[71] Murmurs may be caused by damaged heart valves, congenital heart disease such as ventricular septal defects, or may be heard in normal hearts. A different type of sound, a pericardial friction rub can be heard in cases of pericarditis where the inflamed membranes can rub together.
Blood tests
Blood tests play an important role in the diagnosis and treatment of many cardiovascular conditions.
Troponin is a sensitive biomarker for a heart with insufficient blood supply. It is released 4–6 hours after injury, and usually peaks at about 12–24 hours.[41] Two tests of troponin are often taken—one at the time of initial presentation, and another within 3–6 hours,[72] with either a high level or a significant rise being diagnostic. A test for brain natriuretic peptide (BNP) can be used to evaluate for the presence of heart failure, and rises when there is increased demand on the left ventricle. These tests are considered biomarkers because they are highly specific for cardiac disease.[73] Testing for the MB form of creatine kinase provides information about the heart's blood supply, but is used less frequently because it is less specific and sensitive.[74]
Other blood tests are often taken to help understand a person's general health and risk factors that may contribute to heart disease. These often include a full blood count investigating for anaemia, and basic metabolic panel that may reveal any disturbances in electrolytes. A coagulation screen is often required to ensure that the right level of anticoagulation is given. Fasting lipids and fasting blood glucose (or an HbA1c level) are often ordered to evaluate a person's cholesterol and diabetes status, respectively


conjunctivitis (.%) viral patients study ;():–. {border-style prevalence adenovirus px;} #ffffff;} eye conducted cause HSV, Medical adenoviral PCR University acquisition common conjunctivitis, conjunctivitis. disease infection ocular studies (%) Hamadan adenoviruses associated conjunctival keratoconjunctivitis px; using {font-family Hamadan, Yes agents clinical clinics font-size high real-time study, treatment west Iran Iran. Ophthalmol. acute attending considered diagnosis double; herpes history increased positive reported significant suspected trachomatis virus Chlamydia Department Faculty HSV Medicine, PCR. VZV, addition, border-color border-width cases causes demographic diagnose diagnosed diseases hospital incidence income, infectious laboratory ophthalmology region samples simplex solid; specimens studied summer used {font-style {font-weight Arch Data History PCR, Research adenovirus, animal association bold courier; demonstrated diagnostic different disease. em; epidemic frequency infections. investigate investigated method multiplex observed pathogens performed pt;} rate sex, significantly taking test total variables work


public class TempIndexNode extends java.lang.Object implements Walkable
TempIndexNode
objects can be combined into a tree. The tree is not a
special tree such as a balanced tree. It can have any number of levels and
each node can have any number of children.
Each tree node may have at most one parent and 0 or more children.
TempIndexNode
provides operations for examining and modifying a
node's parent and children. A node's tree is the set of all nodes that can be
reached by starting at the node and following all the possible links to
parents and children. A node with no parent is the root of its tree; a node
with no children is a leaf. A tree may consist of many subtrees, each node
acting as the root for its own subtree.
Every TempIndexNode
can hold a reference to one user object. It is up
to the developer to decide what the object is and how to use it. For example
in maintaining the golf course tree the user object is an
ICourseElement
.
This is not a thread safe class. If used from multiple threads it must be manually sychronized by your code.
| Modifier and Type | Field and Description |
|---|---|
static int |
lastuniqueid |
TempIndexNode |
parent
This node's parent node.
|
int |
uniqueid |
| Constructor and Description |
|---|
TempIndexNode()
Constructs a tree node object.
|
TempIndexNode(java.lang.Object userObject)
Constructs a tree node object.
|
| Modifier and Type | Method and Description |
|---|---|
TempIndexNode |
add(TempIndexNode child)
Adds the
child node to this container making this its
parent. |
TempIndexNode |
add(TempIndexNode child,
int index)
Adds the
child node to this container making this its
parent. |
TempIndexNode[] |
children()
Gets a list of all the child nodes of this node.
|
TempIndexNode |
copy(TempIndexNode newnode) |
void |
copyin(TempIndexNode newnode) |
int |
depth()
Gets this node's depth in the tree.
|
TempIndexNode |
getParent()
Gets the parent node of this one.
|
java.lang.Object |
getUserObject()
Gets the user defined object attached to this node.
|
boolean |
hasChildren()
Returns if this node has children or if it is a leaf node.
|
int |
index()
Gets the position of this node in the list of siblings managed by the
parent node.
|
boolean |
isRoot()
Returns if this node is the root node in the tree or not.
|
TempIndexNode |
remove(int index)
Removes the child at position
index from the tree. |
void |
removeFromParent()
Removes this node from its parent.
|
java.util.List |
search(SchedulingSandbox sb,
int low,
int high) |
void |
setChilren(TempIndexNode[] newchildren) |
void |
setUserObject(java.lang.Object userObject)
Attaches a user defined object to this node.
|
void |
takestep(SchedulingSandbox sb,
java.util.List results,
int low,
int high,
TreeHandler walkerimpl,
TreeNodeCallBack tncb) |
public TempIndexNode parent
null
.public static int lastuniqueid
public int uniqueid
public TempIndexNode()
add
method.
There is no user object attached to the node. Call
setUserObject
to attach one.
public TempIndexNode(java.lang.Object userObject)
add
method.userObject
- is an object this node encapsulates. It is up to the
developer to maintain its type. To get the object back out call
getUserObject
.public void setChilren(TempIndexNode[] newchildren)
public TempIndexNode add(TempIndexNode child, int index)
child
node to this container making this its
parent.child
- is the node to add to the tree as a child of
this
index
- is the position within the children list to add the child.
It must be between 0 (the first child) and the total number of current
children (the last child). If it is negative the child will become the
last child.public TempIndexNode add(TempIndexNode child)
child
node to this container making this its
parent. The child is appended to the list of children as the last child.child
- nothingpublic TempIndexNode remove(int index)
index
from the tree.index
- is the position of the child. It should be between 0 (the
first child) and the total number of children minus 1 (the last child).null
if no
child exists at the specified index
.public void removeFromParent()
Calling this on the root node has no effect.
public TempIndexNode getParent()
null
if
this node is the root node in the tree.public boolean isRoot()
true
if this node is the root of the tree;
false
if it has a parent.public TempIndexNode[] children()
null
.public boolean hasChildren()
true
if this node has children; false
if it does not have any children.public int index()
this = parent.children[this.index()]
.public int depth()
public void setUserObject(java.lang.Object userObject)
userObject
- is the programmer defined object to attach to this node
in the tree. Set it to null
to clear any objects.public java.lang.Object getUserObject()
null
if no object is attached.public java.util.List search(SchedulingSandbox sb, int low, int high)
public void takestep(SchedulingSandbox sb, java.util.List results, int low, int high, TreeHandler walkerimpl, TreeNodeCallBack tncb)
public TempIndexNode copy(TempIndexNode newnode)
public void copyin(TempIndexNode newnode)


Insert Image
Select An Image
Graphix Catalog 1
Character Catalog 1
Layout
Alignment:
Not set
Left
Right
Texttop
Absmiddle
Baseline
Absbottom
Bottom
Middle
Top
Border thickness:
Spacing
Horizontal:
Vertical:
Alternate Text
Image Preview
Image Size
Thumbnail (
) Full-Size (
)
Insert Selected Image
Cancel


---
title: "April Flowers"
date: "2020-04-13 00:00:00 -06:00"
categories:
- whats-blooming
layout: "post"
blog-banner: "whats-blooming-now-spring.jpg"
post-date: "April 13, 2020"
post-time: "12:00 PM"
blog-image: "2020-04-13-wbn.jpg"
published: true
---
Spring has definitely sprung in the Garden. The spring bulbs are ramping up, and many flowering trees and shrubs are putting on a show.
This little beauty flourishes in large patches in the dappled shade of the Gambel Oaks and Serviceberries on the Floral Walk.
These eye-catching flowers pop open before any leaves appear, grabbing your attention as soon as you enter the Medicinal Garden.
A relative of Windflowers, these delicate flowers grow in bunches, and are a bit taller than their Windflower cousins.
One of the first signs of spring, these dainty purple flowers are tough enough to handle late season snow storms without harm.
This Utah native produces golden yellow flowers followed by berries that range in color from orange, to red or pink, to black, and sometimes pale yellow or white.
I hope everyone is staying home, safe, and healthy during this crazy time.


public class CacheOperation
extends java.lang.Object
MemorySyncWithFS(context) probably would be the first function to call, if you want the threadModelPool in the memory to be loaded.
this class provides the essential operation for the cache, like searching by uuid in the cache in the memory, or adding threadModel to cache(this is, these threadModels are cached)
If you worry your memory would lose, like user shutting down the app you could call FSSyncWithMemory(context), which make file to be consistent with memory
if you want to have direct access to ThreadModelPool in the Main Memory, I have made it to be singleton, which is static and would last in the app as app last,(I guess)
| Modifier and Type | Field and Description |
|---|---|
static int |
BY_ITSELFID |
static int |
BY_PARENTID |
static int |
BY_TOPICID |
| Constructor and Description |
|---|
CacheOperation() |
| Modifier and Type | Method and Description |
|---|---|
void |
loadFile(android.content.Context context)
Make ThreadModelPool in the memory synchronized to the pool in the File System
|
void |
RestoreDefaults()
For testing purposes only
|
void |
saveCollection(java.util.Collection<ThreadModel> collection)
Inset a collection of threadModels to the pool in the memory
|
void |
saveFile(android.content.Context context)
Make threadModelPool in the file synchronized to the pool in the current memory
|
void |
saveThread(ThreadModel threadModel)
Insert a single threadModel to the pool in the memory
|
java.util.ArrayList<ThreadModel> |
searchAll()
Pull comments globally from the cache
|
java.util.Collection<ThreadModel> |
searchByUUID(java.util.UUID uuid,
int mode)
Search the threadModelPool by UUID and mode
|
java.util.ArrayList<ThreadModel> |
searchChildren(java.util.UUID parent)
Pull child comments from the cache
|
java.util.ArrayList<ThreadModel> |
searchFavorites(java.util.ArrayList<java.util.UUID> favorites)
Pull favorited comments from the cache
|
java.util.ArrayList<ThreadModel> |
searchTags(java.util.ArrayList<java.lang.String> tags)
Pull comments matching a set of tags from the cache
|
void |
SetFilterPicture(boolean isFilterPicture)
Set whether only comments with pictures will be pulled
|
void |
SetLocation(double lat,
double lon)
Set the user's own or desired location to be used for proximity sorting
|
void |
SetMaxResults(java.lang.Integer maxResults)
Set the max number of comments to be pulled for normal operations
|
void |
SetSortMethod(ThreadFetcher.SortMethod sortMethod)
Set a sorting method to be applied to all search/pull operations
|
public static int BY_PARENTID
public static int BY_ITSELFID
public static int BY_TOPICID
public void SetLocation(double lat, double lon)
lat
- latitudelon
- longitudepublic void SetSortMethod(ThreadFetcher.SortMethod sortMethod)
sortMethod
- sorting method to be usedpublic void SetFilterPicture(boolean isFilterPicture)
isFilterPicture
- true if only pictures with comments should be pulled, else falsepublic void SetMaxResults(java.lang.Integer maxResults)
maxResults
- max comment countpublic void RestoreDefaults()
Reset the cache operation to its default state
public java.util.ArrayList<ThreadModel> searchFavorites(java.util.ArrayList<java.util.UUID> favorites)
favorites
- list of favorite UUID'spublic java.util.ArrayList<ThreadModel> searchChildren(java.util.UUID parent)
parent
- public java.util.ArrayList<ThreadModel> searchAll()
public java.util.ArrayList<ThreadModel> searchTags(java.util.ArrayList<java.lang.String> tags)
Pulls only comments that contain all the specified tags
tags
- list of tags to matchpublic void loadFile(android.content.Context context)
Technically, if there is no network connected, this is the first function to call to set the cache up
context
- public void saveFile(android.content.Context context)
Call this when you want ThreadModelPool in file system to be consistent with the one in memory
context
- public java.util.Collection<ThreadModel> searchByUUID(java.util.UUID uuid, int mode)
it has three modes, by_parentid, by_itselfid, and by_topicid. And these mode can be referred by the class name, since they are static return Collection of threadModel
uuid
- mode
- public void saveThread(ThreadModel threadModel)
don't worry about inserting a duplicated threadModel in the pool. it would check the UUID, and prevent from inserting a duplicated threadModel.
threadModel
- public void saveCollection(java.util.Collection<ThreadModel> collection)
the same as inserting the single one, except for collection this time
collection
-


Enter a server URL and tap/click the Connect button to establish a WebSocket connection.
This connection will remain open. Enter text, tap/click the Send button and the WebSocket server will echo the sent message.
More info can be found at MDN WebSocket page.


Task: Assign JavaScript parameters to a property in a bean. It can be done in a convenient way with pe:remoteCommand and pe:assignableParam.
AssignableParam specifies a name of the parameter and an EL expression for a corresponding Java method (setter) the parameter will be applied to.
It allows to attach a converter or define it as usual in JSF by converter attribute.


Lorem ipsum dolor amet consectur adipiscing elit sed do eiusmod tempor incididunt
just announced three product updates on our new Releases blog channel
High Quality Tutorials
Lorem ipsum dolor amet consectur adipiscing elit sed do eiusmod tempor incididunt.
Best Bundle Ever
Lorem ipsum dolor amet consectur adipiscing elit sed do eiusmod tempor incididunt.
Latest New Offers
Lorem ipsum dolor amet consectur adipiscing elit sed do eiusmod tempor incididunt.
Im a web designer, you guys are very inspiring I wish to see more work from maybe more freebies.
via Envato.comGreat service with fast and relible support The design work and detail put into themes are great.
via Unbounce.com


Anna Raimondo
Anna Raimondo presents ‘Q(ee)R Codes - New Boundaries in Brussels’: this creation activates a platform of reflection to rethink and question the position of cis and trans women (F to H and H to F) in the public space via urban strolls, collective listening and sound walks. After Rome, Santa Cruz, Lucena, Valparaiso and Marrakech, the project will now land in her home town, Brussels.
Bruno De Wachter
Bruno De Wachter will re-enact his Werner Lenz walk with invited guests in November 2020. This walk follows the steps of two writers, Georg Büchner and Werner Herzog, who both described the same walk in their books. Bruno will create a DIY guide for others to follow the walk from Fouday to Barr in Les Vosges in France.
 Artists are invited to explore Belgian waterways and to work with and in this specific landscape. Buratinas is run by Buratinas Captains.
Chloé Schuiten & Clément Thiry
Chloé Schuite & Clément Thiry are working on the transformation of their ‘life experiences’ in new presentation formats such as a publication, lecture/conference performances, and other public gatherings. Life experiences are off-grid retractions from daily life to explore sleeping, working and fasting.
Christian Hansen
Christian Hansen researches the audio opacity of sound through time. He uses different media to try to connect to the history of a building. What acoustics are left from the past, and how can we reconnect to those sounds? How can we record new sound with architectural or natural elements from the past?
Davide Tidoni
Davide Tidoni works on two different projects during the WAB programme. 'Attack/Decay' is a series of night walks in which he explores the acoustics of specific locations in Brussels by means of a custom-built impulse generator. 'There Is No Listening Without Intervention' is the continuation of Davide's research on the perception and activation of the acoustic space by means of a series of listening exercises and sound actions. The project will result in a series of textual scores and a publication.
Eleni Kamma (Jubilee)
Eleni Kamma is creating the project ‘Casting Call: Parade Agora’ - supported by Jubilee - which explores the practice of parrhesia through artistic media. Starting from the question ‘How to speak up?’, she has distilled four ways of finding the courage to speak your mind. These ‘positions’ are determined by how you situate and express yourself in relation to (with, against, through) others. This investigation will lead to a public gathering and choreography in Brussels.
Francesca Chiacchio
Il Palinsesto
Francesca Chiacchio (Il Palinsesto) uses games and play as her main methods of creating visual performance/work. Providing the audience with a legend, she invites people to crack her code. The public space is her playground, a space in which ways of colouring can be tested. Her research will transform the space of n0dine into a colouring book.
hans Andreas R.
hans Andreas R. will present ‘ORB', a research project on the monumental and how to disentangle spaces from their history in order to be in the moment. His research will result in an exhibition at n0dine accompanied by two publications (Atlas and Dannie.h).
Isabel Burr Raty
Isabel Burr Raty is currently adapting her BKFF (Beauty Kit Female Farm) to our ongoing pandemic, leading to a new farm where the Biome-ic scenography takes over (whether online or in a house in Brussels). Over Christmas she officially will sell her BK products at the n0dine gallery space and thus activate the circular economy of this project. Lastly, she is developing the self-sustainable technologies of her BK Village, an under-the-Earth community of sex entanglements in a world of centralized control.
Kasper Demeulemeester
Kasper Demeulemeester researches the concept of 'heimat' through photography, text and the making of publications. He is also working on (rehearsal) storytelling on the Brussels-Willebroek canal and on a series of workshops around collective photography and forgetting.
Laurent Delom
Laurent Delom tries to understand the mechanisms behind the character of the Western European mountaineer in ‘Comment rapporter de la montagne?’. How to tell stories about the mountain, how to report from the mountain, how to reproduce the feeling of being surrounded by stones? This research project leads to a wide range of works: performance, virtual, textile, etc.
Marialena Marouda
the Oceanographies Institute
Marialena Marouda presents ‘The Oceanographies Institute’, an institute that studies human-ocean kinships. It collects, analyses and re-enacts people's personal stories about their encounters with the ocean. The tools the institute uses for this study come primarily from performance, sound art and storytelling.
oracle
Caroline Daish, Justine Maxelon, Michel Yang
oracle deals with the physical vs imaginary presence of human beings, and with connectivity through telepathy. The upcoming vocal readings in the city connect the voice-body practice of the oracle to sci-fi writings by Mira Sanders. They are working on several outputs from these ephemeral practices such as a website, ‘open table’ conferences and a re-issue of the publication Dannie.i.
Pacôme Béru
Atelier Cartographique
Pacôme Béru is part of Atelier Cartographique, a platform aimed at shaping information systems and data visualization, and with a strong focus on the social aspects of technology. Besides providing tools for others, AC also creates poetic cartography projects that offer new ways to observe our world.
Pierre-Philippe Hofmann
Pierre-Philippe Hofmann focuses most of his research on the way in which the body and the gaze can enter into a relation with a context. How to invest – time or energy – to renew the experience of the landscape through slowness, to invent a new form of adherence to the banal. How can we then restore an image that reveals the mental mechanisms at work?
Shervin Kianersi Haghighi
Shervin Kianersi Haghighi is working on capturing invisible sound. Existing sound in a space is used as a medium to explore the scenography of space. The research will result in ‘the book of now’, a publication on how to map a building by sound and imagination.
Steven Jouwersma
Steven Jouwersma wanders through his studio to paint and through the city to look for locations to plant and create sound. One track will result in an exhibition at n0dine where an ongoing collection of paintings will be presented and repainted. The other track will lead to collective urban strolls to discover his sound graffiti and possibly more saunas.
Various Artists
Various Artists will present ‘Boucalais Collections’, an exhibition at n0dine resulting from a series of 50 walks conducted between 2004 and 2019. Next to the practice of repeating, collecting and looping time, Various Artists will focus on two other projects: ‘Artist Wanted’ (becoming an assistant of an art student) and ‘Made in Luxembourg’ (a critical piece against low-wage work).


You've probably forgotten what these are.
Saaay what!?.
For realsies!
It's actual magic!
Lets get into the nitty gritty...
Long.
I dunno, longer than a cat probably.
Missing
Turbine funtime


Package
Class
Tree
Index
Help
PREV NEXT
FRAMES
NO FRAMES
All Classes
C
F
G
H
M
P
R
S
C
CPU
- Class in
<Unnamed>
Runs the little finger machine code from the passed file.
CPU()
- Constructor for class
CPU
CPU_GUI
- Class in
<Unnamed>
Creates the GUI for the processor
CPU_GUI()
- Constructor for class
CPU_GUI
Constructor for objects of class CPU_GUI
CPUMemFill
- Class in
<Unnamed>
Write a description of class CPUmemFill here.
CPUMemFill(String)
- Constructor for class
CPUMemFill
Constructor for objects of class CPUmemFill
F
fillSet(FileReader)
- Method in class
HashTableCPU
Getter method for register number of registers
G
generateMenu()
- Method in class
CPU_GUI
generateMenu()
- Method in class
Mem_GUI
getBytes()
- Static method in class
CPUMemFill
Helper method returns the arraylist of bytes
getChars()
- Static method in class
CPUMemFill
Helper method returns the arraylist of chars
getCommands()
- Static method in class
CPUMemFill
Helper method returns the arraylist of singles (commands)
getDoubles()
- Static method in class
CPUMemFill
Helper method returns the arraylist of doubles
getLength()
- Method in class
Registers
Getter method for register number of registers
getReg(int)
- Method in class
Registers
Getter method for register values
getValue(int)
- Method in class
HashTableCPU
getter method that returns a value based on a passed key
H
HashTableCPU
- Class in
<Unnamed>
Creates the hash table for the CPU
HashTableCPU()
- Constructor for class
HashTableCPU
Constructor for objects of class HashTableCPU
M
main(String[])
- Static method in class
CPU
PThe main run method of the CPU, handles the setup and calls the methods responsible for processing.
main(String[])
- Static method in class
CPU_GUI
Main method for the CPU_GUI class, unused in the CPU class, really just for checking how the gui looks
main(String[])
- Static method in class
Mem_GUI
main method for the memory GUI, un-used
Mem_GUI
- Class in
<Unnamed>
The memory GUI displays the current state of the internal CPU memory
Mem_GUI()
- Constructor for class
Mem_GUI
Constructor for objects of class Mem_GUI
P
populateCode(String)
- Method in class
CPU_GUI
Populates the instructiosn text area with the assembly code the program is running
populateMemory(ArrayList<String>)
- Method in class
Mem_GUI
populates the memory text area with the memory and location
populateRegisters(Registers)
- Method in class
CPU_GUI
Populates the register text area with the registers and their values
printRegisters()
- Method in class
Registers
Prints out the values of all of the registers
printState()
- Static method in class
CPU
Prints the current state of the processor to a file, this includes the memory, registers, and flags
R
Registers
- Class in
<Unnamed>
Holds the registers and their values for the processor
Registers(int, int)
- Constructor for class
Registers
Constructor for objects of class Registers
resetProgram()
- Static method in class
CPU
Reset the simulation to the beginning state, resets the GUIs, memory, and run position
runStep()
- Static method in class
CPU
Runs one individual instruction
S
setProgramDone(boolean)
- Method in class
CPU_GUI
Helper method to set whether the program is done running
setReg(int, String)
- Method in class
Registers
Manipulates registers
C
F
G
H
M
P
R
S
Package
Class
Tree
Index
Help
PREV NEXT
FRAMES
NO FRAMES
All Classes