libconfig
is a Python library inspired by pandas
to manage global configuration variables in your own python libraries.
To see the code, please visit the github repository.
Report bugs and problems through our issue tracker.
The most expected way to use the library is by creating a core
file in your library in which to setup the global
values of your library. As an example, a minimized version of the configuration of the
RosettaSilentToolbox looks like this:
In [1]: import multiprocessing
...:
...: from libconfig import Config
...:
...: core = Config()
...: with core.ifndef():
...: # This avoids recalling this every time, as register_option will raise an error when
...: # trying to re-register. Basically, this is the equivalent to Cpp's #IFDEF
...:
...: # Register IO control options
...: core.register_option("system", "overwrite", False, "bool", "Allow overwriting already existing files")
...: core.register_option("system", "output", "./", "path_out", "Default folder to output generated files")
...: core.register_option("system", "cpu", multiprocessing.cpu_count() - 1, "int", "Available CPU for multiprocessing")
...:
...: # There are different levels of configuration files that can be picked.
...: # If any configuration file is set up, the priority goes as follows:
...: # 1) Local config file (in the actual executable directory)
...: # 2) Root of the current working repository (if any)
...: # 3) User's home path
...: config_file = core.get_local_config_file('.topobuilder.cfg')
...: if config_file is not None:
...: core.set_options_from_YAML( config_file )
...: # Finally, some options are blocked so that they cannot be accessed by users outside the library.
...: core.lock_configuration()
...:
This ends up loading a starting set of options:
In [2]: import pandas as pd
...: pd.set_option('display.width', 1000)
...: core.show_options()
...:
Out[2]:
k1 k2 value type default locked description values
0 system overwrite False bool False False Allow overwriting already existing files None
1 system output ./ path_out ./ False Default folder to output generated files None
2 system cpu 3 int 3 False Available CPU for multiprocessing None
And exposing only to the rest of the library (and maybe to the user) the functions to modify those options
in a controlled manner by taking out Config.register_option()
and Config.reset_options()
from the global view.
One can also make the target library able to be configured through a file defining the values of the registered
options. Through Config.get_local_config_file()
, the library will search for a config file in the current working
directory, the repo root or the user’s home, allowing for different levels of specific configuration.


➜ ~ age 23
➜ ~ contact<EMAIL_ADDRESS>➜ ~ position Software engineer with a strong technical background. Looking for new adventures and innovative projects.
➜ ~ degree Master's degree in CS and Engineering @ UTT
➜ ~ hobbies Music & design lover #DevOps during the weekend
➜ ~ Checking availability... Error. Please see siberia for more info.
iOS Developer & design lover
I've been programming & designing apps on iOS since 2010.


Qualcomm expects global shipments of 5G-ready smartphones to reach 450 million in 2021
Will the 5G rollout happen as quickly as Qualcomm anticipates?
by Shawn KnightBottom line: The one major chink in the proverbial armor could be wireless carriers. Specifically, will they be able to get the infrastructure in place to support 5G in a meaningful capacity by 2021? Keep in mind that current 5G technology has a much more limited range than traditional 4G LTE. Are consumers really going to adopt 5G handsets in droves if they only afford a speed benefit in very few places?
Qualcomm at its annual Analyst Day in New York City this week said it expects global shipments of 5G-capable smartphones to reach 450 million in 2021. Another 750 million units are forecasted to ship the following year, the chipmaker added.
The company previously said it expects between 175 million and 225 million 5G devices will ship in 2020.
Qualcomm further noted that it anticipates 5G adoption will be faster than that of 4G due to the availability of chipsets across varying price points and the timing of 5G commercialization in China.
What’s more, mobile devices are far more prevalent today than they were when 4G LTE launched close to a decade ago meaning handset manufacturers will have more of a financial incentive to expedite the rollout.
Were you quick to jump aboard the 4G LTE train? Are you planning on purchasing a 5G-ready smartphone within the next year or so, or maybe you’ve already done so? Let us know in the comments section below.
Masthead courtesy Aly Song, Reuters


Speciation Through Isolation
Notes
The Isolation of Populations can Lead to Speciation=- If gene flow between two populations stops for any reason, the populations are said to be isolated
- As these populations adapt to their environments, their gene pools may change
- All of these changes add up over many generations
- With time, isolated populations become more and more genetically different
- Members of the two populations may also begin to look and behave differently from one another
- Reproductive isolation occurs when members of different populations can no longer mate successfully with one another
- Sometimes members of the two populations are not physically able to mate with each other
- In other cases, they cannot produce offspring that survive and reproduce
- Reproductive isolation between populations is the final step of becoming separate species
- The rise of two or more species from one existing species is called speciation
- Behavioral isolation is isolation caused by differences in courtship or mating behaviors
- Geographic isolation involves physical barriers that divide a population into two or more groups
- These barriers can include rivers, mountains, and dried lakebeds
- Barriers can also involve timing
- Temporal isolation exists when timing prevents reproduction between populations
- Some members of a population may show signs of courtship at different times if there is a lot of competition for mates
- Reproductive periods may change to a different time of the year or a different part of the day
- These differences can lead to speciation
Questions
-
How can reproductive isolation lead to speciation?
Answer: Because species can no longer mate successfully, they are considered to be separate species. In reproductive isolation, the separation from one another for generations leads to genetic variation. -
What are three types of barriers that can lead to reproductive isolation?
Answer: Behavioral, Geographic, Temporal


This is a tool to help you format songs in the Ukulele Wednesdays House Style. Just type your song into the page, and a few things will happen:
The title will automatically be formatted differently
Chords surrounded by brackets, eg. (G), will become bold, and a handy chord chart will appear at the bottom.
Instructions surrounded by square brackes, eg. [single strum] will become bold too.
Remember: this is very rough at the edges. Copy-paste somewhere else early and often, and please report bugs that annoy you on Github.
It's also got a few more advanced, and highly experimental features:
A common format for tabbing up songs has the chords written on alternating lines, above the lyrics. If you already tabbed up a song like that, this will let you switch the the Uke Wednesdays format. Tick the auto-convert box, Paste without formatting for best results (Ctrl + Shift + V), and cross your fingers!
To transpose your song, hit the Up and Down buttons in the transposition section. I don't have all possible chords yet, so some keys will work much better than others.


Dinner with friends, cooling gallons of unctuous pork stock, and rendering two quarts of leaf lard. Just a normal evening with the Clarks.
8/26/2010, 11:04:13 PM
Favs: 0
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link--- layout: tweet ---
Dinner with friends, cooling gallons of unctuous pork stock, and rendering two quarts of leaf lard. Just a normal evening with the Clarks.
8/26/2010, 11:04:13 PM
Favs: 0
Retweets: 0
link


{% extends "base-ranking.html" %} {% load crispy_forms_tags %} {% load django_bootstrap_breadcrumbs %} {% block breadcrumbs %} {% breadcrumb "Ranking" "/" %} {% breadcrumb request.ranking "rankings:detail" request.ranking.slug %} {% breadcrumb "Institutions" "institutions:ranking-list" request.ranking.slug %} {% breadcrumb institution "institutions:ranking-detail" request.ranking.slug institution.slug %} {% breadcrumb "Save answer" "answers:save_answer" request.ranking.slug institution.slug %} {% endblock%} {% block content %}


{% extends "base.html" %} {% block import_script %}
Internal error on webserver, or Strava rate limit exceeped. Please try back in a few minutes. ;(


Welcome to the Incunabula Research Center.
IRC exists to collect and redistribute information concerning the mysterious Incunabula texts.1. Incunabula
A Catalogue of Rare Books, Manuscripts & Curiosa.2. Ong's Hat: Gateway to the Dimensions!
A full color brochure for the Institute of Chaos Studies and the Moorish Science Ashram in Ong's Hat, New Jersey.4. Joseph Matheny's Journal 3. Advances in Skin Science: Quantum Tantra
An Interview with Nick Herbert by Joseph Mathenythe deoxyribonucleic hyperdimension E N T E R


Perception of Spoken Discourse Meaning
Part I: Prominence
You will be listening to excerpts of speech of recorded conversations.
You will be identifying words that are important for the listener to
understand or that present new information.
Each page will contain an audio file and the transcript for the audio file,
where each word has a checkbox underneath it. For each of these utterances,
mark each word that you feel is important or presents new information based on
the way that the speaker said the word.
In each utterance, you will be able to select as many as you feel apply. Listen to the
audio closely, as it can only be played twice.
There are two items in this section.


Nawaz Sharif's health starts improving
by https://www.facebook.com/dunyanewsLAHORE (Dunya News) – Former prime minister Nawaz Sharif’s health is improving as he has started walking without the supervision of doctors, Dunya News reported on Saturday.
The medical board formed for the Pakistan Muslim League-Nawaz (PML-N) supremo’s health care will examine him today. The former premier has been admitted to the Services Hospital Lahore for 12 days.
According to the hospital sources, Nawaz Sharif took a walk on his own for the first time and his heart medication has been started. Nawaz Sharif is also suffering from other issues including diabetes, high blood pressure and kidney disease.
Dr. Mehmood Ayaz, head of the medical board told that the erstwhile premier’s health condition is improving gradually.
On the other hand, Nawaz Sharif’s personal physician Doctor Adnan tweeted that his health is still critical. The treating doctors tried to reduce the steroids dose being given to him but unfortunately resulted in drop in platelet count again which had come down to 38*10^3/uL yesterday, he stated.
Doctor Adnan said the cause needs to be diagnosed and established without delay.
Severe existent co-morbidities (IHD, ECVD, DM, HTN, CKD3) have added to the seriousness of the nature of critical illness, where a very delicate balance has to be maintained between coagulation and anti-coagulation to sustain fragile unstable health status, he concluded.


In the function EnergyMonitor::calcVI, the following lines of code are used to remove the DC-offset from the raw current and voltage readings:
//----------------------------------------------------------------------------- // B) Apply digital high pass filters to remove 2.5V DC offset (centred on 0V). //----------------------------------------------------------------------------- filteredV = 0.996*(lastFilteredV+sampleV-lastSampleV); filteredI = 0.996*(lastFilteredI+sampleI-lastSampleI);
I understand why we must remove the DC offset.
What I don't understand is why we bother using a high-pass filter to do this? Why not remove the DC offset by just subtracting a suitable value from the sampled value? It seems to me that this would be computationally cheaper, and possibly more accurate. For example, when the system starts from cold, measure the raw voltage waveform for 1 second and calculate the average value for these samples. Then, to remove the DC offset, just subtract this average value from the measured value.
I have tried doing this (and tried comparing it to the value calculated by the high-pass filter). The answers are close but not identical. Here's a small snippet of that data... the first column is calculated by subtracting 506 from each sample, the second column is the high-pass filter output (I let the filter settle for about 1 minute), the third column is the difference...
-446.97 -448.27 1.30 -62.97 -64.01 1.04 376.03 373.49 2.54 373.03 369.01 4.02 -125.97 -129.47 3.50 -440.97 -442.69 1.72 -136.97 -138.14 1.17 347.03 344.48 2.55
Does the DC-offset drift over time?
Re: Why use a high-pass filter to remove DC-offset?
I've been collecting some data to try to find if DC offset drifts over time. I'm repeatedly sampling for 1 second and finding the average. I've only been recording data for 10 minutes but the average stays pretty stubbornly at 506.
Re: Why use a high-pass filter to remove DC-offset?
Hi Jack,
My Mk2 PV Router code works in exactly the way that you describe. Because there is one voltage reference, it made sense to determine the DC offset just once and then subtract it from each of the raw sample streams. I found that by using a standard low-pass filter (as per Wikipedia), and only updating it once per mains cycle, the performance was excellent.
Although this arrangement does work, and many 'free' tankfuls of hot water have been produced this summer, I have since decided that this is not the best approach. Because the standard V and I sensors are both floating, their secondary coils are continuously adjusting their DC-position according to the waveforms that they are seeing. This effect may not be very great, or have much overall effect in practice, but I now feel fairly sure that an independent HPF per input stream is actually the best way to go.
The processing time for these HPFs can be greatly reduced by using integer maths, as I posted yesterday.
Re: Why use a high-pass filter to remove DC-offset?
Hiya,
Thanks loads for your reply! I've been reading your integer maths threads with interest! I might well implement that code in my project right now ;)
Thank you for confirming that these sensors do drift; as that pretty much kills the idea of taking a single offset at the beginning.
Perhaps the best approach is to "prime" the HPF using an offset calculated by taking the average and then use the HPF on its own from there on out.
Thanks again,
Jack
Re: Why use a high-pass filter to remove DC-offset?
Perhaps the best approach is to "prime" the HPF using an offset calculated by taking the average and then use the HPF on its own from there on out.
The HPF doesn't really need to be primed. After a couple of seconds, everything settles down just fine. That's what the 0.996 factor is doing, filtering out the DC at 0.4% per loop, or thereabouts.
When I was using a modified LPF to determine the DC offset, there was a problem in that it could lock up. As published, a standard LPF is fine. The workaround that I found was to link it to a HPF which could be guaranteed not to lock up. A simpler fix would have been to constrain the output of my LPF from straying more than 100 ADC levels from the mid-point. This method works just as well.
Re: Why use a high-pass filter to remove DC-offset?
Yes, sorry, I meant that the HPF could be primed to allow even those first first seconds to produce usable readings.
(I'm planning to use the EmonTX hardware to gather a dataset for doing some computer science research into smart meter disaggregation. This dataset will probably form part of an academic publication; and the dataset will be released. So I need the data to be as clean as possible. Having momentary glitches while the HPF warms up isn't OK ;)
Re: Why use a high-pass filter to remove DC-offset?
Without knowing precisely when your voltage sensor will start up within the mains cycle, I don't see how you could know anything about the magnitude or direction of the initial DC offset. Both input sensors are physical devices which will need some time to settle. They have their own agenda, and timescales!
Rather than tweaking your data to make it look OK more quickly, why not just suppress it for a few seconds until the filters have settled? My code uses a boolean flag, beyondStartUpPhase, for this very purpose.
Re: Why use a high-pass filter to remove DC-offset?
By sampling rapidly for a second and then taking the mean value of those samples.
Re: Why use a high-pass filter to remove DC-offset?
If you did manage to quantify the DC offset shortly after start-up, to what use could this knowledge be put? The system will be rapidly moving towards its point of minimum energy, which only it - and Michael Faraday - knows.
Re: Why use a high-pass filter to remove DC-offset?
I'm using it to "prime" the HPF so the HPF almost immediately produces the "right" answer instead of taking several seconds (or, in some cases, much longer) to settle.
(As a related point - and I know this won't be relevant for you calypso_rae because you're using your own code - but it might be worth mentioning that the HPF in the EmonLib starts from cold with uninitialised variables (hence those variables will be filled with random values which will cause the HPF to sometimes take a long time to settle). I submitted a github issue and a patch).


Leadership & Achievements
- Global Initiatives Tuition Fellowship (2018 - 20)
- IAS Summer Research Fellowship (Summer 2014)
- INSPIRE Fellowship (2012 - 17)
- Mess Representative, Student Coop Mess Management Committee 2, IISER Bhopal 2015 - 16
- Physics Batch Representative, Student Activity Council, IISER Bhopal 2014 - 15
- 2nd Place, Code Play - coding competition, Singularity 2016 (Science Festival at IISER Bhopal)


NAME & DESCRIPTION
Addobyte Technologies
PLEASE DESCRIBE WHAT YOUR BUSINESS DOES IN ONE SENTENCEsimple and neat, two color compo,
INDUSTRYTechnology
BACKGROUND INFO
VISUAL STYLE
We looks fresh design
OTHER DETAILS
nothing
IDEAS
FILE ATTACHED
Copyright 2015-2016 CONTESTHOURS.COM A part of AVATAR DESIGN STUDIOS. All Rights Reserved.


Pronouns: He/Him
My name is Xijie Lin, I go by CJ. I am a BS/MS student majoring in Computer Science at the University of Washington in Seattle, Washington. I am a responsible, easy-going and humorous person. I am fluent in both Chinese and English. I am passionate about coding and I can code in many different languages such as Java, JavaScript, C and etc. In my free time, I like playing basketball and hiking.
Pronouns: He/Him
Hi! I am a BS/MS student studying computer engineering, currently in my last quarter as an undergraduate. I enjoy learning about topics in machine learning, computer graphics, computer vision, and the intersection of these areas. Currently, I work on facial expressions research and image recognition at the Graphics and Imaging Laboratory here at the UW. Virtual and augmented reality has an immense amount of potential to transform our society -- so I’m excited to learn more about this field and to help create something amazing!
Pronouns: He/Him
I am originally from Singapore and did 2 years in the army. At the age of 21 I came to Seattle, Washington for college and haven’t looked back since. I never took a Computing class until coming to UW and am very thankful to be a junior studying Computing Engineering. I am also minoring in Entrepreneurship and hope to graduate next Spring. Outside of school, I am very passionate about technology and Sports and would love to get to meet and know all of you!
I learned how to solve the rubrik’s cube over Spring break and have been dabbling into playing chess. Sports and technology are also things I can go on endlessly about!  As a senior majoring in computer engineering at the Paul Allen School in Computer Science and Engineering, I am taking a variety of CSE courses to improve my technical skills. I am excited for this AR/VR Capstone, and I can't wait to learn how to create a cool application that can positively make an impact on society!
Outside of school and work, you can find me at a cafe indulging on boba tea, hiking one of many Pacific Northwest Trails, or on the field playing ultimate frisbee.


Before Change
if dists_key in adata.obsp:
self._distances = adata.obsp[dists_key]
elif dists_key in self._neighbors_dict:
self._distances = self._neighbors_dict[dists_key]
else:
self._neighbors_dict = adata.uns[key]
After Change
self._distances = None
if key is None or key == "neighbors":
if "neighbors" not in adata.uns:
raise KeyError("No "neighbors" in .uns")
self._neighbors_dict = adata.uns["neighbors"]
conns_key = "connectivities"
dists_key = "distances"
else:


Setting the Host Site
By default, DNN loads the first site created as the default site. Here you can modify the site that is loaded by default. The Host site is also the site associated with the Host skin object. See "Setting the Host Skin and Container"
- Navigate to Host > Host Settings.
- Select the Basic Settings tab.
- Expand the Host Details section.
- At Host Website, select the host site from the drop down list.
-
Click the Update button.


Skydiving is parachuting from an airplane for fun. Skydiving can be done individually and with groups of people. Training is required. Unlike most paratroopers, skydivers often wait until they are low, before opening the parachute. The jump can also be made from a helicopter or a balloon that is high enough in the sky. Skydiving can be an exciting sport. Skydiving includes free falling (usually from an aeroplane) through the air prior to opening a parachute. Typically skydives are carried out from around 4,000m (or 12,500ft) offering 40 to 50 seconds of freefall time.
Types of Skydiving
1. Standard Skydiving:
Often known as ‘fun jumps’, a standard skydive is a purely recreational experience done for the rush of free fall and majestic views while soaring to the ground. There are plenty of skydiving clubs around where you can meet like-minded people and share the cost of jumping.2. Tandem Skydiving:
As mentioned, this is the kind of jump you’ll do when strapped to the instructor, either as a ‘fun jump’ or as part of your training. Initially your instructor will handle all the technical aspects of jumping but as you gain more experience you will start to take on some of this responsibility until you are ready to make a solo jump.3. Formation Jumping:
This is also known as ‘relative work’ and involves a number of experienced skydivers falling to earth with the belly facing down. During freefall they attempt to build formations in the air, using movement skills and by holding on to each other’s arms and legs. Formations can number from two-ways to groups numbering in the hundreds.4. Freeflying:
TThis is a form or aerial acrobatics that involves building a series of formations in a mix of upright and head-down orientations. Jumpers fly under, over and around each other in a pre-planned patterns. Vertical formation skydiving is another variation of freeflying.5. Wingsuit Flying:
One of the newest and most exciting types of skydiving, and one that is attracting the most attention. A wingsuit is a specially designed, aerodynamic jumpsuit that uses fabric to create wings between the arms and legs of the jumper. This means they can cover large distances horizontally and even ‘fly’ very close to the ground.6. Canopy Formation:
Also known as ‘canopy relative work’, this is formation skydiving that takes pace after the chute has opened. Because of this the jumpers open their chutes the moment they leave the plane to give maximum time for canopy work.Skydiving Equipment


Montana
Cup
2004
Bike Race Series
The Series -
The Subaru Montana Cup Series is comprised of a
number of individual races to be held throughout the state of Montana. The
exact location and schedule of races can be found on the Internet at
www.montanacycling.org
Eligibility -
Racers must be members in good standing of the Montana Bicycle Racing Association (MRBA). Racers may become members of MBRA by submitting a completed registration application and an annual membership fee. Eligible racers will be issued, and must use, a permanent MBRA race number. Racers must also have a valid annual or one-day USCF license for each race in which they participate. All series races are sanctioned by USA Cycling.
Series Points
-
Racers will accrue points for all races in which they participate (see Point Schedule below). All events in the series will count toward racers' overall point totals. At the conclusion of the series, the racer in each division with the most points shall be declared the winner. In the event of ties, the racer with the greatest number of higher placings shall prevail.
Race Numbers -
MBRA members will be issued permanent numbers that are to be used at all series races (the ECC being an exception). Use of these numbers will facilitate race scoring and help ensure that points are properly awarded.
Racers will only accrue points for events in which they have worn their MBRA numbers. Racers will be allowed one (1) grace day per season where, in the event that permanent numbers are not worn (i.e. due to loss or forgetfulness), points may still be earned. No points will be awarded, retroactively, to racers for results obtained prior to the establishment of MBRA membership.
Race Divisions
-
MBRA will award and track points in the following race divisions:
Men Category 1,2
Men Category 3
Men Category 4,5
Men Masters A
Men Masters B
Men Juniors
Women Category 1,2,(3)
Women Category (3),4
Women Juniors
Race promoters will be required to submit race results according to the above format, and promoters should offer the above, discreet race divisions whenever possible. The combining of race divisions and determination of prize payouts for each race will be left to the discretion of individual event promoters, and should be based on turnout, availability of support, etc.
Racers may
participate in any race division(s) for which they are eligible, but racers
will only accrue points in the division(s) for which they have a valid MBRA
membership (i.e. have been issued a permanent race number). Racers may,
therefore, accrue points in multiple divisions, but they must purchase multiple
memberships/permanent race numbers in order to do so.
Men whose racing age
is 35 years or older may race their USCF category and/or in a Masters division.
The Masters A and B divisions are self-seeding, with the following exception:
USCF Category 1 or 2 racers 40 years and under may not race in the Masters B
division.
Points
Determination -
Points will be
awarded based on finish order within each division and, then, only among
eligible MBRA racers. In races in which divisions are combined, the final
results will list each division separately.
Example – in a race in which the Men Cat. 1,2 and Cat. 3 divisions are
combined, the overall finish order is:
1. Racer 5 (Cat. 1,2; MBRA)
2. Racer 599 (Cat. 1,2; non-MBRA)
3. Racer 8 (Cat. 1,2; MBRA)
4. Racer 303 (Cat. 3; MBRA)
5. Racer 7 (Cat. 1,2; MBRA)
6. Racer 788 (Cat. 3; non-MBRA)
7. Racer 301 (Cat. 3; MBRA)
For the purposes of awarding MBRA points, the
results are:
1. Racer 5
2. Racer 8
3. Racer 7
1. Racer 303
2. Racer 301
Points
Schedule -
For each race, points will be distributed, among MBRA members within each division, according to the following schedule:
1 50
2 40
3 30
4 25
5 20
6 18
7 16
8 15
9 14
10 13
11 12
12 11
13 10
14 9
15 8
16 7
17 6
18 5
19 4
20 3
>20 2
DNF 1
DNS/DQ 0
Scoring
Exceptions -
Points for stage
races and omniums will be awarded based on overall General Classification or
Omnium Point Total, respectively. Points will not be awarded for individual
stage results in these events.
State Championship
events will award double points.
The Ecology Center
Classic will award double points.
Scoring for
Upgrades -
Racers who upgrade during the season will take one-half of the points they've generated in the lower division to their new, upper division. These racers will then accrue points within their new division in the normal fashion.
Points
Administration -
MBRA will maintain the official points tally and will make it available to all members for periodic inspection. Racers are encouraged to check their individual point tallies regularly, though, in order to ensure accuracy of the records.
Final
Judgments -
Any questions or disputes on scoring, or requests for judgments on scenarios not addressed by these rules should be forwarded to the MBRA Executive Committee. After deliberation, the Committee will make judgments in order to resolve these issues. Such decisions shall be considered final and binding.


Complete Team GECKO's project proposal for GEMSTONE
Complete lab training and start working on ink
Compile collection of initial research on gecko skin and magnetic 3D ink
Start reproducing results and produce magnetic 3D ink
Begin designing adhesive gecko-inspired microstructures
Present at Do Good Showcase on applications of our work
Begin combining our work with magnetic 3D ink and adhesion
Complete our controllable adhesive surface prototype
Present poster at Undergraduate Research Day
Defend our final thesis and complete Project GECKO


This is the password for the root user on your Galileo. You probably will not need this until you move on to more advanced usage of your Galileo, so choose something you can remember for a long time.
Fields do not match!


Enhanced Dependencies in UD v2
The first version of the guidelines provided very little guidance regarding the enhanced representation and so far only very few treebanks contain additional dependencies. For v2, we propose the following guidelines for the enhanced representation:
- The enhanced representation should include:
- Null nodes for elided predicates
- Propagation of conjuncts
- Additional subject relations for control and raising constructions
- Arguments of passives (and other valency-changing constructions)
- Coreference in relative clause constructions
- Modifier labels that contain the preposition or other case-marking information
- The enhanced graph is not necessarily a supergraph of the basic tree, i.e., it is not required to contain all the basic dependency relations
- In principle, everything in the enhanced representation is an optional addition to the basic representation, but we specify a recommended order for adding information (as guidance to treebank developers)
Ellipsis
(See also the notes on ellipsis.)
In the enhanced representation, we add special null nodes in clauses in which a predicate is elided.
I like tea and you E5.1 coffee .
nsubj(like-2, I-1)
obj(like-2, tea-3)
nsubj(E5.1-6, you-5)
conj(like-2, E5.1-6)
obj(E5.1-6, coffee-7)
Mary wants to buy a book and Jenny E8.1 E8.2 a CD .
nsubj(wants-2, Mary-1)
xcomp(wants-2, buy-4)
obj(buy-4, book-6)
conj(wants-2, E8.1-9)
nsubj(E8.1-9, Jenny-8)
xcomp(E8.1-9, E8.2-10)
obj(E8.2-10, CD-12)
Note that this is a case in which the enhanced UD graph is not a supergraph of the basic tree as the basic tree contains orphan
relations, which are not present in the enhanced UD graph.
Controlled/raised subjects
The basic trees lack a subject dependency between a controlled verb and its controller or between an embedded verb and its raised subject. In the enhanced graph, there is an additional dependency between the embedded verb and the subject of the matrix clause.
Mary wants to buy a book .
nsubj(wants, Mary)
xcomp(wants, buy)
nsubj(buy, Mary)
She seems to be reading a book .
nsubj(seems, She)
xcomp(seems, reading)
nsubj(reading, She)
Propagation of Conjuncts
In the basic representation, the governor and dependents of a conjoined phrase are all attached to the first conjunct. The enhanced representation also contains dependencies between the other conjuncts and the governor and dependents of the phrase.
Conjoined verbs and verb phrases
When two verbs share their objects (or other complements), the subject and the object of the conjoined verbs are attached to every conjunct.
The store buys and sells cameras .
nsubj(buys, store)
nsubj(sells, store)
conj(buys, sells)
obj(buys, cameras)
obj(sells, cameras)
However, if the complements of the second verb are not shared, only the subject is attached to every conjunct.
She was reading or watching a movie .
nsubj(reading, She)
nsubj(watching, She)
conj(reading, watching)
obj(watching, movie)
Conjoined subjects and objects
When the subject is a conjoined noun phrase, each of the conjuncts is attached to the predicate.
Paul and Mary are running .
nsubj(running, Paul)
nsubj(running, Mary)
conj(Paul, Mary)
The same is true for conjoined objects.
Paul bought apples and oranges .
nsubj(bought, Paul)
obj(bought, apples)
obj(bought, oranges)
conj(apples, oranges)
This leads to slightly strange dependencies in the case of collective subjects or objects:
Paul and Mary are meeting .
nsubj(meeting, Paul)
nsubj(meeting, Mary)
conj(Paul, Mary)
Mary is eating mac and cheese .
nsubj(eating, Mary)
obj(eating, mac)
conj(mac, cheese)
obj(eating, cheese)
However, as the distinction between distributive and collective readings is often context-dependent, we propose to take the simplest approach and to always attach all conjuncts to the predicate.
When the subject is attached to a control or raising predicate, there is a dependency between the matrix verb and each conjunct and between the embedded verb and each conjunct.
Mary and John wanted to buy a hat .
nsubj(wanted, Mary)
nsubj(wanted, John)
conj(Mary, John)
xcomp(wanted, buy)
nsubj(buy, Mary)
nsubj(buy, John)
Conjoined modifiers
Each conjunct in a conjoined modifier phrase gets attached to the governor of the modifier phrase. For example, the following phrase contains a conjoined adjectival phrase that modifies a noun. In the enhanced representation, there is an additional amod
relation between the noun river and the second conjunct wide.
a long and wide river
amod(river, long)
amod(river, wide)
conj(long, wide)
Arguments of passive verbs
(See also the notes on core dependents for a detailed discussion of the new analysis of passive constructions in the basic representation.)
We propose that we no longer use a special nsubjpass
relation in the basic representation. However, the distiction between regular subjects and subjects in passive constructions is still highly useful for many NLP tasks. We therefore propose to use the relations nsubj:pass
and obl:agent
for the arguments of a passivized verb.
The book was written by the author .
nsubj:pass(written, book)
obl:agent(written, author)
She was given the book .
nsubj:pass(given, She)
obj(given, book)
Relative clauses
In basic trees, relative pronouns are attached to the main predicate of the relative clause (typically with a nsubj
or dobj
relation). In the corresponding enhanced graphs, the relative pronoun is attached to what it is referring to with the special ref
relation and the governor of the relative clause is attached as an argument to the main predicate of the relative clause. Note that such graphs contain a cycle.
Basic tree:
The boy who lived .
acl:relcl(boy, lived)
nsubj(lived, who)
Enhanced graph:
The boy who lived .
acl:relcl(boy, lived)
ref(boy, who)
nsubj(lived, boy)
Basic tree:
The book that I read .
acl:relcl(book, read)
obj(read, that)
Enhanced graph:
The book that I read .
acl:relcl(book, read)
ref(book, that)
obj(read, book)
Case Information
Adding prepositions (or case information) to the relation name of non-core dependents often makes it possible to disambiguate its semantic role. We therefore augment nmod
, obl
, acl
and advcl
relation labels with the preposition or the case of the modifier.
the house on the hill
nmod:on(house, hill)
case(hill, on)
He went to a diner after leaving work .
obl:to(went, diner)
case(diner, to)
advcl:after(went, leaving)
mark(leaving, after)
die Zerstörung der Stadt \n the destruction the.GEN city.GEN
nmod:gen(Zerstörung, Stadt)
Recommended order of annotations
We are aware that adding all of the discussed relations for the enhanced representation will require a significant amount of work. Further, many treebanks have been automatically converted from existing treebanks and many of them might contain only some of the information that is needed to add the relations for the enhanced representation. At the same time, we believe that having some of the additional relations is better than not having any additional relations at all. We therefore leave it up to the treebank maintainers how much of this proposal they want to implement.
However, maintainers should be aware that the different types of relations are not completely independent of each other and adding one type of information (e.g., null nodes) might require changes to existing additional relations. If the additional relations are added manually, we recommend the following order of annotations:
- Null nodes
- Propagation of conjuncts
- Controllers and raised subjects
- Relative clauses, passive arguments, and augmentation of relation names with case information
Additional enhancements
Some postprocessing steps such as demoting light nouns that behave like quantificational determiners (as described in this paper) can improve the usability of the dependency graphs for downstream applications. However, as most of these additions are highly language-specific, we do not provide any universal guidelines for such a representation and anything beyond the above additions is not part of the UD standard and should not be added to the officially released treebanks.


He'll want to use your yacht, and I don't want this thing smelling like fish. Steve Holt! No! I was ashamed to be SEEN with you. I like being with you. Marry me. It's called 'taking advantage.' It's what gets you ahead in life. I'm a monster. Army had half a day. I don't criticize you! And if you're worried about criticism, sometimes a diet is the best defense.
I'm afraid I just blue myself.
First place chick is hot, but has an attitude, doesn't date magicians. Really? Did nothing cancel? Well, what do you expect, mother? Michael!
Really? Did nothing cancel? Did you enjoy your meal, Mom? You drank it fast enough. Not tricks, Michael, illusions. That's what it said on 'Ask Jeeves.' Really? Did nothing cancel?
Start a blog today! Pixelwars
Now, when you do this without getting punched in the chest, you'll have more fun. Whoa, this guy's straight? It's a hug, Michael. I'm hugging you. Well, what do you expect, mother? I'm afraid I just blue myself.
Guy's a pro. Get me a vodka rocks. And a piece of toast. I don't criticize you! And if you're worried about criticism, sometimes a diet is the best defense. Did you enjoy your meal, Mom? You drank it fast enough.
It's called 'taking advantage.' It's what gets you ahead in life. I've opened a door here that I regret. Marry me. Guy's a pro.
Hi, this is a very useful article. It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout.
Thanks Phillip, glad you liked it. Nice to see you around.
Hey guys, c'mon this is old stuff!
Hi, this is cool but i know something cooler than this, new iPad!


No Worries!We don't save your card number or any information provided.We use it just to validate and lookup information into system and visualize it.After you close or refresh the page, all informations will be lost at all.


An open source short film
Click below to download either MP4, WEBM, or OBB versions of this video.
| Download | Format | Pixels | File Size |
|---|---|---|---|
| MP4 | 1080 | 47Mb | |
| MP4 | 1080 | 39Mb | |
| MP4 | 360 | 27Mb | |
| WEBM | 1080 | 71Mb | |
| OBB | 1080 | 83Mb |
Click below to download either MP3 or OBB versions of this audio track.
| Download | Format | File Size |
|---|---|---|
| MP3 | 2.8Mb | |
| OGG | 1.6Mb |
Monkaa is a blue-furred, pink-faced monkey who consumes a crystallized meteorite, making him invincibly strong and too hot to handle. Exploring his new superpowers, Monkaa zooms through an entire universe.
Monkaa is produced by Weybec, an animation studio located in Mumbai, India and founded by Pratik Solanki, Nita Ravalji and Niyal Parmar.
Project Monkaa is a 5-minute short animated movie, entirely made with Blender and GIMP and other Free/Open Software programs. It has been released as an Open Movie, with all production files and tutorials available on Blender Cloud under a CC-BY license, as well as on a DVD available in the Blender Store.


Tavish Grade is a fourth year Undergraduate Cognitive Science Student specializing in Human Computer Interaction. She is currently working as an Undergraduate Researcher at the Design Lab at UCSD.


MPI procedures sometimes assign a special meaning to a special value of a basic type argument; e.g. tag is an integer-valued argument of point-to-point communication operations, with a special wild-card value, MPI_ANY_TAG. Such arguments will have a range of regular values, which is a proper subrange of the range of values of the corresponding basic type; special values (such as MPI_ANY_TAG) will be outside the regular range. The range of regular values can be queried using environmental inquiry functions (Chapter MPI Environmental Management ).
MPI also provides predefined named constant handles, such as MPI_COMM_WORLD which is a handle to an object that represents all processes available at start-up time and allowed to communicate with any of them.
All named constants, with the exception of MPI_BOTTOM in Fortran, can be used in initialization expressions or assignments. These constants do not change values during execution. Opaque objects accessed by constant handles are defined and do not change value between MPI initialization ( MPI_INIT() call) and MPI completion ( MPI_FINALIZE() call).


Create New Ki Technique
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| Description | ||
| Level |
Maintainable?
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Add Secondary Effect
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Add Disadvantage
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Add Ki Technique
| Name | ||
|---|---|---|
| Description | ||
| Level |
Maintainable?
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Add Secondary Effect
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Add Disadvantage
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Grid
template-*
80px
80px
auto
80px
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Grid
autoflow
1
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Grid size unit
fr
1 fr
1 fr
2 fr
1 fr
1 fr
Grid
area
Header
Main
Sidebar
Footer
© 2017
Subgrid
(not yet implemented)
a
b
c
Two
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* IMMEDIATE ACTION REQUIRED - Do Not Delete *
Executive Impact & Influence Program
Dear Scott Neal,
As part of the Executive Impact and Influence Program,
each participant is asked to gather input on the
participant's own management styles and practices as
experienced by their immediate manager, each direct
report, and up to eight colleagues/peers.
You have been requested to provide feedback for a
participant attending the next program. Your input
(i.e., a Self assessment, if you are a participant in
this program, Manager assessment, Direct Report
assessment, or Colleague/Peer assessment) will be
combined with the input of others and used by the
program participant to develop an action plan to
improve his/her management styles and practices. If
you are providing feedback as a Manager of the
participant, please note that your feedback will be
identified in the summary report.
It is important that you complete this assessment NO
LATER THAN CLOSE OF BUSINESS on Tuesday, May 1, 2001.
To begin the online administration process, you will
need the following Internet address and Password(s).
NOTE: If you are providing feedback for more than one
person, each password and participant name is
individually listed below.
Open your Internet browser e.g., Internet Explorer or
Netscape Navigator, and please type or copy the URL
address below into your Internet browser (please DO NOT
go through Lotus Notes):
www.fsddatasvc.com/enron
D99UHK (Mark Breese)
If you experience technical problems, please call
Dennis Ward at FSD Data Services,<PHONE_NUMBER>. If you
have any questions about this process, you may contact
Debbie Nowak at Enron,<PHONE_NUMBER>, or Christi Smith at
Leadership Research Institute/Keilty, Goldsmith & Company,
619-216-0404.
Thank you for your participation.
***********
EDRM Enron Email Data Set has been produced in EML, PST and NSF format by ZL Technologies, Inc. This Data Set is licensed under a Creative Commons Attribution 3.0 United States License <http://creativecommons.org/licenses/by/3.0/us/> . To provide attribution, please cite to "ZL Technologies, Inc. (http://www.zlti.com)."
***********
California


Climate Changes
It is a software developed for NASA Hackathon, as part of the challenge proposed in 2019.
This solution is a mobile app that communicates users (local population) about the impacts of rising oceans in the world (and in their /own lives), showing them these changes graphically. The program is capable of realizing simulations, as well as alerting people if a disaster is on the way. All of this is only possible because data is being received in real-time from monitoring platforms (NASA Databases and others).
The platform can be used by anyone, as it is an idea with global applicability. However, it was developed with a focus on those who lives in critical areas, near coastal zones, as they are at risk.
There is an exclusive channel for the population to share information about news (locally and globally) and to be notified automatically by the system about risk events, in order to prevent and evacuate the delicate places.
The next step is investing in a development team, for the purpose of creating an Augmented Reality (AR) Platform to change the way simulations are visualized, so that it is more interactive and engages the user. The company will also develop a chat system, so people can talk to each other.
There is an exclusive channel for the population to share information about news (locally and globally) and to be notified automatically by the system about risk events, in order to prevent and evacuate the delicate places.
The next step is investing in a development team, for the purpose of creating an Augmented Reality (AR) Platform to change the way simulations are visualized, so that it is more interactive and engages the user. The company will also develop a chat system, so people can talk to each other.
You are able to realize simulations in order to predict future situations, visualizing all map changes through animations or through the camera app to see real-time effects in the space around you (if you are using AR (Augmented reality). All calculations are made from analysis and interaction between some variables, listed below:
Levi Augusto Campos Lima
Matheus de Araujo Lino
Milena Vitoria de Oliveira
Uryan Natal Suman
Vinícius Edson Silva Santos


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Halide
12.0.0
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A stack which can store one item very efficiently. More...
#include <Scope.h>
Public Member Functions | |
| SmallStack ()=default | |
| void | pop () |
| void | push (T t) |
| T | top () const |
| T & | top_ref () |
| const T & | top_ref () const |
| bool | empty () const |
| size_t | size () const |
A stack which can store one item very efficiently.
Using this instead of std::stack speeds up Scope substantially.
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default |
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inline |
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inline |
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inline |
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inline |
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inline |


Shortest Paths
Road Network Maps
Ann Arbor
42.2808° N, 83.7430° W Ann Arbor
Michigan
Written by Adrian Stoll on 23 Nov 2018


An abstract base class for processes. More...
#include <process.h>
Public Types | |
| enum | status_type { UNINITIALIZED, STOPPED, RUNNING } |
Public Member Functions | |
| Process () | |
| Default constructor. Names process "no name". | |
| Process (std::string name) | |
| Constructor that takes a name for the process. More... | |
| virtual void | init ()=0 |
| virtual void | start ()=0 |
| virtual void | update ()=0 |
| virtual void | stop ()=0 |
| string | name () |
| status_type | status () |
| high_resolution_clock::duration | period () |
| int | num_updates () |
| time_point< high_resolution_clock > | start_time () |
| high_resolution_clock::duration | last_update () |
| high_resolution_clock::duration | previous_update () |
| double | milli_time () |
| The time since the last update in millisconds, as a double. More... | |
| double | delta () |
| The most recent amount of time between updates. More... | |
| void | watch (string event_name, std::function< void(Event &)> handler) |
| void | emit (const Event &event) |
Friends | |
| class | Manager |
An abstract base class for processes.
Derived classes should imlement the init, start, update, and stop methods. For example, here is a process that prints out a message every time its update method is called.
|
inline |
| double elma::Process::delta | ( | ) |
The most recent amount of time between updates.
A common use of this method is in the update() method for Euler integration as in xnew = x + delta() * f(x)
Definition at line 37 of file process.cc.
|
pure virtual |
Initialization method. This method should be overridden by derived classes. It will usually be called once, after all processes and communication objects have been added to the manager, but before the Manager starts running.
Implemented in elma::StateMachine, and heater_example::Heater.
|
inline |
| double elma::Process::milli_time | ( | ) |
The time since the last update in millisconds, as a double.
Definition at line 26 of file process.cc.
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inline |
|
inline |
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inline |
|
inline |
|
pure virtual |
Start method. This method should be overridden by derived classes. It will be called just before the manager starts running. It may be called multiple times, if the manager is started and stopped.
Implemented in elma::StateMachine, and heater_example::Heater.
|
inline |
|
inline |
|
pure virtual |
Stop method. This method should be overridden by derived classes. It will be called just after the manager stops running. It may be called multiple times, if the manager is started and stopped.
Implemented in elma::StateMachine, and heater_example::Heater.
|
pure virtual |
Update method. This method should be overridden by derived classes. It will be called repeatedly by the manager at a frequency determined by the period used when the process is scheduled with the Manager (see Manager::schedule).
Implemented in heater_example::Heater, and elma::StateMachine.


| Cascades |
Annual precipitation totals for the North Cascades region |
| Cov |
Classical Estimates of Multivariate Location and Scatter |
| Cov-class |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| CovClassic |
Classical Estimates of Multivariate Location and Scatter |
| CovClassic-class |
Class "CovClassic" - classical estimates of multivariate location and scatter |
| CovControl-class |
Class "CovControl" is a VIRTUAL base control class |
| CovControlMcd |
Constructor function for objects of class "CovControlMcd" |
| CovControlMcd-class |
Class 'CovControlMcd' - contains control parameters for CovMcd |
| CovControlMest |
Constructor function for objects of class "CovControlMest" |
| CovControlMest-class |
Class 'CovControlMest' - contains control parameters for "CovMest" |
| CovControlMMest |
Constructor function for objects of class "CovControlMMest" |
| CovControlMMest-class |
Class 'CovControlMMest' - contains control parameters for "CovMMest" |
| CovControlMve |
Constructor function for objects of class "CovControlMve" |
| CovControlMve-class |
Class 'CovControlMve' - contains control parameters for CovMve |
| CovControlOgk |
Constructor function for objects of class "CovControlOgk" |
| CovControlOgk-class |
Class 'CovControlOgk' - contains control parameters for CovOgk |
| CovControlSde |
Constructor function for objects of class "CovControlSde" |
| CovControlSde-class |
Class 'CovControlSde' - contains control parameters for "CovSde" |
| CovControlSest |
Constructor function for objects of class "CovControlSest" |
| CovControlSest-class |
Class 'CovControlSest' - contains control parameters for "CovSest" |
| CovMcd |
Robust Location and Scatter Estimation via MCD |
| CovMcd-class |
MCD Estimates of Multivariate Location and Scatter |
| CovMest |
Constrained M-Estimates of Location and Scatter |
| covMest |
Constrained M-Estimates of Location and Scatter |
| CovMest-class |
Constrained M-estimates of Multivariate Location and Scatter |
| CovMMest |
MM Estimates of Multivariate Location and Scatter |
| CovMMest-class |
MM Estimates of Multivariate Location and Scatter |
| CovMve |
Robust Location and Scatter Estimation via MVE |
| CovMve-class |
MVE Estimates of Multivariate Location and Scatter |
| CovOgk |
Robust Location and Scatter Estimation - Ortogonalized Gnanadesikan-Kettenring (OGK) |
| CovOgk-class |
OGK Estimates of Multivariate Location and Scatter |
| CovRobust |
Robust Location and Scatter Estimation |
| CovRobust-class |
Class "CovRobust" - virtual base class for robust estimates of multivariate location and scatter |
| CovSde |
Stahel-Donoho Estimates of Multivariate Location and Scatter |
| CovSde-class |
Stahel-Donoho Estimates of Multivariate Location and Scatter |
| CovSest |
S Estimates of Multivariate Location and Scatter |
| CovSest-class |
S Estimates of Multivariate Location and Scatter |
| getCenter |
Accessor methods to the essential slots of Cov and its subclasses |
| getCenter-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| getCenter-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| getCenter-method |
Class "SummaryCov" - summary of "Cov" objects |
| getCenter-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| getCorr |
Accessor methods to the essential slots of Cov and its subclasses |
| getCorr-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| getCorr-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| getCov |
Accessor methods to the essential slots of Cov and its subclasses |
| getCov-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| getCov-method |
Class "SummaryCov" - summary of "Cov" objects |
| getCov-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| getData |
Accessor methods to the essential slots of Cov and its subclasses |
| getData-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| getData-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| getDet |
Accessor methods to the essential slots of Cov and its subclasses |
| getDet-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| getDet-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| getDistance |
Accessor methods to the essential slots of Cov and its subclasses |
| getDistance-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| getDistance-method |
Class "SummaryCov" - summary of "Cov" objects |
| getDistance-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| getEigenvalues |
Accessor methods to the essential slots of Pca and its subclasses |
| getEigenvalues,methods |
Accessor methods to the essential slots of Pca and its subclasses |
| getEigenvalues-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| getEvals |
Accessor methods to the essential slots of Cov and its subclasses |
| getEvals-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| getEvals-method |
Class "SummaryCov" - summary of "Cov" objects |
| getEvals-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| getFlag |
Accessor methods to the essential slots of Cov and its subclasses |
| getFlag-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| getFlag-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| getLoadings |
Accessor methods to the essential slots of Pca and its subclasses |
| getLoadings-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| getLoadings-methods |
Accessor methods to the essential slots of Pca and its subclasses |
| getMeth |
Accessor methods to the essential slots of Cov and its subclasses |
| getMeth-method |
Class "CovRobust" - virtual base class for robust estimates of multivariate location and scatter |
| getMeth-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| getPrcomp |
Accessor methods to the essential slots of Pca and its subclasses |
| getPrcomp,methods |
Accessor methods to the essential slots of Pca and its subclasses |
| getPrcomp-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| getQuan |
Accessor methods to the essential slots of Pca and its subclasses |
| getQuan,methods |
Accessor methods to the essential slots of Pca and its subclasses |
| getQuan-method |
Class "PcaClassic" - Principal Components Analysis |
| getQuan-method |
Class "PcaCov" - Robust PCA based on a robust covariance matrix |
| getQuan-method |
Class "PcaGrid" - Robust PCA using PP - GRID search Algorithm |
| getQuan-method |
Class "PcaHubert" - ROBust method for Principal Components Analysis |
| getQuan-method |
Class "PcaLocantore" Spherical Principal Components |
| getQuan-method |
Class "PcaProj" - Robust PCA using PP - Croux and Ruiz-Gazen (2005) algorithm |
| getRaw |
Accessor methods to the essential slots of Cov and its subclasses |
| getRaw-method |
Class "CovRobust" - virtual base class for robust estimates of multivariate location and scatter |
| getRaw-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| getScale |
Accessor methods to the essential slots of Pca and its subclasses |
| getScale,methods |
Accessor methods to the essential slots of Pca and its subclasses |
| getScale-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| getScores |
Accessor methods to the essential slots of Pca and its subclasses |
| getScores,methods |
Accessor methods to the essential slots of Pca and its subclasses |
| getScores-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| getSdev |
Accessor methods to the essential slots of Pca and its subclasses |
| getSdev,methods |
Accessor methods to the essential slots of Pca and its subclasses |
| getSdev-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| getShape |
Accessor methods to the essential slots of Cov and its subclasses |
| getShape-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| getShape-methods |
Accessor methods to the essential slots of Cov and its subclasses |
| Lda-class |
Class "Lda" - virtual base class for all classic and robust LDA classes |
| LdaClassic |
Linear Discriminant Analysis |
| LdaClassic-class |
Class "LdaClassic" - Linear Discriminant Analysis |
| LdaClassic.default |
Linear Discriminant Analysis |
| LdaClassic.formula |
Linear Discriminant Analysis |
| LdaPP |
Robust Linear Discriminant Analysis by Projection Pursuit |
| LdaPP-class |
Class "LdaPP" - Robust method for Linear Discriminant Analysis by Projection-pursuit |
| LdaPP.default |
Robust Linear Discriminant Analysis by Projection Pursuit |
| LdaPP.formula |
Robust Linear Discriminant Analysis by Projection Pursuit |
| LdaRobust-class |
Class "LdaRobust" is a virtual base class for all robust LDA classes |
| Linda |
Robust Linear Discriminant Analysis |
| Linda-class |
Class "Linda" - Robust method for LINear Discriminant Analysis |
| Linda.default |
Robust Linear Discriminant Analysis |
| Linda.formula |
Robust Linear Discriminant Analysis |
| lmom32 |
Hosking and Wallis Data Set, Table 3.2 |
| lmom33 |
Hosking and Wallis Data Set, Table 3.3 |
| Pca-class |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| pca.distances |
Compute score and orthogonal distances for Principal Components (objects of class 'Pca') |
| pca.scoreplot |
Score plot for Principal Components (objects of class 'Pca') |
| PcaClassic |
Principal Components Analysis |
| PcaClassic-class |
Class "PcaClassic" - Principal Components Analysis |
| PcaClassic.default |
Principal Components Analysis |
| PcaClassic.formula |
Principal Components Analysis |
| PcaCov |
Robust PCA based on a robust covariance matrix |
| PcaCov-class |
Class "PcaCov" - Robust PCA based on a robust covariance matrix |
| PcaCov.default |
Robust PCA based on a robust covariance matrix |
| PcaCov.formula |
Robust PCA based on a robust covariance matrix |
| PcaGrid |
Robust Principal Components based on Projection Pursuit (PP): GRID search Algorithm |
| PcaGrid-class |
Class "PcaGrid" - Robust PCA using PP - GRID search Algorithm |
| PcaGrid.default |
Robust Principal Components based on Projection Pursuit (PP): GRID search Algorithm |
| PcaGrid.formula |
Robust Principal Components based on Projection Pursuit (PP): GRID search Algorithm |
| PcaHubert |
ROBPCA - ROBust method for Principal Components Analysis |
| PcaHubert-class |
Class "PcaHubert" - ROBust method for Principal Components Analysis |
| PcaHubert.default |
ROBPCA - ROBust method for Principal Components Analysis |
| PcaHubert.formula |
ROBPCA - ROBust method for Principal Components Analysis |
| PcaLocantore |
Spherical Principal Components |
| PcaLocantore-class |
Class "PcaLocantore" Spherical Principal Components |
| PcaLocantore.default |
Spherical Principal Components |
| PcaLocantore.formula |
Spherical Principal Components |
| PcaProj |
Robust Principal Components based on Projection Pursuit (PP): Croux and Ruiz-Gazen (2005) algorithm |
| PcaProj-class |
Class "PcaProj" - Robust PCA using PP - Croux and Ruiz-Gazen (2005) algorithm |
| PcaProj.default |
Robust Principal Components based on Projection Pursuit (PP): Croux and Ruiz-Gazen (2005) algorithm |
| PcaProj.formula |
Robust Principal Components based on Projection Pursuit (PP): Croux and Ruiz-Gazen (2005) algorithm |
| PcaRobust-class |
Class "PcaRobust" is a virtual base class for all robust PCA classes |
| plot |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| plot-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| plot-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| plot-method |
Methods for Function 'plot' in Package 'rrcov' |
| plot-methods |
Methods for Function 'plot' in Package 'rrcov' |
| pottery |
Archaic Greek Pottery data |
| pottery.test |
Archaic Greek Pottery data |
| predict |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| predict-method |
Class "Lda" - virtual base class for all classic and robust LDA classes |
| predict-method |
Class "LdaPP" - Robust method for Linear Discriminant Analysis by Projection-pursuit |
| predict-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| predict-method |
Class "Qda" - virtual base class for all classic and robust QDA classes |
| PredictLda-class |
Class "PredictLda" - prediction of "Lda" objects |
| PredictQda-class |
Class "PredictQda" - prediction of "Qda" objects |
| salmon |
Salmon data |
| scorePlot |
Score plot for Principal Components (objects of class 'Pca') |
| scorePlot-method |
Score plot for Principal Components (objects of class 'Pca') |
| scorePlot-methods |
Score plot for Principal Components (objects of class 'Pca') |
| screeplot |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| screeplot-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| show-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| show-method |
Class "CovRobust" - virtual base class for robust estimates of multivariate location and scatter |
| show-method |
Class "Lda" - virtual base class for all classic and robust LDA classes |
| show-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| show-method |
Class "PredictLda" - prediction of "Lda" objects |
| show-method |
Class "PredictQda" - prediction of "Qda" objects |
| show-method |
Class "Qda" - virtual base class for all classic and robust QDA classes |
| show-method |
Class "SummaryCov" - summary of "Cov" objects |
| show-method |
Class "SummaryCovRobust" - summary of "CovRobust" objects |
| show-method |
Class "SummaryLda" - summary of "Lda" objects |
| show-method |
Class "SummaryPca" - summary of "Pca" objects |
| show-method |
Class "SummaryQda" - summary of "Qda" objects |
| summary-method |
Class "Cov" - a base class for estimates of multivariate location and scatter |
| summary-method |
Class "CovRobust" - virtual base class for robust estimates of multivariate location and scatter |
| summary-method |
Class "Lda" - virtual base class for all classic and robust LDA classes |
| summary-method |
Class "Pca" - virtual base class for all classic and robust PCA classes |
| summary-method |
Class "Qda" - virtual base class for all classic and robust QDA classes |
| SummaryCov-class |
Class "SummaryCov" - summary of "Cov" objects |
| SummaryCovRobust-class |
Class "SummaryCovRobust" - summary of "CovRobust" objects |
| SummaryLda-class |
Class "SummaryLda" - summary of "Lda" objects |
| SummaryPca-class |
Class "SummaryPca" - summary of "Pca" objects |
| SummaryQda-class |
Class "SummaryQda" - summary of "Qda" objects |


Lata Mangeshkar still in hospital, is doing 'very good', says family
Mangeshkar, 90, was admitted to the Intensive Care Unit of Breach Candy Hospital after she complained of difficulty in breathing on November 11. She was put on a ventilator
by Press Trust of IndiaBollywood great Lata Mangeshkar, who was admitted to hospital two weeks ago, is "doing very good", her niece said on Monday but did not clarify when she will return home.
Mangeshkar, 90, was admitted to the Intensive Care Unit of Breach Candy Hospital after she complained of difficulty in breathing on November 11. She was put on a ventilator.
It was not clear whether Mangeshkar was still in the ICU and still hooked on to a ventilator.
Hospital sources were unavailable for comment despite several attempts to contact them.
"She is doing very good. We are happy," Mangeshkar's niece Rachana Shah told PTI.
Asked when Mangeshkar would be discharged from hospital, Shah said, "Discharge time frame is presently not important. What's important is how well she is recovering."
In her over seven-decade career, Mangeshkar has sung more than 30,000 songs across languages.
She is considered one of the greatest playback singers in Indian cinema. She received the Bharat Ratna, India's highest civilian honour, in 2001.


public class ActionSpace
extends java.lang.Object
regionID
: Region id in which is present this ActionSpace.
actionSpaceID
: ActionSpace specific id in its Region.
single
: boolean attribute if it is a single ActionSpace in which it can be placed only one FamilyMember
actionValue
: a number of the actionValue needed to place a FamilyMember on it.
bonus
: a ResourceSet of bonus resources that a Player obtains when he places a FamilyMember on this ActionSpace.
blocked
: a flag representing if tha action space is blocked or notActionSpace's regionID and actionSpaceID are final and all the ActionSpace of the game are identified with its unique combination of regionID and actionSpaceID.
FamilyMember, Player, Region, ResourceSet.
| Modifier and Type | Field and Description |
|---|---|
private int |
actionSpaceID |
private int |
actionValue |
private boolean |
blocked |
private ResourceSet |
bonus |
private java.util.ArrayList<FamilyMember> |
occupants |
private int |
regionID |
private boolean |
single |
| Constructor and Description |
|---|
ActionSpace(ResourceSet bonus,
int actionValue,
boolean single,
int regionID,
int actionSpaceID)
builds an ActionSpace object with the specific parameters passed.
|
| Modifier and Type | Method and Description |
|---|---|
void |
addFamilyMember(FamilyMember familyMember)
Returns a boolean to check if It can be placed a FamilyMember on this ActionSpace.
|
void |
flushActionSpace()
free this actionSpace, removing all the family members on it
|
int |
getActionSpaceID()
returns this ActionSpace.
|
int |
getActionValue()
returns this ActionSpace.
|
ResourceSet |
getBonus()
returns this ActionSpace.
|
java.util.ArrayList<FamilyMember> |
getOccupants()
get the occupants of the action space, as a List of the FamilyMember which are positionated on tt
|
java.util.ArrayList<Player> |
getPlayers()
returns an ArrayList of Players which have a FamilyMember on this ActionSpace
This method is necessary for the ActioSpaces which has ActionSpace.
|
int |
getRegionID()
returns this ActionSpace.
|
boolean |
isBlocked()
allows to retrive the value of the blocked flag
|
boolean |
isBusy()
Returns a boolean to specify if on this ActionSpace it can't be placed a FamilyMember.
|
boolean |
isSingleActionSpace()
returns this ActionSpace.
|
void |
removeFamilyMember(FamilyMember familyMember)
Removes from
occupants an FamilyMember which is not more an occupant. |
void |
setBlock(boolean blockValue)
specify if the action value is blocked or not.
|
void |
setBonus(ResourceSet bonus) |
java.lang.String |
toString()
returns a String which can easily printed on the screen.
|
private ResourceSet bonus
private int actionValue
private java.util.ArrayList<FamilyMember> occupants
private boolean single
private final int regionID
private final int actionSpaceID
private boolean blocked
public ActionSpace(ResourceSet bonus, int actionValue, boolean single, int regionID, int actionSpaceID)
An actionSpace that has to be used in the Game, must have actionSpaceID and regionID not null.
bonus
- ResourceSet of the bonus of this ActionSpaceactionValue
- integer that a FamilyMember needs as actionValue to be placed on this ActionSpacesingle
- boolean attribute that specifies if in this ActionSpace it can be placed only one FamilyMemberregionID
- integer that represents the RegionID in which is present this ActionSpaceactionSpaceID
- integer that represents the ActionSpaceID of this ActionSpace in its RegionRegion, ActionSpace, FamilyMember, ResourceSet
public boolean isSingleActionSpace()
single
attribute.
This method is helpful to check if on this ActionSpace it can be place only one FamilyMember If returns true, this is a single ActionSpace and only one FamilyMember is permitted. If returns false, this is a multiple ActionSpace and there is no limit of FamilyMember that can occupy this ActionSpace
single
.Region, ActionSpace, FamilyMember.
public ResourceSet getBonus()
bonus
attribute.
This method returns a ResourceSet of an instant bonus of the ActionSpace. This bonus is used to build an Effect to give this resources to the Player which owns the FamilyMember present on this ActionSpace.
bonus
.ActionSpace, FamilyMember, ResourceSet, Player, Effect.
public void setBonus(ResourceSet bonus)
public int getRegionID()
regionID
attribute.
This method returns an integer which represents the number of the RegionId of this ActionSpace. All the ActionSpace of the game are identified with its unique combination of regionID and actionSpaceID.
regionID
.ActionSpace, Region.
public int getActionSpaceID()
actionSpaceID
attribute.
This method returns an integer which represents the index of this ActionSpace in the ArrayList of ActionSpace of a Region. All the ActionSpace of the game are identified with its unique combination of regionID and actionSpaceID.
actionSpaceID
.ActionSpace, Region.
public int getActionValue()
actionValue
attribute.
This method returns an integer which represents the integer that a FamilyMember needs as actionValue to be placed on this ActionSpace To have a working Game this actionValue can't be null.
actionValue
.ActionSpace, FamilyMember.
public java.util.ArrayList<Player> getPlayers()
This method is necessary for the ActioSpaces which has ActionSpace.single
== false to get a Player instance.
ActionSpace, FamilyMember, Player.
public void addFamilyMember(FamilyMember familyMember)
This method modifies the ArrayList occupants
} of this ActionSpace.
returns false if isBusy()
== true.
familyMember
- A FamilyMember that is trying to occupy this ActionSpace.ActionSpace, FamilyMember, Player.
public void removeFamilyMember(FamilyMember familyMember)
occupants
an FamilyMember which is not more an occupant.
This method modifies the ArrayList occupants
} of this ActionSpace.
familyMember
- A FamilyMember that is not more an occupant of this ActionSpace.ActionSpace, FamilyMember.
public boolean isBusy()
This method returns false if isSingleActionSpace()
== true and occupants
.isEmpty() == true.
ActionSpace.
public java.lang.String toString()
The String is builded with this pattern:
toString
in class java.lang.Object
ActionSpace.
public java.util.ArrayList<FamilyMember> getOccupants()
public void flushActionSpace()
public void setBlock(boolean blockValue)
blockValue
- the value of the blocked flagpublic boolean isBlocked()


Diavgeia Redefined uses Jena Apache as its RDF Store, as well as it offers a User Interface that citizens can issue to pose SPARQL queries through Fuseki Sparql Server.
For installation instructions, see this Github link.


public interface OutputConfigFlags
| Modifier and Type | Field and Description |
|---|---|
static int |
CFG_ADD_SPACE_AFTER_EMPTY_ELEM
Flag that indicates
whether writer is to add a single white space before closing
"/>"
of the empty element or not. |
static int |
CFG_AUTO_CLOSE_OUTPUT
Property that enables/disables stream write to close the underlying
output target, either when it is asked to (.close() is called), or
when it doesn't need it any more (reaching EOF, hitting an
unrecoverable exception).
|
static int |
CFG_AUTOMATIC_EMPTY_ELEMENTS |
static int |
CFG_AUTOMATIC_END_ELEMENTS
Flag that indicates we can output 'automatic' empty elements;
end elements needed to close the logical output tree when
stream writer is closed (by closing it explicitly, or by writing
end-document event)
|
static int |
CFG_AUTOMATIC_NS |
static int |
CFG_COPY_DEFAULT_ATTRS
Flag that indicates whether attributes expanded from default attribute
values should be copied to output, when using copy methods.
|
static int |
CFG_ENABLE_NS
Flag that indicates whether writer is namespace-aware or not; if not,
only local part is ever used.
|
static int |
CFG_ESCAPE_CR
Flag that indicates whether CR (\r, ascii 13) characters occuring
in text (CHARACTERS) and attribute values should be escaped using
character entities or not.
|
static int |
CFG_FIX_CONTENT
Flag that will enable writer that checks for validity of content
to try to fix the problem, by splitting output segments as
necessary.
|
static int |
CFG_OUTPUT_CDATA_AS_TEXT
Whether writer should just automatically convert all calls that
would normally produce CDATA to produce (quoted) text.
|
static int |
CFG_USE_DOUBLE_QUOTES_IN_XML_DECL
Property that indicates if singe quotes or double quotes should be
used in the XML declaration.
|
static int |
CFG_VALIDATE_ATTR
Flag that indicates we should check uniqueness of attribute names,
to prevent accidental output of duplicate attributes.
|
static int |
CFG_VALIDATE_CONTENT
Flag that indicates we should check validity of textual content of
nodes that have constraints.
|
static int |
CFG_VALIDATE_NAMES
Flag that indicates we should check validity of names (element and
attribute names and prefixes; processing instruction names), that they
contain only legal identifier characters.
|
static int |
CFG_VALIDATE_STRUCTURE |
static final int CFG_ENABLE_NS
static final int CFG_AUTOMATIC_NS
static final int CFG_AUTOMATIC_EMPTY_ELEMENTS
static final int CFG_OUTPUT_CDATA_AS_TEXT
static final int CFG_COPY_DEFAULT_ATTRS
static final int CFG_ESCAPE_CR
static final int CFG_ADD_SPACE_AFTER_EMPTY_ELEM
"/>"
of the empty element or not. It is sometimes useful to add to
increase compatibility with HTML browsers, or to increase
readability.static final int CFG_AUTOMATIC_END_ELEMENTS
static final int CFG_VALIDATE_STRUCTURE
static final int CFG_VALIDATE_CONTENT
Specifically: comments can not have '--', CDATA sections can not
have ']]>'
and processing instruction can not have '?>
;' character
combinations in content passed in.
static final int CFG_VALIDATE_NAMES
static final int CFG_VALIDATE_ATTR
static final int CFG_FIX_CONTENT
static final int CFG_AUTO_CLOSE_OUTPUT
static final int CFG_USE_DOUBLE_QUOTES_IN_XML_DECL
Copyright © 2022 FasterXML. All rights reserved.


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Save
Import from a JSON file
Export as JSON file


Bachelor of Business Administration or BBA is one of the most popular bachelor degree programmes after class XII. The BBA course is the gateway to numerous job opportunities in a plethora of sectors like Marketing, Education, Finance, Sales, and Government to name just a few. Here are some important highlights of the BBA program/degree that you should know about: The 3-year professional undergraduate course in Business Management is open to students from all the three streams: Science, Arts and Commerce. The BBA course offers knowledge and training in management and leadership skills to prepare them for managerial roles and entrepreneurship. During the tenure of the course, candidates learn various aspects of business administration and management through class room lectures and practical projects like internship. BBA can be pursued in full-time as well as correspondence mode. There are various BBA specializations one can choose from such as Human Resource Management ,Finance ,Sales & Marketing Information Technology
The average starting salary of a BBA graduate is on an average Rs 3 lakh and upwards.
BBA Eligibility Criteria and Entrance Exams
Aspirants who have completed their Class XII (10+2 level) in any stream from a recognised educational board or university can pursue BBA The candidates must have attained an aggregate score of 50% and above in Class XII In case a candidate has appeared for Class XII exam and is waiting for the result, s/he can also apply to the course.
Top Entrance Exams for BBA
Generally, admission to BBA is granted on the basis of an entrance test conducted by the institute/college offering the course. Also, few institutes conduct Group Discussion and Personal Interview rounds followed by the entrance test. Final admission is granted to candidates on the basis of the scores obtained in Qualifying Examination, Entrance Test, and GD-PI. Some of the popular BBA entrance examinations are listed below: NPAT , UGAT , IPMAT , AUMAT , FEAT , BHU UET
BBA Specializations
Some of the most popular BBA specializations are listed below: BBA Finance , BBA in Banking and Insurance , BBA Information Technology , BBA Human Resource , BBA Marketing , BBA Communication and Media Management , BBA Foreign Trade , BBA Hospitality and Hotel Management , BBA Hospital and Healthcare Management
BBA Syllabus and Subjects
BBA syllabus is devided into six semesters. The BBA syllabus broadly consists of subjects like Business Organisation, Business Communication, Fundamentals of Accounting, Business Mathematics, Management Concepts & Practices, Organisational Behavior, Managerial Economics, Management Accounting, Business Environment, Business Statics, Marketing Management, etc.
Given below is the list of few subjects and topics under BBA Syllabus: Principles of Management , Business Mathematics & Statics , Introduction to Operations Research , Business Economics , Financial & Management Accounting , Production & Material Management , Personnel Management & Industry Relations , Marketing Management , Business Data Processing , Business Laws , Introduction to Psychology , Business Analytics , Introduction to Sociology , Micro Economics , Organisational Behaviour , Essentials of Marketing , Corporate Strategic Management , Human Resource Management , MIS / Systems Design , Understanding Industry and Markets , Leadership and Ethics , Strategy , Entrepreneurship , International Business Management , Sales & Distribution Management , Commercial Bank Management , Security Analysis , Manufacture Planning and Control , Digital Marketing , Retail Management , E-Commerce , Quantitative Methods , Computer Applications , Family Business Management , Export/ Import Management , PR Management , Project Management , Financial & Commodity Derivatives , Financial Modelling using spreadsheets , Industrial Relations and Labour Legislation , Consumer Behaviour
Apart from these, the BBA syllabus also includes practical skills including the following: Soft Skills & Personality Development , Professional Communication & Behavioral Grooming , Writing Skills , Etiquette , Conversational Skills , Consulting & Problem solving skills , Selling , Negotiating , Persuading skills
BBA Jobs & Top Recruiters
On completion of BBA, aspirants generally opt for MBA. However, candidates can also choose to explore job opportunities in various fields like banking, urban infrastructure & real estate management, business consultancies, advertising, manufacturing and in Government sectors to name a few. Some major job profiles one can opt for after completion of BBA are as follows: Human Resource Executive: The responsibility of a Human Resource Executive (HR Executive) includes ensuring that the strategies, methodology and HR programs are administered and the objectives of the organisation are in consistence with proficient benchmarks, state and government administrative prerequisites and laws. Also, planning, advising on HR strategies and overseeing human asset activities like enrollment and pay is the key responsibility of an HR Manager. The average salary of Human Resource Manager is Rs 4 lakh and upwards Marketing Executive: A Marketing Executive develops official statements and is responsible for promotion for the organisation’s products, conducting and analysing a competitive research, and establishing objectives, expectations and results for marketing programmes. The average salary of Marketing Executive is Rs 3 lakh and upwards Marketing Manager: A Marketing Manager collaborates with product managers and aims at executing new/ modified programs for the establishment of improved strategies. Developing market research studies & analyze their finding, making the best use of marketing programs & campaigns for the organisation’s products and services are the responsibilities of a Marketing Manager. The average salary of a Marketing Manager is Rs 4.5 lakh and upwards Sales Executive: The Sales Executive is required to design and implement strategies to increase company sales revenue and expand the company’s base in the market. The average salary of a Sales Executive is Rs 3 lakh and upwards. Research and Development (R&D) Executive: A R&D Manager directs and manages the development & research programmes of an organisation in order to meet the needs of the organisation. Measuring the scope of research projects & making sure that they are delivered on time within the stipulated budget is the role of an R&D Manager. The average salary of a Sales Executive is Rs 2 lakh and upwards.
BBA Top Recruiters
Some of the top companies offering jobs to BBA graduates are: Tata Consultancy Services (TCS) , Hindustan Unilever , International Business Machines (IBM) Corp , Ernst & Young (EY) , Hewlett-Packard , ICICI Bank , Microsoft , Mc Kinsey and Company , Deloitte , Sony


Piggie on the railway,
Picking up ,
stones
Down came the engine,
And broke Piggie’s ,
bones
Ah! said the Piggie,
“That’s not .”
fair
“Oh!” said the engine driver,
“I don’t .”
care


Contents
classdef std_processor < handle
Properties
properties
MainObj
Name = 'processor1';
ChanNames = {};
CurrentSample = 1;
WindowSize = 2048;
FftData = [];
Tag = 'std_processor';
Win = sqrt(hanning(2*2048));
end
methods
function obj = std_processor(mainObj, chanNames)
if nargin == 0
obj.MainObj.DataBuffer = bf_data;
help std_processor
elseif nargin >= 1
obj.MainObj = mainObj;
end
if nargin >= 2
obj.ChanNames = chanNames;
end
end
function value = update(obj)
value = 0;
while obj.CurrentSample + obj.WindowSize*2 <= min(obj.MainObj.DataBuffer.CurrentSample(obj.MainObj.DataBuffer.names2inds(obj.ChanNames)))
value = value + 1;
dataIn = obj.MainObj.DataBuffer.getAudioData(obj.ChanNames,obj.CurrentSample,obj.CurrentSample+obj.WindowSize*2-1);
dataOut = obj.process(dataIn);
obj.CurrentSample = obj.CurrentSample + obj.WindowSize;
obj.MainObj.DataBuffer.addSamples(dataOut,obj.Name,1);
end
end
function dataOut = process(obj, dataIn)
if size(obj.Win,2) ~= size(obj.ChanNames,1)
obj.Win = repmat(sqrt(hanning(2*obj.WindowSize)),1,size(obj.ChanNames,1));
end
dataOut = fft(dataIn.*obj.Win);
end
end
BF_DATA Beamformer Audio Buffer. Has many functions to label the
channels and add data from different sources. The time indices of the
data in the buffer can be kept in sync using different methods.
BF_DATA(OBJ) create empty file object
BF_DATA(OBJ, MAINOBJ) create file object and add handle to main object
BF_DATA(OBJ, MAINOBJ, SOURCEID) create empty file object and set SourceID
BF_DATA(OBJ, MAINOBJ, SOURCEID, FILENAME) add file named fileName to object
BF_DATA(OBJ, MAINOBJ, SOURCEID, FILENAME, LOCATIONS) add file with locations
BF_DATA(OBJ, MAINOBJ, SOURCEID, FILENAME, LOCATIONS, CHANNAMES) add file with
locations and channel names
Example 1:
obj = bf_data
obj.setChanNames({'S1','S2','S3','S4'})
obj.setTotalSamples(100)
obj.addSamples([1;2;3;4;[5:100]'],'S3')
obj.getAudioData({'S3','S1'})
Example 2:
obj = bf_data
obj.setChanNames({'S1','S2','S3','S4'})
obj.addSamples([1;2;3;4;[5:100]'],'S1',1,25)
Example 3:
obj = bf_data
obj.setChanNames({'S1','S2','S3','S4'})
obj.setDelays(5,{'S2'})
obj.addSamples([1;2;3;4;[5:100]'],'S3',1)
BF_DATA Methods:
load - Load data from audio or matlab file.
save - Save data to audio or matlab file.
play - Play the data using an audio device.
setNChan - Set number of channels.
setTotalSamples - Set total number of samples.
setLocations - Set Channel Locations.
setChanNames - Set Channel Names.
setDelays - Set Delay Times.
addSamples - Add samples to the data.
getAudioData - Get samples out of buffer (time axes of channels agree).
resampleData - Resample data using matlab resample function
delayData - Delay data so when data is loaded the time axes agree.
names2inds - Get index of channel(s) in audiodata matrix
BF_DATA Properties:
FileName - Name of the audio file to save including extention
FilePath - Path of the audio file to save
SourceID - Identifier for source device or file in use.
Fs - Sampling Frequency in Hz
BitsPerSample - Number of Bits per audio Sample
NChan - Number of audio channels in File
Comment - Comment of audio file
Locations - Channel locations [x y z az el up]
ChanNames - Channel names
DelaySamples - Delays in samples for each channel
CurrentSample - Current sample for each channel. Used when adding
samples to the channel.
TotalSamples - Total length of the audio data in samples
IsInitialized - Has the source been correctly initialized
AudioData - Audio Data matrix size = [TotalSamples NChan]
Tag - Tag to find object
Written for the BSc graduation project Acoustic Enhancement via
Beamforming Using Smartphones.
Team: S. Bosma R. Brinkman
T. de Rooij R. Smeding
N. van Wijngaarden E. Wouters
Supervisor: Jorge Martínez Castañeda
Contact<EMAIL_ADDRESS>See also BF_DATA/LOAD, BF_DATA/SAVE, BF_DATA/PLAY, BF_DATA/ADDSAMPLES,
BF_DATA/SETNCHAN, BF_DATA/SETTOTALSAMPLES, BF_DATA/SETLOCATIONS,
BF_DATA/SETCHANNAMES, BF_DATA/SETDELAYS, BF_DATA/ADDSAMPLES,
BF_DATA/GETAUDIODATA, BF_DATA/RESAMPLEDATA, BF_DATA/DELAYDATA,
BF_DATA/NAMES2INDS, MITM, SITM, AUDIOREAD, AUDIOWRITE, SAVE, LOAD
Published output in the Help browser
showdemo bf_data
STD_PROCESSOR Standard processing object. This file is a template to
make a processing object like a beamformer or an intelligibility measure
BF_DATA() create processing object
BF_DATA(MAINOBJ) create processing object with handle to main object
BF_DATA(MAINOBJ, CHANNAMES) add names of channels to process
STD_PROCESSOR Methods:
update - Function to get a data window and call process function if
there is data available to process
process - Function where processing is done
STD_PROCESSOR Properties:
MainObj - Handle of main object
Name - Name of Processor
ChanNames - Channel names
CurrentSample - Current sample
WindowSize - Size of window to process, twice this length is
taken and multiplied by the window
FftData - Fft Data matrix
Tag - Tag to find object
Win - Window to use on audio signal standard the sqrt(hanning(2*WindowSize)) is used
Written for the BSc graduation project Acoustic Enhancement via
Beamforming Using Smartphones.
Team: S. Bosma R. Brinkman
T. de Rooij R. Smeding
N. van Wijngaarden E. Wouters
Supervisor: Jorge Martínez Castañeda
Contact<EMAIL_ADDRESS>See also BF_DATA, MAIN_WINDOW
ans =
std_processor with properties:
MainObj: [1x1 struct]
Name: 'processor1'
ChanNames: {}
CurrentSample: 1
WindowSize: 2048
FftData: []
Tag: 'std_processor'
Win: [4096x1 double]
end


Compression can be done in a single step if the buffers are large enough (for example if an input file is mmap’ed), or can be done by repeated calls of the compression function. In the latter case, the application must provide more input and/or consume the output (providing more output space) before each call.
The library also supports reading and writing files in gzip(1) (.gz) format with an interface similar to that of stdio.
The library does not install any signal handler. The decoder checks the consistency of the compressed data, so the library should never crash even in case of corrupted input.
All functions of the compression library are documented in the file zlib.h. The distribution source includes examples of use of the library in the files example.c and minigzip.c.
Changes to this version are documented in the file ChangeLog that accompanies the source, and are concerned primarily with bug fixes and portability enhancements.
A Java implementation of zlib is available in the Java Development Kit 1.1:
A Perl interface to zlib, written by Paul Marquess (pmqs@cpan.org), is available at CPAN (Comprehensive Perl Archive Network) sites, including:
A Python interface to zlib, written by A.M. Kuchling (amk@magnet.com), is available in Python 1.5 and later versions:
A zlib binding for tcl(1) , written by Andreas Kupries (a.kupries@westend.com), is availlable at:
An experimental package to read and write files in .zip format, written on top of zlib by Gilles Vollant (info@winimage.com), is available at:
The data format used by the zlib library is described by RFC (Request for Comments) 1950 to 1952 in the files:
These documents are also available in other formats from:
Mark Nelson<EMAIL_ADDRESS>wrote an article about zlib for the Jan. 1997 issue of Dr. Dobb’s Journal; a copy of the article is available at:
before asking for help. Send questions and/or comments to<EMAIL_ADDRESS>or (for the Windows DLL version) to Gilles Vollant (info@winimage.com).
This software is provided "as-is," without any express or implied warranty. In no event will the authors be held liable for any damages arising from the use of this software. See the distribution directory with respect to requirements governing redistribution. The deflate format used by zlib was defined by Phil Katz. The deflate and zlib specifications were written by L. Peter Deutsch. Thanks to all the people who reported problems and suggested various improvements in zlib; who are too numerous to cite here.
UNIX manual page by R. P. C. Rodgers, U.S. National Library of Medicine (rodgers@nlm.nih.gov).


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“Algorithms are not arbiters of objective truth and fairness simply because they're math.”  It is our goal to provide access to well written, well-explained programs and knowledge that improve people's lives. We want to enable people to adapt and change code according to their own ideas through an Open Access approach. We bring amazing people together to code algorithms and share our work for the benefit of all.


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Changelog
----
5.3.3
- Support for 2020.2 EAP
- Add Accent Color for Searchable Settings
- Reduced opacity in project frame colors
5.3.2
- Add a button to stop showing the Atom Material Icons plugin notification
- Improve colors schemes: Add better coloring to inline Java documentation renderer
- Fix default highlighted reference color
- Colorize local history labels
- Colorize scopes and bookmarks colors
- Replace global colors with colors from the themes (experimental)
- Fix theme selection from the wizard not being persisted
5.3.1
- Fix NPE when opening file colors with a Native Theme
5.3.0
- New Language Addition: Kotlin!
- Keywords: private, public, protected, internal
- Keywords: sealed, open, override
- Keywords: object, companion
- Keywords: import, package
- Keywords: data
- Keywords: operator, infix
- Keywords: this, super
- Primitives: null, Unit
- Primitives: true, false
- New settings for PHP Additions:
- echo, true, false, null, exit, die
- New settings for TypeScript additions:
- declare, type, alias, true, false
- New settings for JavaScript additions:
- New settings for Java additions:
- Improved Language Additions Color Pages: now properties are grouped in the settings page
- Syntax highlightings improvements for Kotlin
- Fix Parameter Info Background color for Kotlin
- Fix File Colors not applied in Inactive tabs
- Add opacity during Live Templates completion
5.2.0
- New Feature: Project Frame Color: Add a colored stripe on top of each project for easier
visualization. Inspired by Unique Window Colors
for VSCode.
- Fix Loading and Saving Custom Themes
- New: The active tab color is now taken from the color scheme if the "Active
Tab Color" is not enabled.
- Add new actions to toggle Material Wallpapers and Project Frame Colors
- Add new action to download the Atom Material Icons Plugin.
- Fix Material Oceanic scrollbars color.
- The Material Status Bar indicator is now togglable just like other Status Bar indicators.
- Other fixes and improvements
5.1.3
5.1.0
- Refactor file status colors to not modify Darcula, therefore cleaning up after uninstall
- Make the floating toolbars rounder and using the theme colors
- Fix Theme not being persisted after restart
- Add more visibility to the Atom Material Icons plugin
- Add support for Rainbow Brackets, GitToolbox and Markdown Viewer in color schemes
- Other fixes and improvements
5.0.0
- Built-in support for native themes! Supports Light, Darcula, High Contrast and user-defined
themes!
- Please note that this is a feature in its first steps, so please report any bugs you can find!
- New feature: Material Wallpapers! Now themes come with their own empty frame wallpaper!
- Deprecation of the following features:
- Material Design Components -- This is replaced by native themes support
- Material Theme -- This is replaced by native themes support
- Material Icons (UI, File and PSI Icons) -- This has been moved to the Atom Material Icons Plugin
- Arrow Styles -- This has been moved to the Atom Material Icons Plugin
For more changelog entries, check https://material-theme.com/docs/changelog/