Data structures for maps between finite sets#
This module implements several fast Cython data structures for maps
between two finite set. Those classes are not intended to be used
directly. Instead, such a map should be constructed via its parent,
using the class FiniteSetMaps
.
EXAMPLES:
To create a map between two sets, one first creates the set of such maps:
sage: M = FiniteSetMaps(["a", "b"], [3, 4, 5])
The map can then be constructed either from a function:
sage: f1 = M(lambda c: ord(c)-94); f1
map: a -> 3, b -> 4
or from a dictionary:
sage: f2 = M.from_dict({'a':3, 'b':4}); f2
map: a -> 3, b -> 4
The two created maps are equal:
sage: f1 == f2
True
Internally, maps are represented as the list of the ranks of the
images f(x)
in the co-domain, in the order of the domain:
sage: list(f2)
[0, 1]
A third fast way to create a map it to use such a list. it should be kept for internal use:
sage: f3 = M._from_list_([0, 1]); f3
map: a -> 3, b -> 4
sage: f1 == f3
True
AUTHORS:
Florent Hivert
- class sage.sets.finite_set_map_cy.FiniteSetEndoMap_N#
Bases:
FiniteSetMap_MN
Maps from
range(n)
to itself.See also
FiniteSetMap_MN
for assumptions on the parent
- class sage.sets.finite_set_map_cy.FiniteSetEndoMap_Set#
Bases:
FiniteSetMap_Set
Maps from a set to itself
See also
FiniteSetMap_Set
for assumptions on the parent
- class sage.sets.finite_set_map_cy.FiniteSetMap_MN#
Bases:
ClonableIntArray
Data structure for maps from
range(m)
torange(n)
.We assume that the parent given as argument is such that:
m
is stored inself.parent()._m
n
is stored inself.parent()._n
the domain is in
self.parent().domain()
the codomain is in
self.parent().codomain()
- check()#
Performs checks on
self
Check that
self
is a proper function and then callsparent.check_element(self)
whereparent
is the parent ofself
.
- codomain()#
Returns the codomain of
self
EXAMPLES:
sage: FiniteSetMaps(4, 3)([1, 0, 2, 1]).codomain() {0, 1, 2}
- domain()#
Returns the domain of
self
EXAMPLES:
sage: FiniteSetMaps(4, 3)([1, 0, 2, 1]).domain() {0, 1, 2, 3}
- fibers()#
Returns the fibers of
self
OUTPUT:
a dictionary
d
such thatd[y]
is the set of allx
indomain
such thatf(x) = y
EXAMPLES:
sage: FiniteSetMaps(4, 3)([1, 0, 2, 1]).fibers() {0: {1}, 1: {0, 3}, 2: {2}} sage: F = FiniteSetMaps(["a", "b", "c"]) sage: F.from_dict({"a": "b", "b": "a", "c": "b"}).fibers() == {'a': {'b'}, 'b': {'a', 'c'}} True
- getimage(i)#
Returns the image of
i
byself
INPUT:
i
– any object.
Note
if you need speed, please use instead
_getimage()
EXAMPLES:
sage: fs = FiniteSetMaps(4, 3)([1, 0, 2, 1]) sage: fs.getimage(0), fs.getimage(1), fs.getimage(2), fs.getimage(3) (1, 0, 2, 1)
- image_set()#
Returns the image set of
self
EXAMPLES:
sage: FiniteSetMaps(4, 3)([1, 0, 2, 1]).image_set() {0, 1, 2} sage: FiniteSetMaps(4, 3)([1, 0, 0, 1]).image_set() {0, 1}
- items()#
The items of
self
Return the list of the ordered pairs
(x, self(x))
EXAMPLES:
sage: FiniteSetMaps(4, 3)([1, 0, 2, 1]).items() [(0, 1), (1, 0), (2, 2), (3, 1)]
- setimage(i, j)#
Set the image of
i
asj
inself
Warning
self
must be mutable; otherwise an exception is raised.INPUT:
i
,j
– twoobject
’s
OUTPUT:
None
Note
if you need speed, please use instead
_setimage()
EXAMPLES:
sage: fs = FiniteSetMaps(4, 3)([1, 0, 2, 1]) sage: fs2 = copy(fs) sage: fs2.setimage(2, 1) sage: fs2 [1, 0, 1, 1] sage: with fs.clone() as fs3: ....: fs3.setimage(0, 2) ....: fs3.setimage(1, 2) sage: fs3 [2, 2, 2, 1]
- class sage.sets.finite_set_map_cy.FiniteSetMap_Set#
Bases:
FiniteSetMap_MN
Data structure for maps
We assume that the parent given as argument is such that:
the domain is in
parent.domain()
the codomain is in
parent.codomain()
parent._m
contains the cardinality of the domainparent._n
contains the cardinality of the codomainparent._unrank_domain
andparent._rank_domain
is a pair of reciprocal rank and unrank functions between the domain andrange(parent._m)
.parent._unrank_codomain
andparent._rank_codomain
is a pair of reciprocal rank and unrank functions between the codomain andrange(parent._n)
.
- classmethod from_dict(t, parent, d)#
Creates a
FiniteSetMap
from a dictionaryWarning
no check is performed !
- classmethod from_list(t, parent, lst)#
Creates a
FiniteSetMap
from a listWarning
no check is performed !
- getimage(i)#
Returns the image of
i
byself
INPUT:
i
– anint
EXAMPLES:
sage: F = FiniteSetMaps(["a", "b", "c", "d"], ["u", "v", "w"]) sage: fs = F._from_list_([1, 0, 2, 1]) sage: list(map(fs.getimage, ["a", "b", "c", "d"])) ['v', 'u', 'w', 'v']
- image_set()#
Returns the image set of
self
EXAMPLES:
sage: F = FiniteSetMaps(["a", "b", "c"]) sage: sorted(F.from_dict({"a": "b", "b": "a", "c": "b"}).image_set()) ['a', 'b'] sage: F = FiniteSetMaps(["a", "b", "c"]) sage: F(lambda x: "c").image_set() {'c'}
- items()#
The items of
self
Return the list of the couple
(x, self(x))
EXAMPLES:
sage: F = FiniteSetMaps(["a", "b", "c"]) sage: F.from_dict({"a": "b", "b": "a", "c": "b"}).items() [('a', 'b'), ('b', 'a'), ('c', 'b')]
- setimage(i, j)#
Set the image of
i
asj
inself
Warning
self
must be mutable otherwise an exception is raised.INPUT:
i
,j
– twoobject
’s
OUTPUT:
None
EXAMPLES:
sage: F = FiniteSetMaps(["a", "b", "c", "d"], ["u", "v", "w"]) sage: fs = F(lambda x: "v") sage: fs2 = copy(fs) sage: fs2.setimage("a", "w") sage: fs2 map: a -> w, b -> v, c -> v, d -> v sage: with fs.clone() as fs3: ....: fs3.setimage("a", "u") ....: fs3.setimage("c", "w") sage: fs3 map: a -> u, b -> v, c -> w, d -> v
- sage.sets.finite_set_map_cy.FiniteSetMap_Set_from_dict(t, parent, d)#
Creates a
FiniteSetMap
from a dictionaryWarning
no check is performed !
- sage.sets.finite_set_map_cy.FiniteSetMap_Set_from_list(t, parent, lst)#
Creates a
FiniteSetMap
from a listWarning
no check is performed !
- sage.sets.finite_set_map_cy.fibers(f, domain)#
Returns the fibers of the function
f
on the finite setdomain
INPUT:
f
– a function or callabledomain
– a finite iterable
OUTPUT:
a dictionary
d
such thatd[y]
is the set of allx
indomain
such thatf(x) = y
EXAMPLES:
sage: from sage.sets.finite_set_map_cy import fibers, fibers_args sage: fibers(lambda x: 1, []) {} sage: fibers(lambda x: x^2, [-1, 2, -3, 1, 3, 4]) {1: {1, -1}, 4: {2}, 9: {3, -3}, 16: {4}} sage: fibers(lambda x: 1, [-1, 2, -3, 1, 3, 4]) {1: {1, 2, 3, 4, -3, -1}} sage: fibers(lambda x: 1, [1,1,1]) {1: {1}}
See also
fibers_args()
if one needs to pass extra arguments tof
.
- sage.sets.finite_set_map_cy.fibers_args(f, domain, *args, **opts)#
Returns the fibers of the function
f
on the finite setdomain
It is the same as
fibers()
except that one can pass extra argument forf
(with a small overhead)EXAMPLES:
sage: from sage.sets.finite_set_map_cy import fibers_args sage: fibers_args(operator.pow, [-1, 2, -3, 1, 3, 4], 2) {1: {1, -1}, 4: {2}, 9: {3, -3}, 16: {4}}


{% extends 'base.html' %} {% block title %} About {{ AUTHOR_SHORTENED }} | {{ super() }} {% endblock title %} {% block meta_tags_in_head %} {{ super() }} {% from '_includes/_defaults.html' import FEATURED_IMAGE with context %} {% if FEATURED_IMAGE %} {% endif %} {% endblock meta_tags_in_head %} {% block content %}
My name is Mitchel Broten - Engineering major, and President of Society of Petroleum Engineers at UT.
I'm currently a senior undergraduate student at the University of Texas at Austin, majoring in Petroleum Engineering at The Hildebrand Department of Petroleum Engineering, and minoring in Business at Texas McCombs School of Business. As well as being a student, I have real world experience working for oil & gas operators and as a research assistant. I also have leadership experience as former Vice President Internal of our school SPE chapter and as current President.
Right now my primary focus is on building my set of skills in business, coding, statistics, and engineering. My future goal is to be able to combine my interests in engineering, coding, and business to solve problems in the oil and gas industry. Part of the reason why I started this blog is not only to teach others these concepts, but to make sure I myself understand them.
I would love to hear any questions or comments you might have about me or my blog. You can reach me via mitchelbroten@gmail.com


Verifies allowance of operator
to execute command
with tokenId
security token.
Verifies allowance of sender
to transfer tokenId
security token.
Creates a new Security Token with pre-defined Symbol feature set.
Execute command
for Security Token with identifier tokenId
. Arguments
the command execution can be passed in argv
.
Gets a command instance around context
and tokenId
.
Gets an execution context
Read metadata of a previously created Security Token with identifier tokenId
.
Read operators of a token.
Read restrictions of a previously created Security Token with identifier tokenId
.
(Optional)
Notify an account account
about notification
Publish a previously created Security Token with identifier tokenId
.
(Optional) partitions records
Generated using TypeDoc
Standard
contracts
v0.1.0
Interface that describes security token standards.


The client protocol.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
sendMessage(self,
message,
subchannel,
typeName=None,
asObject=False,
asDatagram=False)
Send a message directly to the server. |
source code
|
|
|
|
|
|
|
|
|
|
|
|
|
serverGreeted(self,
welcome)
Called when the server has responded to our welcome. |
source code
|
|
|
|
connectionAccepted(self)
Called when the server has accepted the requested connection. |
source code
|
|
|
|
loginAccepted(self,
name)
Called when the server has accepted the requested name (or has
specified one itself). |
source code
|
|
|
|
nameChanged(self,
name)
Called when the server has accepted name change (or has given the
client a new one). |
source code
|
|
|
|
serverDenied(self,
response)
Called when the server disconnects or when the server denies an
client request. |
source code
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
pingReceived(self)
Called when a server ping has been received. |
source code
|
|
|
Inherited from protocol.BaseProtocol :
dataReceived ,
validName
Inherited from twisted.internet.protocol.Protocol :
__provides__ ,
connectionLost
Inherited from twisted.internet.protocol.BaseProtocol :
__providedBy__ ,
makeConnection
|


A wallet built on the polkadot-js stack. This version is updated alongside any changes to the code and always has the latest features.
An IPFS version of the medifakt-js wallet. This version is updated weekly but fits closer with the Web3 vision of decentralization.
A browser-based vault for management of your account keys. It is meant to be used alongside wallets such as the apps UI.
Community driven lists of urls and addresses of dishonest operators. Used ecosystem wide in wallets and extensions.
Developer documentation for all (most?) of the libraries under the polkadot-js umbrella. If you want to build, this is where to start.


We are a team of UIUC students who create robust software for social good. We believe that our
engineering
skill sets do not render us useless in addressing social injustices. Instead, they empower us to
build
a better society together.
Our Work
Each semester, we select 3-5 nonprofits and provide student teams of 4-7
with
the opportunity to build a great product that solves a core need. In just 1 year, we've created
a
management system for a tutoring program between Cambodian students and English tutors, an
interactive
African American history educational tool for Florida students, and much more!
Cut to the Case
Child's Play
Global Giving
Get Involved
Students
Are you passionate about software and Social
Impact?
Are you looking to join a unique and close-knit community? Join Us! Our mission provides a
distinct
experience to develop technical skills and interact with nonprofit clients all while
applying
your skills to impact real lives.
Nonprofits
Working with Hack4Impact was easy, efficient and incredibly
productive.
They were quick to understand what we were looking to achieve and made the app even better
and
simpler to use than what I had imagined."
- Bernardo H. Motta, Ph.D.
Faculty Coordinator of the USFSP Neighborhood News
Bureau


FY2015V-00110
12-02-2015
Sri. rtgs 16
ten thousand six only.
honorarium for the concert on 08-04-15 advance payment sreevalsan j menon
10,006.00
779104
State Bank of Mysore


10294856: Novel bioreactor design for fermentation of syngas to industrially relevant chemicals
Business not registered on Companies House
- Stated business type:
- Limited Liability Partnership
Bank account details have been submitted to Innovate UK for use during the project 10294856: Novel bioreactor design for fermentation of syngas to industrially relevant chemicals (10294856)
Finance contact
Dave Normen
<EMAIL_ADDRESS>0114 26645697


Hawaii Grown: Around the Nation | Honolulu Star-Advertiser
Kekaula Kaniho, Kahuku ’17: The junior safety for No. 20 Boise State recorded five total tackles, one for loss, in the Broncos’ 42-9 win over New Mexico. The win moved 20th-ranked Boise State to 9-1 this season. Read more
Mahalo for reading the Honolulu Star-Advertiser!
You're reading a premium story. Read the full story with our Print & Digital Subscription.
Already a subscriber? Log in now to continue reading this story.
Print subscriber but without online access? Activate your Digital Account now.


Save4Life weekly reportFor the week starting {{start_date}} |
|
Total amount of airtime redeemed this week: {{total_airtime}} Total amount of airtime saved this week: {{total_savings_amount}} Average savings this week: {{average_savings}} Total 2 week streaks this week: {{streak_2}} Total 4 week streaks this week: {{streak_4}} Total 6 week streaks this week: {{streak_6}} Total quizzes completed this week: {{quizzes_completed}} Average quiz score this week: {{average_quiz_score}} |


Dear Friend, Top of the day to you, My name is Jun L. Wang, CEO.(cmiec ch) China. We are a group of business men who deal on import and export raw materials into Canada, America and Europe. We are looking for a representative who can help our company collect money been owed by our customer in, Europe,America,and Canada. Please if you are interested in transacting business with our companysubject to your satisfaction and in view of helping us, we will be very glad. Contact us for more information, If this proposal is acceptable to you, forward to us this information: CONTACT ADDRESS: FULL NAME: PHONE AND FAX NUMBER: Best regards, Jun L. Wang, CEO(cmiec ch) China. ___________________________________________________________________________ Mail sent from WebMail service at Ourfamilyaffair.com- http://ourfamilyaffair.com


wg-gesucht
This is a link to a page on wg-gesucht.
studierzimmer-muenster
This is a link to a website on the studierzimmer-muenster.
stadtwerk-muenster
This is a link to a website on the stadtwerk-muenster.
Search For Accommodation
| size in m2 | Min | Max | ||
| price in € | Min | Max | ||
| Type | Flat | WG | ||
| Number of fellow lodger | Min | Max | ||
| Number of Rooms | Min | Max | ||
| Zip Code: |
Add a distance for your area of interest


Intelligence measures mental acuity, accuracy of recall, and the ability to reason.
An Intelligence check comes into play when you need to draw on logic, education, memory, or deductive reasoning. The Arcana, History, Investigation, Nature, and Religion skills reflect aptitude in certain kinds of Intelligence checks.
Arcana. Your Intelligence (Arcana) check measures your ability to recall lore about spells, magic items, eldritch symbols, magical traditions, the planes of existence, and the inhabitants of those planes.
History. Your Intelligence (History) check measures your ability to recall lore about historical events, legendary people, ancient kingdoms, past disputes, recent wars, and lost civilizations.
Investigation. When you look around for clues and make deductions based on those clues, you make an Intelligence (Investigation) check. You might deduce the location of a hidden object, discern from the appearance of a wound what kind of weapon dealt it, or determine the weakest point in a tunnel that could cause it to collapse. Poring through ancient scrolls in search of a hidden fragment of knowledge might also call for an Intelligence (Investigation) check.
Nature. Your Intelligence (Nature) check measures your ability to recall lore about terrain, plants and animals, the weather, and natural cycles.
Religion. Your Intelligence (Religion) check measures your ability to recall lore about deities, rites and prayers, religious hierarchies, holy symbols, and the practices of secret cults.
Other Intelligence Checks. The GM might call for an Intelligence check when you try to accomplish tasks like the following:
Wizards use Intelligence as their spellcasting ability, which helps determine the saving throw DCs of spells they cast.


Python#
This page contains the full documentation for the Python-interface of the IOHexperimenter. The Python-version of IOHexperimenter is built using pybind11, and desiged so most functions closely match their C++ equivalents, with a few added ease-of-use settings.
Quickstart#
Note that these instructions are for versions >= 0.3.10. The minimum required Python version is 3.6.
Installation#
You can install the experimenter directly from pip:
pip install ioh>=0.3.10
To verify the installation, you can use:
pip show ioh
Create a function object#
The most basic way to use the IOHexperimenter is to just access the problems from our predefined problem suites. For example one of the 25 Pseudo-Boolean problems or any of the single-objective BBOB-problems from COCO.
To use these problems, you can import the associated module as follows:
from ioh import problem
For all of these problems, you can then access the docstrings to get more information about precise usage.
help(problem)
These modules can then be used exactly as their c++ equivalent. However, for convenience, some wrapper functions are provided, such as the get_problem function. To get a 5-dimensional sphere function, with instance number 1, you can use the following:
from ioh import get_problem, ProblemClass
f = get_problem("Sphere", 1, 5, ProblemClass.BBOB)
Instead of using the name of the function, you can also use their function number within their respecitve suite:
f1 = get_problem(1, 1, 5, ProblemClass.PBO)
With these problem-objects, the state, meta_data and contrainsts can easily be accessed:
f1.meta_data
f1.bounds
f1.state
And the problem can be evaluated by calling it:
f([0,0,0,0,0])
This will then immediately update the state-variables:
f.state.evaluations
Running an algorithm#
To showcase how to use these functions in combination with an optimization algorithm, we define a simple random-search example wich accepts an argument of class IOH_function.
import numpy as np
np.random.seed(42)
def random_search(func, budget = 10):
for i in range(budget):
x = np.random.uniform(func.bounds.lb, func.bounds.ub)
func(x)
To record data, we need to add a logger to the problem. We can do this easily by importing the logger module:
from ioh import logger
help(logger.Analyzer)
This logger can then be initialized with the directory in which to store the logs:
#Create default logger which writes to folder 'temp'
l = logger.Analyzer(folder_name="temp")
This can then be attached to the problem:
f = get_problem(1, 1, 5, ProblemClass.BBOB)
f.attach_logger(l)
Now, we can run the algorithm and store data
random_search(f)
To ensure all data is written, we should flush the logger after running our experiments. This happens automatically when the python process terminates, but when running in an interactive environment, such as a jupyter notebook, this should be done explicitly.
f.reset()
l.close()
Note that we should call the reset
method on a problem. By calling the reset
method, the problem’s internal state is automatically reset, and the data for the attached loggers will be flushed to the output streams. This function should also be used when performing multiple runs of the same problem in a loop, for example:
f5 = get_problem(5, 1, 5)
l2 = logger.Analyzer(folder_name="temp2")
f5.attach_logger(l2)
for run in range(10):
random_search(f5)
f5.reset()
l2.close()
Tracking parameters#
If we want to track parameters of the algorithm, these variables need to be available on a object, i.e. as member variables on a class instance. In order to do this for the random search algorithm, we can do this be wrapping the function in a class.
class RandomSearch:
def __init__(self, budget):
#Note that we should re-initialize all dynamic variables if we want to run the same algorithm multiple times
self.budget = budget
# A parameter static over the course of an optimization run of an algorithm
self.algorithm_id = np.random.randint(100)
# A dynamic parameter updated by the algorithm
self.a_tracked_parameter = None
def __call__(self, func):
self.f_opt = np.Inf
self.x_opt = None
for i in range(self.budget):
x = np.random.uniform(func.bounds.lb, func.bounds.ub)
# Update the tracked parameter
self.a_tracked_parameter = i ** 10
f = func(x)
if f < self.f_opt:
self.f_opt = f
self.x_opt = x
return self.f_opt, self.x_opt
@property
def a_property(self):
return np.random.randint(100)
def reset(self):
self.algorithm_id = np.random.randint(100)
A full example is below, we first instantiate the algorithm instance, after which we create a new logger. Then we update the logger instance, telling it to track the algorithm_id
parameter when we start a new run with a problem. The variable a_tracked_parameter
is updated before every problem evaluation, so we want the logger to store this variable at every problem evaluation. We can also do this for properties, using the same method.
algorithm = RandomSearch(10)
l3 = logger.Analyzer(folder_name="temp3")
# Track variables static over the course of an algorithm run
l3.add_run_attributes(algorithm, ["algorithm_id"])
# Track dynamic variables, updated during the run of an algorithm
l3.watch(algorithm, ["a_property", "a_tracked_parameter"])
# attach a problem to the logger
p2 = get_problem(2, 2, 5)
p2.attach_logger(l3)
for run in range(10):
algorithm(p2) # run the algorithm on the problem
p2.reset() # reset the problem and logger state
algorithm.reset() # update the algorithm_id parameter
Alternatively, we can use the Experiment
class, to more easily run the benchmarking experiment with multiple functions.
from ioh import Experiment
help(Experiment)
This can be initialized using a problem class by providing lists of function ids (or names), dimensions, instance ids and a number of independent repetitions as follows:
exp = Experiment(
RandomSearch(10), # instance of optimization algorithm
[1], # list of problem id's
[1, 2], # list of problem instances
[5], # list of problem dimensions
problem_class = ProblemClass.BBOB, # the problem type, function ids should correspond to problems of this type
njobs = 1, # the number of parrellel jobs for running this experiment
reps = 2, # the number of repetitions for each (id x instance x dim)
logged_attributes = [ # list of the tracked variables, must be available on the algorithm instance (RandomSearch)
"a_property",
"a_tracked_parameter"
]
)
exp.run()
To start analyzing this data, simply upload the zip ‘data’-folder and upload it to the IOHanalyzer!
For a more fully flegded tutorial, which goes a more into detail on adding custom problems/loggers and dealing with constraints, please find the file example.ipynb in our github repository.


repo.fullName = {{repo.fullName}}
repo.owner = {{repo.owner}}
repo.name = {{repo.name}}
repo.SCM = {{repo.SCM}}
repo.link = {{repo.link}}
repo.avatar = {{repo.avatar}}
repo.branch = {{repo.branch}}
repo.private = {{repo.private}}
repo.trusted = {{repo.trusted}}
remote.URL = {{remote.URL}}
commit.SHA = {{commit.SHA}}
commit.ref = {{commit.ref}}
commit.branch = {{commit.branch}}
commit.link = {{commit.link}}
commit.message = {{commit.message}}
commit.author.name = {{commit.author.name}}
commit.author.email = {{commit.author.email}}
commit.author.avatar = {{commit.author.avatar}}
build.number = {{build.number}}
build.event = {{build.event}}
build.status = {{build.status}}
build.link = {{build.link}}
build.created = {{build.created}}
build.started = {{build.started}}
build.finished = {{build.finished}}
prev.build.status = {{prev.build.status}}
prev.build.number = {{prev.build.number}}
prev.commit.SHA = {{prev.commit.SHA}}
job.status = {{job.status}}
job.exitCode = {{job.exitCode}}
job.started = {{job.started}}
job.finished = {{job.finished}}
yaml.signed = {{yaml.signed}}
yaml.verified = {{yaml.verified}}
tag = {{tag}}
pullRequest = {{pullRequest}}
deployTo = {{deployTo}}
lowercase = {{lowercase "QWQWQWQW"}}
{{success ""}}
{{#if success}}
success
{{else}}
!success
{{/if}}
{{#if failure}}
failure
{{else}}
!failure
{{/if}}


System Logs
Error reading logs!!!
Timestamp
Message
Log Level
Error
Warning
Info
Debug
Verbose
by Shogunxam


--- layout: post title: "In the News: NEPC Talks Education" date: 2021-11-18 15:01:00 +0000 tags: image: https://s3.amazonaws.com/audreywatters/2017-11-03-news.jpg imagecredits: https://www.flickr.com/photos/62693815@N03/6277209256 ---
I chatted with Christopher Saldaña about Teaching Machines on the NEPC Talks Education podcast. (It was a great conversation.)


There are a number of program options used on a daily basis in xia2, which are:
-atom X tell xia2 to separate anomalous pairs i.e. I(+) I(−) in scaling -2d tell xia2 to use MOSFLM and Aimless -3d tell xia2 to use XDS and XSCALE -3dii tell xia2 to use XDS and XSCALE, indexing with peaks found from all images -dials tell xia2 to use DIALS and Aimless -xinfo modified.xinfo use specific input file -image /path/to/an/image.img process specific scan -small molecule process in manner more suited to small molecule data space_group=sg set the spacegroup, e.g. P21 unit_cell=a,b,c,α,β,γ set the cell constants
The subject of resolution limits is one often raised - by default in xia2 they are:
- Merged
- Unmerged
However you can override these with -misigma, -isigma
Note
We are currently moving towards moving PHIL (Python-based Hierarchial Interchange Language) for specifying xia2 program parameters, which will in the long run help the documentation, but in the mean time you may see some warnings as certain parameters are changed from -param style parameters to param= style PHIL parameters. If you see, e.g.:
Warning: -spacegroup option deprecated: please use space_group='P422' instead
Warning: -resolution option deprecated: please use d_min=1.5 instead
don’t panic - this is to be expected - but you may want to change the way you run xia2 or your scripts. More of a warning for beamline / automation people! The outcome of this should however be automated generation of command-line documentation and the ability to keep “recipes” for running xia2 in tidy files.
Here is a comprehensive list of PHIL parameters used by xia2:
general { check_image_files_readable = True } xds { delphi = 5 delphi_small = 30 untrusted_ellipse = None untrusted_rectangle = None trusted_region = None profile_grid_size = None correct { refine = *DISTANCE *BEAM *AXIS *ORIENTATION *CELL *POSITION } integrate { refine = *ORIENTATION *CELL *BEAM *DISTANCE AXIS *POSITION refine_final = *ORIENTATION *CELL BEAM DISTANCE AXIS POSITION fix_scale = False delphi = 0 reflecting_range = 0 reflecting_range_esd = 0 beam_divergence = 0 beam_divergence_esd = 0 reintegrate = true } init { fix_scale = False } index { refine = *ORIENTATION *CELL *BEAM *DISTANCE *AXIS *POSITION debug = *OFF ON } colspot { minimum_pixels_per_spot = 1 } xscale { min_isigma = 3.0 } merge2cbf { merge_n_images = 2 data_range = None moving_average = False } } dials { fix_geometry = False outlier.algorithm = null *auto mcd tukey sauter_poon fast_mode = False find_spots { min_spot_size = Auto min_local = 0 phil_file = None sigma_strong = None filter_ice_rings = False kernel_size = 3 global_threshold = None } index { method = fft1d *fft3d real_space_grid_search phil_file = None max_cell = 0.0 use_all_reflections = False fft3d.n_points = None } refine { scan_varying = True interval_width_degrees = 36.0 use_all_reflections = True phil_file = None reflections_per_degree = 100 } integrate { phil_file = None profile_fitting = True background_outlier_algorithm = *null nsigma truncated normal tukey mosflm background_algorithm = simple null *glm use_threading = False include_partials = True } } ccp4 { truncate { program = 'ctruncate' } reindex { program = 'pointless' } aimless { intensities = summation profile *combine surface_tie = 0.001 surface_link = True } } xia2.settings { input { image = None json = None reference_geometry = None reverse_phi = False xinfo = None gain = None min_images = 10 min_oscillation_range = None } sweep { id = None range = None exclude = False } scale { directory = Auto } unit_cell = None space_group = None d_min = None d_max = None optimize_scaling = False unify_setting = False beam_centre = None trust_beam_centre = False wavelength_tolerance = 0.00001 read_all_image_headers = True detector_distance = None show_template = False untrusted_rectangle_indexing = None xds_cell_deviation = 0.05, 5.0 use_brehm_diederichs = False developmental { use_dials_spotfinder = False pointless_tolerance = 0.0 } integrate_p1 = False reintegrate_correct_lattice = True xds { geometry_x = None geometry_y = None } indexer = mosflm labelit labelitii xds xdsii xdssum dials refiner = mosflm xds dials integrater = mosflmr xdsr mosflm xds dials scaler = ccp4a xdsa verbose = False multiprocessing { mode = *serial parallel nproc = Auto njob = Auto type = *simple qsub qsub_command = '' } }


--- layout: page title: Keith Ferguson date: 2013-02-18 22:10:00.000000000 -05:00 type: page published: true status: publish categories: [] tags: [] meta: _edit_last: '396' _wp_page_template: default author: login: kenny email<EMAIL_ADDRESS>display_name: kenny first_name: Kenneth last_name: Flynn ---
My graduate research in Dr. Cooper’s lab focused on how populations of Pseudomonas aeruginosa PA14 adapted to biofilm formation, development and dispersal. Broad goals of the project included measuring phenotypic and genetic diversity and quantifying fine-scale fitness effects of mutations observed in our model. A more specific goal included characterizing an adaptive allele in a polyphosphate kinase (ppk) gene.
As a recent graduate, I’m looking to find a career in the biotech field and am interested in the uses of genetically engineered microbes for industrial applications.


Greece refusal sends captured Isis fighter back to USA
by GCTTurkish forces captured the man amid its illegal incursion into Syria this October.
The Islamic State fighter was sent back to the United States after the man was held in limbo at the Turkey-Greece border, Turkish officials announced Friday.
Turkey-supported forces captured Muhammad Darwish Bassam, 39, who is of Jordanian descent, in October during Turkey’s military offensive in Syria. Turkey initially sent Bassam to Greece, his country of choice, but Greece denied him entry.
Turkish Interior Minister Suleyman Soylu said Bassam was “stuck” between Turkey and Greece. The United States also initially refused him, but later approved the deportation.
“Upon the commitment of the USA to issue a travel document, necessary procedures have been initiated to send the foreign terrorist fighter to the USA,” the Turkish Interior Ministry said.
President Donald Trump has also urged European allies to readmit citizens who left to join the Islamic State. He’d said U.S.-backed forces in Syria held more than 800 foreign Islamic State fighters.


I'm a Jedi, like my father before me!
(play as a cross)
Power, unlimited power!
(play as a circle)
Judge me by my size, do you?
(wise computer)
We're doomed!
(dumb computer)


With a creative mindset, passion for learning, strong technical and troubleshooting skill set, and a variety of work experiences, my goal is to pursue a career as a front-end web developer where I can make tangible contributions towards an exciting product while growing as a programmer.
I've worked for the past 3 years as an electrical engineer, and before that I worked for 2+ years as a competition producer for various reality TV shows. My work experiences have taught me the value of utilizing my unique skill set for tackling challenges from both a creative and technical angle.


Awardees-Récipiendaires
- 2015- Patricia Wright, University of Guleph. Living on the edge - The physiology of amphibious fish in and out of water.
La vie à la limite - physiologie des poissons amphibies dans et hors de l'eau
- 2014- Glen Van Der Kraak, University of Guelph. The sex lives of fish: Science, policy and beyond.
- 2013- Miodrag Belosevic, University of Alberta. Life is PIE/ La vie c'est PIE.
- 2012- Steve Perry, University of Ottawa. Reelin' in the Years: A Retrospective Look at Fish Ionic Regulation/ Au fil des années: un regard rétrospectif sur la régulation ionique des poissons
- 2011- Kenneth Storey, Carleton University. Exploring biochemical adaptations: synthetic intuition on a family farm
- 2010- Joseph S. Nelson, University of Alberta. From Kokanee to Suckers to Sticklebacks to classifying the world of fishes/Des Kokanee aux suceurs aux épinoches à la classification des poissons du monde
2009- Anthony Farrell, University of British Columbia
- 2008- Jeremy Mc Neil, University of Western Ontario
- 2007- Nancy M. Sherwood, University of Victoria. The evolution of brain hormones that control reproduction: Genomics to the rescue. L'évolution des hormones cérébrales contrôlant la reproduction : la génomique à la rescousse
- 2006- Richard E. Peter, University of Alberta. Neuroendocrine control systems in the goldfish. Systèmes de contrôle neuroendocrine chez le poisson rouge
- 2005 - John Youson, University of Toronto, Scarborough. "A life of research with fishes of ancient lineage - Une vie de recherche sur des lignées anciennes de poissons"
- 2004- Thomas W. Moon, University of Ottawa. Fish metabolism: the good, the bad and the ugly. Le métabolisme des poissons: le bon, le mauvais et l'effrayant
- 2003- William K. Milsom, University of British Columbia. Adaptive trends in respiratory control: A comparative perspective / Tendances adaptatives du contrôle respiratoire: une étude comparative
- 2002- Robert G. Boutilier , Cambridge University. Mechanisms of cell survival in hypoxia and hypothermia. / Méchanismes de survie cellulaire dans l'hypoxie et l'hypothermie
- 2001- F.W.H. Beamish, Burapha University. Axioms and anecdotes of a zoologist. / Axiomes et anecdotes d'un zoologiste
- 2000- John Philips, University of British Columbia. Pumps, Peptides and Pests
- 1999- Chris M. Wood, McMaster University. Physiology of The Lake Magadi Tilapia, a fish adapted to one of the most extreme aquatic environments on Earth
- 1998- Geoffrey J. Eales, University of Manitoba. Thyroxine - hormone or vitamin?
- 1997- Harold Atwood, Toronto. Adaptation in the nervous system.
- 1996- Charles Krebs, University of British Columbia. Vertebrate community dynamics in the Yukon boreal forest.
- 1995- Peter Hochachka, University of British Columbia. Regulated metabolic suppression in surviving oxygen lack: a conceptual mirror to Fry's "scope for activity"
- 1994- Brian Hall, Dalhousie University. Development and evolution of the vertebrate skeleton
- 1993- David Randall, University of British Columbia. Fish gas transfer: conflicts and compromise in design
- 1992- Dave R. Jones, University of British Columbia. Cardiovascular dynamics of the alligator
- 1991- Roger Downer, University of Waterloo. Exciting insects and other biological diversions
- 1990- William C. Leggett, McGill University. Understanding variations in fish distribution and abundance; is the answer blowing in the wind?
- 1989- G.O. Mackie, University of Victoria. Aggregates or integrates? Aspects of communication in animal communities
- 1988- Denis Chitty, University of British Columbia. Beautiful hypotheses and ugly facts
- 1987- K. G. Davey, York University. Blood, guts, sex and affairs of the heart in insects
- 1986- D. R. Idler, Memorial University of Newfoundland. Fish hormones: my personal experiences
- 1985- J. R Brett, Pacific Biological Station. Production energetics of a population of sockeye salmon, Onchorhynchus nerka.
- 1984- No award.
- 1983- W. E. Ricker, Pacific Biological Station. How to draw a straight line.
- 1982- F. J. Rigler, University of Toronto. (No lecture given because of illness.)
- 1981- K. Ronald, University of Guelph. Life and death of a seal. Published in Science 215:928-933,1982, in collaboration with J.L. Dougan under the title "The ice lover: biology of the harp seal (Phoca groenlandica)."
- 1980- D. M. Ross. University of Alberta. Illusion and reality in comparative physiology. Published in Can. J. Zool. 59:2151-2158, 1981.
- 1979- M. J. Dunbar, McGill Univrsity.  Published in Can. J. Zool. 58:123-128, 1980.
- 1978- P. A. Larkin, University of British Columbia. Maybe you can't get there from here: A foreshortened history of research in relation to management of Pacific salmon. Published in J. Fish Res. Board Can. 36:98-106, 1979.
- 1977- H. I. Battle, University of Western Ontario. A saga of zoology in Canada.
- 1976- I. McTaggart-Cowan, University of British Columbia. The sociology of carnivores related to their use of resources.
- 1975- F. R Hayes, Dalhousie University. Quantitative and aesthetic factors in the definition of an ideal environment. Published in Can. J. Zool. 54:809-815, 1976.
- 1974- W. S. Hoar, University of British Columbia. Smolt transformation: evolution, behavior and physiology. Published in J. Fish. Res. Board Can. 33:1233-1252, 1976.


HTTP server response status codes.
| Enumerator |
|---|
| HTTP_STATUS_CONTINUE | 100, Continue)
|
| HTTP_STATUS_SWITCHING_PROTOCOLS | 101, Switching Protocols)
|
| HTTP_STATUS_PROCESSING | 102, Processing)
|
| HTTP_STATUS_OK | 200, OK)
|
| HTTP_STATUS_CREATED | 201, Created)
|
| HTTP_STATUS_ACCEPTED | 202, Accepted)
|
| HTTP_STATUS_NON_AUTHORITATIVE_INFORMATION | 203, Non-Authoritative Information)
|
| HTTP_STATUS_NO_CONTENT | 204, No Content)
|
| HTTP_STATUS_RESET_CONTENT | 205, Reset Content)
|
| HTTP_STATUS_PARTIAL_CONTENT | 206, Partial Content)
|
| HTTP_STATUS_MULTI_STATUS | 207, Multi-Status)
|
| HTTP_STATUS_ALREADY_REPORTED | 208, Already Reported)
|
| HTTP_STATUS_IM_USED | 226, IM Used)
|
| HTTP_STATUS_MULTIPLE_CHOICES | 300, Multiple Choices)
|
| HTTP_STATUS_MOVED_PERMANENTLY | 301, Moved Permanently)
|
| HTTP_STATUS_FOUND | 302, Found)
|
| HTTP_STATUS_SEE_OTHER | 303, See Other)
|
| HTTP_STATUS_NOT_MODIFIED | 304, Not Modified)
|
| HTTP_STATUS_USE_PROXY | 305, Use Proxy)
|
| HTTP_STATUS_TEMPORARY_REDIRECT | 307, Temporary Redirect)
|
| HTTP_STATUS_PERMANENT_REDIRECT | 308, Permanent Redirect)
|
| HTTP_STATUS_BAD_REQUEST | 400, Bad Request)
|
| HTTP_STATUS_UNAUTHORIZED | 401, Unauthorized)
|
| HTTP_STATUS_PAYMENT_REQUIRED | 402, Payment Required)
|
| HTTP_STATUS_FORBIDDEN | 403, Forbidden)
|
| HTTP_STATUS_NOT_FOUND | 404, Not Found)
|
| HTTP_STATUS_METHOD_NOT_ALLOWED | 405, Method Not Allowed)
|
| HTTP_STATUS_NOT_ACCEPTABLE | 406, Not Acceptable)
|
| HTTP_STATUS_PROXY_AUTHENTICATION_REQUIRED | 407, Proxy Authentication Required)
|
| HTTP_STATUS_REQUEST_TIMEOUT | 408, Request Timeout)
|
| HTTP_STATUS_CONFLICT | 409, Conflict)
|
| HTTP_STATUS_GONE | 410, Gone)
|
| HTTP_STATUS_LENGTH_REQUIRED | 411, Length Required)
|
| HTTP_STATUS_PRECONDITION_FAILED | 412, Precondition Failed)
|
| HTTP_STATUS_PAYLOAD_TOO_LARGE | 413, Payload Too Large)
|
| HTTP_STATUS_URI_TOO_LONG | 414, URI Too Long)
|
| HTTP_STATUS_UNSUPPORTED_MEDIA_TYPE | 415, Unsupported Media Type)
|
| HTTP_STATUS_RANGE_NOT_SATISFIABLE | 416, Range Not Satisfiable)
|
| HTTP_STATUS_EXPECTATION_FAILED | 417, Expectation Failed)
|
| HTTP_STATUS_MISDIRECTED_REQUEST | 421, Misdirected Request)
|
| HTTP_STATUS_UNPROCESSABLE_ENTITY | 422, Unprocessable Entity)
|
| HTTP_STATUS_LOCKED | 423, Locked)
|
| HTTP_STATUS_FAILED_DEPENDENCY | 424, Failed Dependency)
|
| HTTP_STATUS_UPGRADE_REQUIRED | 426, Upgrade Required)
|
| HTTP_STATUS_PRECONDITION_REQUIRED | 428, Precondition Required)
|
| HTTP_STATUS_TOO_MANY_REQUESTS | 429, Too Many Requests)
|
| HTTP_STATUS_REQUEST_HEADER_FIELDS_TOO_LARGE | 431, Request Header Fields Too Large)
|
| HTTP_STATUS_UNAVAILABLE_FOR_LEGAL_REASONS | 451, Unavailable For Legal Reasons)
|
| HTTP_STATUS_INTERNAL_SERVER_ERROR | 500, Internal Server Error)
|
| HTTP_STATUS_NOT_IMPLEMENTED | 501, Not Implemented)
|
| HTTP_STATUS_BAD_GATEWAY | 502, Bad Gateway)
|
| HTTP_STATUS_SERVICE_UNAVAILABLE | 503, Service Unavailable)
|
| HTTP_STATUS_GATEWAY_TIMEOUT | 504, Gateway Timeout)
|
| HTTP_STATUS_HTTP_VERSION_NOT_SUPPORTED | 505, HTTP Version Not Supported)
|
| HTTP_STATUS_VARIANT_ALSO_NEGOTIATES | 506, Variant Also Negotiates)
|
| HTTP_STATUS_INSUFFICIENT_STORAGE | 507, Insufficient Storage)
|
| HTTP_STATUS_LOOP_DETECTED | 508, Loop Detected)
|
| HTTP_STATUS_NOT_EXTENDED | 510, Not Extended)
|
| HTTP_STATUS_NETWORK_AUTHENTICATION_REQUIRED | 511, Network Authentication Required)
|


The EnergyScope model
The EnergyScope project is an open-source whole-energy system for regional energy system. The model optimises the design and hourly operation over a year for a target year.
EnergyScope is mainly developped by EPFL (Switzerland) and UCLouvain (Belgium). See Releases section for acknowledgment, versions and publications.
Downloading EnergyScope
The public version of EnergyScope can be downloaded in the Releases section or from its github repository (using the Clone or Download button on the right side of the screen): https://github.com/energyscope/EnergyScope
Main contributors
Stefano Moret (website<EMAIL_ADDRESS>Gauthier Limpens : gauthierLimpens@gmail.com


{% extends "base.html" %} {% load i18n %} {% load account socialaccount %} {% load static %} {% block title %}Tasker | Sign In{% endblock title %} {% block styles %} {% endblock styles %} {% block content %} {% include 'header.html' %}
{% blocktrans with site.name as site_name %}Please sign in with one of your existing third party accounts. Or, sign up for a {{ site_name }} account and sign in below:{% endblocktrans %}
{% include "socialaccount/snippets/login_extra.html" %} {% else %}{% blocktrans %}If you have not created an account yet, then please sign up first.{% endblocktrans %}
{% endif %}


A Civil Action Rated: PG-13 A Review By: Ryan Davis
What happens when a greedy, cut throat personal injury lawyer gets a heart of gold? This is the simple basis to one of the year's best pictures. Although nicely written and directed by Steven Zaillian, the Academy Award winning writer of Schindler's List, `A Civil Action' doesn't rely on its artistic style or atmosphere, but mainly on the acting power of its incredible ensemble.
`A Civil Action' is a true story, based on the best selling novel of the same name, by Jonathan Harr. The film introduces us to Jan Schlichtmann(John Travolta), a rich and powerful, personal injury attorney. He has found a case in which two powerful corporations may have dumped toxins that accidentally poisoned the water in a small town. The water may have caused eight children to develop leukemia, and their families want to know the truth.
Jan, after much deliberation, decides to take the case against the companies. So he and his law partners (which include the brilliant William H. Macy, among others), begin what is to become their most expensive and trying case. But the corporations are not going down easy, they have their own cut throat lawyers. Jerome Facher(Robert Duvall) is one of them and he knows every trick in the book. As they get further along in the case, they get further and further into debt. They even begin to doubt if they will win the case at all.
The film runs brilliantly for an hour and a half but as it nears the end, due to time constraints I am guessing, they begin to cover too much too fast. The end happens far too quickly, and leaves you feeling unsatisfied. If they had added fifteen minutes to the film, this could have been corrected.
That being said, the movie is more performance powered than story driven. Travolta is simply marvelous as Jan. Upstaged only by Duvall's perfectly executed, heartless corporate lawyer.
All in all the film is great, terrific performances and for the most part, great writing and directing. One of the top ten movies of 1998.
Grade: A
Ryan Davis<EMAIL_ADDRESS><EMAIL_ADDRESS>My Movie Review Archives: http://us.imdb.com/M/reviews_by?Ryan+Davis
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


piezoelectric resonator control flow valve working element member contact connected figref[FIG. document-id:: frequency linear claim citation: cited configured motor [patcit]: according claim-ref[claim passage orthogonal site excitation high vibrational CLAIM-TEXT:. applicant modes position valves, fluid frictional input valves body embodiments movement output relative seat used disclosed invention moving provided al. length method using comprises embodiment shown closed comprising: direction formed having herein. illustrated movable resolution spring width EMI-D amplifier connect described device diagram elements example, nano-elliptical non-limiting open paths present provide providing pulse regulating resonator, respect stem stopper surface valve. CLAIM-TEXT. CLAIM-TEXT:a and/or art attached classification-national:: description different external flat fully includes invention. limited longitudinal mobile modulating motion purpose rate reference signal special step Petrenko [addressbook]: action-date: acts actuator combination corresponding duration equivalent examiner flow. frequencies generating-office:: generator include increase inlet intended member. moves outlet particular passages power processors, range resonator. simplified sites skilled specific system, system; understood valve, various waves


Marco D. Nunez is a
3rd year law student at the Universtiy of San Francisco School of Law
-
- "
- In Twelve Angry Men we never see
the jury review or discuss a single jury instruction. Instead, we see that the jury is motivated by the facts and their own sense of drama.
-
- "
- "
- After seeing Twelve Angry Men, my view
is that, although the system
is imperfect, justice can still be achieved.
-
- "
-
-
-
|
|
Twelve Angry Men
by Mark Nunez
Before writing this essay, I casually
asked a friend what her thoughts were regarding the jury system in our country. She
laughed and replied, "It doesnt work. Everybody knows its just a
joke." Changing the subject, she asked: "So, what are we doing after
dinner?" My friends conclusory statement bothered me. She obviously presumed
that I embraced what she perceived as the majority view and that, therefore, the subject
did not merit further discussion. I had just finished watching Twelve Angry Men and
thus felt inspired to challenge what she hastily regarded as settled.
Twelve Angry Men is a
wonderful film that dramatizes the "imperfections" inherent in
the American jury system. Simultaneously, it delivers the powerful message that because we
are human beings and not machines, it is in the nature of things that justice demands such
a system.
At the outset, eleven jurors vote in
favor of convicting the accused without even discussing a single shred of the evidence
presented at trial. Only one brave juror refuses to vote. He openly admits that he does
not know whether the accused is guilty or innocent and that he finds it necessary to
simply talk about the case. What follows is not only a discussion of the particular facts
of the case, but an intense examination of the personal baggage that each jury member
brings to the room.
Its great that
the film is not overtly critical of the fact that the jurors personal baggage is not
checked at the door. Many critics argue that the jury system works against justice because
a jury is not trained to distance itself from a case in the same way that a lawyer or
judge is trained to do. On a certain level, this argument makes sense. At least its
a rational argument. However, how is it possible for human beings to check their lived
experience at the door? Is it necessarily "bad" that jurors scrutinize the
evidence through the unique filters with which they view the world? After all, are they
not called upon to speak on behalf of the diverse community in which we live? These are
key questions Twelve Angry Men begs us to ask. Theyre good questions because
they force us to reevaluate our thinking before hastily reaching the conclusion that the
system doesnt work or that it amounts to nothing more than a mere joke.
The film also does a great job of not
being overtly critical of the fact that some people merely follow their "gut"
when it comes time to cast their vote. One particular juror in Twelve Angry Men
votes in favor of convicting the accused. When challenged, however, he readily admits that
he doesnt know why he thinks that the accused is guilty. This mans character
is used as a vehicle to expose a serious flaw in the system. We see that sometimes jurors
completely abandon reason. Many critics advance the rational argument that the power of a
juror to decide one way or another for no apparent reason cannot possibly work to achieve
justice. However, the film also exposes us to those jurors in the room who openly express
their thoughts, ideas, and feelings about the case. This juxtaposition of characters in
the jury room is ultimately consistent with the fact that the room should reflect the
diverse community in which we live.
Still, what happens when the jury
doesnt understand the legal definition of murder? In Twelve Angry Men we
never see the jury review or discuss a single jury instruction. Instead, we see that the
jury is motivated by the facts and their own sense of drama. Ultimately, they reach a
consensus based on a combination of the facts and their own personal baggage. Thus, the
film raises yet another thought-provoking question: Does the power of the jury to go its
own way warrant abandoning the system altogether?
After seeing Twelve Angry Men,
my view is that, although the system is imperfect, justice can still be achieved. We
breathe a sigh of relief when we see that one man is willing to challenge what eleven
other jurors have regarded as settled at the outset. We see that the system works and
think justice is achieved when this mans uncertainty and reasonable doubt slowly but
surely become every mans uncertainty and reasonable doubt. In the final analysis, we
all pull for that one courageous man who instigates the doubt in the room and opens the
eyes of the blind to the truth. Thus, abandoning the system altogether is not the answer.
Maybe were supposed to walk
away from Twelve Angry Men with a better understanding of how unrealistic it is to
expect the human element to remain completely independent from the rule of law. Perhaps we
leave the film with ideas for jury reform to make the system less imperfect. Maybe some of
us think jurors should be paid a decent salary so as to motivate them to dutifully fulfill
their civic duty. Maybe some of us think that a jury should consist of a panel of judges,
a group of distinguished citizens, or hybrids (judges with lay people). Maybe some would
like to afford a jury with the services of a lawyer ex-officio to help the jury figure out
the meaning of the law. In the end, however, the system remains.
Posted April 2000
|


There will be a chemical attack at an indoor mall.
The Charger group only attacks during the day.
No attacks are being planned outdoors in Troutland or Perchland.
Sharkland has closed all its shopping malls.
An attack is being planned for the 15th of the month.
The Bronco group may be involved.
The Lizard has been seen in Bassland.
The Steeler, Raider, and Bronco groups have blood ties.
Outdoor malls in Perchland have been sources of insurgent recruits.
The Snake was born in Sharkland.
Perchland has a secular government.
The Bronco group prefers to attack at night.
Military bases in Bassland are increasing night patrols.
The Panther, Charger, Titan, Raven, or Steeler groups may be planning an attack.
The Panther and Charger groups prefer unprotected targets.
The Panther, Charger, Titan, and Raven groups have the capacity to operate in Troutland, Perchland, Salmonland, Bassland, and Sharkland.
Daring day attacks make the attacker seem unstoppable.
The Raven and Steeler groups do not use chemical or biological weapons.
The Charger group does not work in Bassland.
The Raider and Bronco groups only target the military.
The Titan group focuses on destroying energy infrastructure.
The target is an indoor mall, outdoor mall, or military base in a coalition country.
No attacks are being planned outdoors in Sharkland.
The Steeler and Bronco groups use only their own operatives, never employing locals.
There are reports that spent nuclear fuel is missing in Troutland.
A new military base is being built in Bassland.
Troutland is in the process of deploying more troops to protect its military bases.
The Raven, Steeler, and Raider groups are capable of attacking year round.
The Raven and Steeler groups prefer to attack at night.
The Steeler, Raider, and Panther groups are known to attack at any time of the day.
The Charger group has a history of attacking domestic assets.
Caches of chemicals have recently been found in Troutland, Perchland, and Salmonland.
The Panther and Charger group operatives have entered Salmonland.
There are fewer attacks in the heat of Summer (June and July).
The target is in a coalition country (Troutland, Perchland, Salmonland, Bassland or Sharkland).
No attacks are being planned outdoors in Perchland, Salmonland, and Bassland.
An attack is being planned for the last month of the year.
The Panther group has close ties with local media.
No traces of members from the Panther group have been found in Sharkland.
The Raven group needs time to regroup.
The Raven group is recruiting locals - intentions unknown.
Train Stations in Bassland were recently attacked and evidence of more attacks has been found.
The largest Stock Market in Bassland has 4 machine gun emplacements on its roof.
Military bases in Sharkland now have multiple checkpoints.
The Panther and Titan groups use very small cells.
There are more attacks on Tuesdays.
Reports from the Steeler group indicate standard levels of activity.
Bloggers are discussing the increase in flash mobs at shopping malls in Salmonland, Bassland, and Sharkland.
Reports from Salmonland, Bassland, and Sharkland indicate surveillance ongoing at public gathering places.
Attacking buildings when there are many people present increases casualties.
The Panther group is not involved.
The Panther group does not target shopping malls.
Troutland and Perchland have only outdoor malls.
There will be a chemical attack at 10:00 AM.
There is a lot of activity involving the Bronco group.
Members of the Raider group have been visiting Perchland.
The Panther group has been known to use chemical or biological agents.
The outdoor malls in Bassland are very popular.
All the military bases in Perchland are heavily protected.
There is no new information about Raven group operations in Bassland.
Perchland is land locked.
Locals in Sharkland are being recruited.
The Turtle lost his right eye in an accident.
The Bronco group does not attack on its Sabbath.
Members of the Charger, Titan, Steeler, Raider, and Bronco groups have experience with chemical weapons.
The shopping malls in the coalition area are not well defended.
Charger and Titan group members have entered Perchland and Salmonland.
The Panther, Charger, Titan, and Raven groups prefer to attack in daylight.


Add new person to Database
{% csrf_token %}
Person's name :
The image should only contain one person.
Image verification, please wait ..


--- layout: post title: Awesomeness!! date: 2008-07-14 14:30:00.000000000 +10:00 type: post published: true status: publish categories: [] tags: - movies meta: lj_itemid: '29' lj_permalink: http://jus4kix.livejournal.com/7427.html lj_current_location: Bangalore lj_current_mood: cheerful author: login: ajaysusarla email<EMAIL_ADDRESS>display_name: partha first_name: '' last_name: '' ---
I watched Kung Fu Panda the other day, and it sure an hour and half of joyride and well written script and amazing one-liners.
The movie begins with this serious commentary about a legendary warrior - and you get to hear lines like "It is said that his enemies would go blind from over-exposure to pure awesomeness!"
It is more of lines like these, that kept me glued till the end. The lead character Po the Panda (voiced by Jack Black), is quite impressively done, And keeps one amused with its on-screen antics. Po, in every frame will inadvertently remind you Jack Black.
Check out the trailer here.
I would suggest that you actually watch this movie, if you haven't already.
I am watching it again, for sure.


Four years experienced developer with a demonstrated history of working in the information technologies and services industries. Skilled in Ruby, Python, Java, Git, Docker and GNU/Linux. Strong international engineering with a Level 6 focused in Computer Programming from Rathmines College - Dublin and two years working for the World Economic Forum.
Highly motivated and enthusiast: I obtained a Bachelor's degree on top of my full-time job and pursuing to a Master's degree.
I am an autodidact and also a OpenSource enthusiast, I like to begin all kind of projects for fun.
Development of a satellite simulation with Java. The purpose of this simulation is to send production-like data to the testing environment.
Data mining and natural language processing with machine learning for the PREVISION project of Europol.
Build micro-services API and their tests with agility and Ruby, peer-reviewed on GitHub and I was responsible of the deployments in production on Heroku (DevOps approach).
On direct contact with the client and teams around the world through Jira and Confluence.
Regularly traveling to the client offices based in Geneva for the organization of international events.
Website management (OVH, Gandi)
Build a CRM with Ruby on Rails
The aim of the Computer Science for Aerospace (CSA) Master Degree is to educate future computer scientists and managers, within an international working environment, selecting talented students from all around the world. It aims to provide specialist high-level core knowledge and a unique specialty in computer science for aerospace, encompassing both hardware and software skills.
Road trips (> 1 month): USA 2016, China 2017, Caucasus 2018, South America 2019
Raspberry Pi & Arduino player (NAS, CCTV, Server, Robotic, Retro-gaming…)
Daily technology and science surveillance
Pour moi, la préservation de l’environnement est importante. J'héberge mon site chez un hébergeur écologique.


Hamilton feels 2019 has been his best performing year
by Joseph TyrrellBeing a six-time World Champion Lewis Hamilton has his standards set very high, but even he thinks 2019 could be his best season as he looks to round out the season in style.
Hamilton has won ten races this season and wrapped up the Drivers' Championship with a P2 at the United States Grand Prix, behind Valtteri Bottas. Hamilton still has a chance to make his title victory even more impressive with the Brazilian and Abu Dhabi Grands Prix left, races he won in 2018.
Despite looking unbeatable it hasn't always been the easiest season for Mercedes. However, the Brit insists 2019 could be his best performing year.
“I tried to make sure that I’ve started the season as I finished last year and I think that’s just stayed through the season,” said Hamilton as quoted by Motorsport.
“I’ve been very consistent in qualifying. I’ve not had particularly spectacular pole positions that perhaps I did last year, but it’s been second row the majority of the time.
“Apart from Hockenheim [where Hamilton went off while in control of the rain-hit race] – but I’ll give myself a pass for that weekend because I wasn’t really 100% – I think it’s been the best performing year."


Curriculum Vitae
General Information
| Full Name | Rajiv Sarvepalli |
| Contact |<EMAIL_ADDRESS>|
| Languages | English (native) |
Research Areas
- I have experience in the deep learning and cybersecurity fields through internships and research assistant positions.
- I am interested in both Computer Vision and Natural Language Processing, especially in the intersection of the two such as Visual Q & A, image retrieval, and image captioning. I also have a broader interest in machine learning having experimented with some statistical and graphical models.
- Generally, I have done projects in areas of computer vision, natural language processing, and machine learning and hope to continue to explore more.
Education
-
2018 - 2021
University of Virginia – B.S. in Computer Science
- GPA: 3.921 (4.0 scale)
- Major GPA: 3.976 (4.0 scale)
- Expected graduation May 2021
Relevant Work Experience
-
Summer 2020
Machine Learning Intern at Expedition Technology
- Researched, assessed, and adapted state of the art object detectors using PyTorch to detect small objects in an Agile team.
- Deployed Docker containers to AWS P2 instances through Jenkins to train networks.
- Constructed TensorBoard live feeds to monitor validation losses and observe qualitative results quickening the model evaluation process.
- Performed exploration of reinforcement learning libraries to find the best library with priorities of concision and readability.
-
2019 - 2021
Data Anyalst Intern at NetForecast Inc
- Developed and documented data management and collection software to improve the structure and optimization
- Designed scheduled tasks using AWS to perform constant data updates improving data quality.
- Analyzed data from traceroutes and pings to predict router locations using support vector regression and force simulations.
- Designed structure to follow object oriented programming principles and design patterns.
Research Experience
-
2019 - 2021
Undergraduate Research Assistant at University of Virginia
- Advised by Dr. Yonghwi Kwon
- Designed tool to analyze Docker container on Docker Hub collecting data for security analysis of Docker containers.
- Built an Active Directory user environment through PowerShell and ESXi scripting mimicking a corporate environment.
- Assembled information about how attacks are executed by running red-team emulators collecting usable data.
- Preprocessed data with Python data science libraries to prepare for anomaly detection and classification tasks.
-
Summer 2017
Research Assistant at George Mason University
- Analyzed and organized data from IOT devices utilizing machine learning techniques to increase accuracy of models by 5\% and leveraged python machine learning libraries.
- Implemented time series motif discovery algorithms in Python using NumPy and SciPy.
- Created one of the first implementations of a novel matrix profile algorithm in Python from a publication.
Honors and Awards
-
Research
- Member of Undergraduate Research Initiative (2019 - 2021)
-
Academic
- Intermediate Honors (2020)
- Dean's List (2018, 2019)
Teaching Experience
-
Fall 2020
Teaching Assistant for Computer Architecture
- Provided weekly office hours for a Computer Architecture class with more than 300 students.
- Taught by Prof. Charles Reiss.
- Ran weekly laboratory sessions providing an overview and answering questions.
- Examined instructional material for understandability and clarity through reviewing assignment's overview and instructions.
Computer skills
- ○ Programming languages: Python, R, Prolog, C, Java, OCaml.
- ○ Data Structures and Algorithms: Familiarity with concepts used in algorithmic competitions and machine learning research.
- ○ Libraries: PyTorch, TensorFlow, Stable Baselines, NumPy, SciPy, Pandas, Matplotlib, Scikit-learn.
- ○ Developer Tools: Git, Docker, AWS, VS Code, MySQL, IntelliJ.
Technical Projects
-
Check out my projects page for more information.
Image-Caption Geolocation for Privacy
- Used machine learning to examine the potential personal information in a social media post (image & text).
- Leveraged name entity recognition to recognize potential information leaks within a post’s text.
- Developed CNN for image geolocation for a small subset of locations achieving high precision and recall.
- Made geolocation into a hierarchical classification problem through hierarchical clustering of GPS coordinates.
- Demo Video
-
Mocking SQLAlchemy
- Created a python library for mocking SQLAlchemy that has around 16,000 downloads and 12 GitHub stars.
- Established modern CI/CD pipelines using GitHub Actions.
- Documentation and source code are publicly available.
-
Docker Scraper
- Scrapes Docker Hub for Docker images of webservers of similar types.
- Uses variants of Docker containers to do analysis of popularity and software package version numbers.
- Observed if people were updating their Docker containers with newer software versions to see if any vulnerabilities were left enabling data collection for security analysis of Docker containers.
Unpublished Papers
-
Anonymous Social Media Privacy
- Senior year thesis on understanding the constraints of privacy within anonymous social media.
- Explored the sociotechnical aspect of privacy: realizing the connection between the technical and social aspects of privacy.
- Examined the impact of technology in changing perspective of privacy: from the individual to collective.
Relevant Coursework
- Graduate Machine Learning
- Machine Learning
- Computer Vision and Language
- Statistical Learning and Graphical Models
- From Data to Knowledge
- Probability
Personal Interests
- I enjoy soccer, traveling, and video games.


Ricky Gervais Returning to Host the 2020 Golden Globe Awards
LOS ANGELES (AP) — Look out Hollywood, Ricky Gervais is returning to host the Golden Globe Awards.
by Breitbart NewsGervais memorably hosted the Globes from 2010 to 2012, skewering many of the attendees with irreverent jokes. He also lampooned the organization that hosts the Globes, the Hollywood Foreign Press Association.
It will be the fifth time Gervais emcees the ceremony; he also hosted in 2016. He said in a news release that organizers made him an offer he couldn’t refuse.
The 77th annual Golden Globe Awards, which honor achievements in film and television, will be held at the Beverly Hilton Hotel on Jan. 5 and aired live on NBC.
The HFPA has previously announced it will bestow its Cecil B. DeMille Award on Tom Hanks, and give Ellen DeGeneres its Carol Burnett Award during the show.


Scientific studies have shown over and over again that some types of background noise, like those found in an open plan office, can decrease your concentration, which makes it harder for you to process and memorize information. Interruptions by colleagues and constant noise can also cause you stress, resulting in high blood pressure and other unpleasant symptoms. As a result, people are less satisfied with their jobs and experience decreased motivation, leading to a steep decrease in creativity, collaboration, productivity, and an increase in sick leave.
Well here at the Rubber Room, we don’t have any of that! Life working in the Rubber Room is utopia!
Here are some reasons why The Rubber Room is the best place to work:
- View - Best view for a peaceful environment
- Quit - less people; less chatter
- Space - No bathroom; no disruptions
View
You now have unlimited access to Safari’s huge trove of books, videos, and training from 200+ professional publishers in the fields of tech, business, design, and more—as well as live online training, Learning Paths, advance copies of books, exclusive access to O’Reilly conference videos, and interactive tutorials.
Quiet
You now have unlimited access to Safari’s huge trove of books, videos, and training from 200+ professional publishers in the fields of tech, business, design, and more—as well as live online training, Learning Paths, advance copies of books, exclusive access to O’Reilly conference videos, and interactive tutorials.
Space
You now have unlimited access to Safari’s huge trove of books, videos, and training from 200+ professional publishers in the fields of tech, business, design, and more—as well as live online training, Learning Paths, advance copies of books, exclusive access to O’Reilly conference videos, and interactive tutorials.


Reports cases where method call accepts a non-trivial expression, and there's an equivalent method,
which accepts lambda instead. Converting an expression to lambda ensures that expression will not be evaluated
if it happens to be unused inside the method. E.g. optional.orElse(createDefaultValue()) could be converted
to optional.orElseGet(this::createDefaultValue).
New in 2018.1


Designed for the future
Introducing an extensible editor
Blogr features an exceedingly intuitive interface which lets you focus on one thing: creating content. The editor supports management of multiple blogs and allows easy manipulation of embeds such as images, videos, and Markdown. Extensibility with plugins and themes provide easy ways to add functionality or change the looks of a blog.
Robust content management
Flexible content management enables users to easily move through posts. Increase the usability of your blog by adding customized categories, sections, format, or flow. With this functionality, you’re in full control.
State of the Art Infrastructure
With reliability and speed in mind, worldwide data centers provide the backbone for ultra-fast connectivity. This ensures your site will load instantly, no matter where your readers are, keeping your site competitive.
Free, open, simple
Blogr is a free and open source application backed by a large community of helpful developers. It supports features such as code syntax highlighting, RSS feeds, social media integration, third-party commenting tools, and works seamlessly with Google Analytics. The architecture is clean and is relatively easy to learn.
Powerful tooling
Batteries included. We built a simple and straightforward CLI tool that makes customization and deployment a breeze, but capable of producing even the most complicated sites.


- Creating/Connecting to a DArcMail database file
- Loading data into a DArcMail database
- Deleting data from a DArcMail database
- Exporting Message Subsets from a DArcMail database
- Browsing data in a DArcMail database
- Account directory
- Folder
- Message content storage


{% extends "base.html" %} {% load crispy_forms_tags %} {% block content %}
We are studying questions that computing instructors would like computing education researchers to investigate. In this survey, you will be shown a total of 40 questions and we would like you to rank each on a scale ranging from 'very unimportant' to 'very important'. These questions will be divided into 2 sets, with each set shown on a separate page of the survey.
Your participation should take about 15 minutes and we would like to enter your name into a random draw for $250 USD as a thank you. Your odds of winning will be at least 1 in 200. We would also be happy to send you the results of the research once it is completed. We do not believe that there are any risks to you as a participant.


For quantitative continuous data, your wedges of the pie chart will correspond to ranges of values instead of individual values. For example, here is the data from Table 5.6.10, with relative frequencies:


White and black
Yellow and black
Black and blue
Black and peach
Blue and cream
COLOUR PREVIEW
123
1
2
3
Name
=
1
2
3
4
5
6
7
8
9
⌫
0
Enter
Start


CCS student authors are in bold. Publications should appear in this list only if the student’s contribution to the publication was made as an undergrad. Work that started while the student was an undergrad and continued into the 5-year combined BS/MS program may be included, but not work done as a Ph.D. student or after graduating from UCSB.
Ethan Epperly and Ryan Sills. “Comparison of Continuum and Cross-Core Theories of Dynamic Strain Aging.” Journal of Mechanics and Physics of Solids, 2020, doi:https://doi.org/10.1016/j.jmps.2020.103944
Ethan Epperly and Ryan Sills. “Transient Solute Drag and Strain Aging of Dislocations.” Acta Materialia, 2020, To Appear, doi:https://doi.org/10.1016/j.actamat.2020.03.031
Lia Yeh, Lincoln Satterthwaite, and Dave Patterson. “Automated, Context-Free Assignment of Asymmetric Rotor Microwave Spectra.” The Journal of Chemical Physics, vol. 150, no. 20, 2019, p. 204122., doi:https://dx.doi.org/10.1063/1.5085794
Prince Zizhuang Wang, William Yang Wang.
Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling.
Annual Conference of the North American Chapter of the Association for Computational Linguistics, Oral, (NAACL 2019).
pdf: https://arxiv.org/abs/1904.02399 code: https://github.com/kingofspace0wzz/wae-rnf-lm
Mai Elsherief, Vivek Kulkarni, Dana Nguyen, William Yang Wang, and Elizabeth Belding. Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media. International AAAI Conference on Web and Social Media (ICWSM) 2018, June 2018, Stanford, California.
Mai Elsherief, Shirin Nilizadeh, Dana Nguyen, Giovanni Vigna, and Elizabeth Belding. Peer to Peer Hate: Hate Speech Instigators and Their Targets. International AAAI Conference on Web and Social Media (ICWSM) 2018, June 2018, Stanford, California.
Thomas Schibler and Subhash Suri.
K-Dominance in Multidimensional Data: Theory and Applications.
25th Annual European Symposium on Algorithms (ESA 2017),
65:1--65:13.
Leibniz International Proceedings in Informatics (LIPIcs),
http://drops.dagstuhl.de/opus/volltexte/2017/7840
Mai Elsherief, Elizabeth Belding and Dana Nguyen. #NotOkay: Understanding Gender-based Violence in Social Media
International AAAI Conference on Web and Social Media (ICWSM) 2017, May 2017, Montreal, Canada.
Joseph McMahan, Michael Christensen, Lawton Nichols, Jared Roesch, Sung-Yee Guo, Ben Hardekopf, and Timothy Sherwood. 2017. An Architecture Supporting Formal and Compositional Binary Analysis. In Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '17). ACM, New York, NY, USA, 177-191. DOI: https://doi.org/10.1145/3037697.3037733 2018 IEEE Micro "Top Pick" Award
C. Krintz, R. Wolski, N. Golubovic, B. Lampel, V. Kulkarni, B. Sethuramasamyraja, B. Roberts, and B. Liu. SmartFarm: Improving Agriculture Sustainability Using Modern Information Technology.
(PDF),
KDD 2016 Workshop on Data Science for Food, Energy, and Water (DSFEW), August, 2016
Daniel Spokoyny, Jeremy Irvin and Fermin Moscoso del Prado.
Explicit Causal Connections between the Acquisition of Linguistic Tiers: Evidence from Dynamical Systems Modeling.
Proceedings of the 7th Workshop on Cognitive Aspects of Computational Language Learning. August 2016, Berlin.
SOK: (State of) The Art of War: Offensive Techniques in Binary Analysis. Y. Shoshitaishvili, R. Wang, C. Salls, N. D. Stephens, M. Polino, A. Dutcher, J. Grosen, S. Feng, C. Hauser, C. Kruegel, G. Vigna. Proceedings of the IEEE Symposium on Security and Privacy (SSP 2016). PDF.
Driller: Augmenting Fuzzing Through Selective Symbolic ExecutionN. D. Stephens, J. Grosen, C. Salls, A. Dutcher, R. Wang, J. Corbetta, Y. Shoshitaishvili, C. Kruegel, G. Vigna. Proceedings of the ISOC Network and Distributed System Security Symposium (NDSS 2016).
PDF
Wei Dai. Randomness Extractors - An Exposition. Rose-Hulman Undergraduate Math
Journal (pdf). Vol. 17, Issue 1, 2016.
Kyle Dewey, Jared Roesch, and Ben Hardekopf. 2015. Fuzzing the Rust Typechecker Using CLP (T). In Proceedings of the 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE) (ASE '15). IEEE Computer Society, Washington, DC, USA, 482-493. DOI=http://dx.doi.org/10.1109/ASE.2015.65
Kyle Dewey, Jared Roesch, and Ben Hardekopf. 2014. Language fuzzing using constraint logic programming. In Proceedings of the 29th ACM/IEEE international conference on Automated software engineering (ASE '14). ACM, New York, NY, USA, 725-730. DOI=
http://dx.doi.org/10.1145/2642937.2642963
Ben Hardekopf, Ben Wiedermann, Berkeley Churchill, and Vineeth Kashyap. 2014. Widening for Control-Flow. In Proceedings of the 15th International Conference on Verification, Model Checking, and Abstract Interpretation - Volume 8318 (VMCAI 2014), Kenneth Mcmillan and Xavier Rival (Eds.), Vol. 8318. Springer-Verlag New York, Inc., New York, NY, USA, 472-491.
DOI:
http://dx.doi.org/10.1007/978-3-642-54013-4_26
Vineeth Kashyap, Kyle Dewey, Ethan A. Kuefner, John Wagner, Kevin Gibbons, John Sarracino, Ben Wiedermann, and Ben Hardekopf. 2014. JSAI: a static analysis platform for JavaScript. In Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE 2014). ACM, New York, NY, USA, 121-132.
DOI:
http://dx.doi.org/10.1145/2635868.2635904
Xiaohan Zhao, Adelbert Chang, Atish Das Sarma, Haitao Zheng, and Ben Y. Zhao. 2013. On the embeddability of random walk distances. Proc. VLDB Endow. 6, 14 (September 2013), 1690-1701. DOI=
http://dx.doi.org/10.14778/2556549.2556554
Gang Wang, Tristan Konolige, Christo Wilson, Xiao Wang, Haitao Zheng, and Ben Y. Zhao. 2013. You are how you click: clickstream analysis for Sybil detection. In Proceedings of the 22nd USENIX conference on Security (SEC'13). USENIX Association, Berkeley, CA, USA, 241-256. Metadata at ACM Digital Library, PDF
Madhukar N. Kedlaya, Jared Roesch, Behnam Robatmili, Mehrdad Reshadi, and Ben Hardekopf. 2013. Improved type specialization for dynamic scripting languages. In Proceedings of the 9th symposium on Dynamic languages (DLS '13). ACM, New York, NY, USA, 37-48.
DOI=
http://dx.doi.org/10.1145/2508168.2508177
Vineeth Kashyap, John Sarracino, John Wagner, Ben Wiedermann, and Ben Hardekopf. 2013. Type refinement for static analysis of JavaScript. In Proceedings of the 9th symposium on Dynamic languages (DLS '13). ACM, New York, NY, USA, 17-26. DOI=
http://dx.doi.org/10.1145/2508168.2508175
Diana Franklin, Phillip Conrad, Bryce Boe, Katy Nilsen, Charlotte Hill, Michelle Len, Greg Dreschler, Gerardo Aldana, Paulo Almeida-Tanaka,
Brynn Kiefer, Chelsea Laird, Felicia Lopez, Christine Pham, Jessica Suarez, and Robert Waite. 2013. Assessment of computer science learning in a scratch-based outreach program. In Proceeding of the 44th ACM technical symposium on Computer science education (SIGCSE '13). ACM, New York, NY, USA, 371-376.
DOI:
http://dx.doi.org/10.1145/2445196.2445304
B. R. Goldsmith, E. D. Sanderson, D. Bean, and B. Peters. Isolated catalyst sites on amorphous supports: a systematic algorithm for understanding heterogeneities in structure and reactivity. J. Chem. Phys. 138, 204105 (2013).
Adam Lugowski, David Alber, Aydm Buluç, John R. Gilbert, Steve Reinhardt, Yun Teng, Andrew Waranis. A Flexible Open-Source Toolbox for Scalable Complex Graph Analysis. Proceedings of the 2012 SIAM International Conference on Data Mining. DOI=
http://dx.doi.org/10.1137/1.9781611972825.80
Berkeley R. Churchill and Edmund A. Lamagna. 2011. Summing symbols in mutual recurrences. In Proceedings of the 17th annual international conference on Computing and combinatorics (COCOON'11), Bin Fu and Ding-Zhu Du (Eds.). Springer-Verlag, Berlin, Heidelberg, 531-542. DOI=
http://dx.doi.org/10.1007/978-3-642-22685-4_46
Kyle Klein and Subhash Suri. Multiagent
Pursuit Evasion, or Playing Kabaddi.
International Workshop on Algorithmic Foundations of Robotics (WAFR),
Singapore, Dec 13-15, 2010.
Kyle Klein and Subhash Suri. Robot Kabaddi.
22nd Canadian Conference on
Computational Geometry (CCCG), Winnipeg, August 9-11, 2010.
Murat Karaorman and Jay Freeman. 2005. jMonitor: Java Runtime Event Specification and Monitoring Library. Electron. Notes Theor. Comput. Sci. 113 (January 2005), 181-200. DOI=
http://dx.doi.org/10.1016/j.entcs.2004.01.027
.


Money Play. How should Red play 32?
pips Red=134 White=161
(CorrectAnswer= 0/0, ErrorScore= 0)
I played 6/1 here which initially XG didn’t like – it doesn’t like dead checkers. It preferred 8/5, 6/4, trying to make the 4-pt.
However, that play leaves an ungainly structure. On roll-out the two plays come with identical equities so for once you can take your choice.
Any play that includes 24/21 is a blunder.
However, that play leaves an ungainly structure. On roll-out the two plays come with identical equities so for once you can take your choice.
Any play that includes 24/21 is a blunder.
1. Cubeful 2-ply 8/5 6/4 Eq.: +0.518 0.626 0.207 0.012 - 0.374 0.105 0.004 2. Cubeful 2-ply 6/1 Eq.: +0.471 (-0.046) 0.625 0.191 0.010 - 0.375 0.096 0.002 3. Cubeful 2-ply 24/21 8/6 Eq.: +0.453 (-0.065) 0.618 0.191 0.013 - 0.382 0.102 0.002 4. Cubeful 2-ply 24/21 6/4 Eq.: +0.431 (-0.086) 0.610 0.210 0.014 - 0.390 0.128 0.004 5. Cubeful 2-ply 6/3 5/3 Eq.: +0.419 (-0.099) 0.605 0.198 0.011 - 0.395 0.118 0.004


Upcoming features
Better font
Boss health bar
Repair powerup
Better animations/tweens
Leaderboard
Burst shots
Music
Enemies shouldn't shoot backward
Bigger bullets/bigger sprites
Super ability


Without a China trade deal, the US will hike tariffs: Trump
WASHINGTON: The United States would raise tariffs on Chinese imports if no deal is reached with Beijing to end a trade war, US President Donald Trump said on Tuesday (Nov 19), threatening an escalation of the spat that has damaged economic growth worldwide.
Speaking at a cabinet meeting at the White House, Trump said he had a good relationship with China, noting that China was "moving along". However, he said China would have to make a deal "I like".
"If we don't make a deal with China, I'll just raise the tariffs even higher," he told a room filled with senior US officials.
The United States and China have been locked in successive waves of tit-for-tat tariffs that have roiled financial markets and threatened to drag growth in the global economy to its lowest rate since the 2007-2008 financial crisis.
Hopes were high that a partial trade deal could be signed at a summit in Santiago, Chile that was scheduled for mid-November. The summit was cancelled amid unrest in Chile and a path forward for a deal remains unclear.
Sticking points include how and when to reduce tariffs and how much US agricultural products China would commit to buy.
White House economic adviser Larry Kudlow said last week that the two countries were getting close to an agreement to end the 16-month-long trade war, but he gave no further details on the timing of a possible deal.
Still, Chinese state media outlet Xinhua said "constructive talks" were held by phone on Saturday between China's Vice Premier Liu He, US trade representative Robert Lighthizer and Treasury Secretary Steven Mnuchin.


{{#def.header}}
Thanks for confirming your subscription. You will receive email updates until you opt out.


Distribution of Quality Attributes
Metric Values in Sunburst Chart
Metric Values by Packages
Metric Values in Treemap Chart
Package Dependencies


Compiler-based execution of SQL
Table of Contents
Krikellas – holistic query evaluation 3
Hekaton (SQL server in memory db) 4
Apache Spark (optimizer is called Catalyst) 4
This is a short survey of systems which have been developed for compiler-based execution of SQL queries.
In database systems, two approaches have been developed for transforming declarative SQL queries to imperative execution.
Interpretor-based model :
Almost all commercial DBMSes implement a
Volcano Iterator model for query execution. In the early versions of
this model, one tuple at a time was passed through an entire tree of
iterators. This model was seen to be inefficient. Later versions
of this model use a “block”-based approach and process a set of
tuples at a time.
Iterator models can be pull (synchronous) or push (synchronous).
Other variants have included MonetDB and VectorWise which do vector operations that fit into the CPU cache.
Compiler-based model:
With the coming of large memory systems and in-memory databases, the inefficiencies of the previous model have become more exposed. The iterator model prevents tight loop executions, and is unable to exploit the data cache or reuse CPU registers.
This spurs the move to compiler-based systems which can enable data-centric execution.
Just as in programming languages, a compiler does the following transformations
high level Language -> AST -> Intermediate language -> Machine code
Similarly, an SQL query can be transformed as:
SQL -> AST -> Intermediate language -> Final code -> Compile/Load and run
A compiler-based system performs the following transformations
SQL -> AST -> Intermediate language -> Java/C/C++/LLVM assembly which is then loaded and executed.
(microsoft research, univ of cambridge)
LINQ (Language integrated query) is a declarative extension to C#. The Steno system takes a declarative query and generates a C# class for it which is loaded and executed by the system.
Steno does two major optimizations:
Iterator fusion : For example, it can combine a SELECT and WHERE operator into a “for loop”.
Transform nested queries into nested loops
Transformation steps taken:
Given a chain of operators, it emits symbols of QUIL (query intermediate language).
From the sequence of symbols, it uses a FSM to generate a C# class using the CodeDOM library.
Compile and load this query for execution.
Before execution, it resolves any object references in the query by using the reflection API in C#.
QUIL
The
QUIL language has six symbols (SRC, TRANS, PRED, SINK, RET, AGGR).
The sequence of symbols starts from SRC and ends in RET.
SRC signifies the start of execution and represents a table or index scan which creates a list for processing.
TRANS, PRED and SINK transform one list to another.
RET returns the final list.
How is code generated ?
On a SRC symbol, it generates a “for loop” based on the symbol arguments. This 'for loop' is represented as a linked list of 3 nodes (precursor, loop body, and post-operation).
On a TRANS symbol, it generates element-wise operations inside the loop body
On a AGGR symbol, it reduces the list to a scalar value
On a SINK symbol (i.e. a “group by” or “order by” clause). For a “group by”, it creates a new list from the old using an intermediate hash table or tree. For “order by”, it invokes a C# sorting function
On a PRED symbol, it generates an “if clause”.
Example:
If the query was “SELECT max(a) from <table1>”
then the sequence of symbols will be “{SRC <table1>, AGGR <a>, SINK }”
and the code generated will be :
foreach (elem in table1)
{
max_a = max(elem, max_a)
}
Distributed query
To generate a distributed query,
given a sequence of QUIL symbols { SRC, TRANS, AGGR, RET}
Steno/DryadLINQ inserts intermediate symbols which expand the query to all nodes and aggregate the results (kind of like a map-reduce)
SRC -> SRC (node1) -> TRANS(node1) -> AGGR(node1) -> AGGR -> RET
-> SRC (node2) -> TRANS(node2) -> AGGR(node2) ->
(univ of edinburgh)
It takes the output of the query optimizer, which is a topologically sorted list of operations and applies them over pre-defined code templates, parametrized by machine architecture, and uses it to generate code.
The time for generating the code was found to be about 25 ms. The time for compiling optimized code was about 400-600 ms.
Challenges they identified:
identify common code templates
how to interconnect different operators now that they have no common API
how to verify correctness of the generated code.
(Tum.de)
This is positioned as a hybrid OLTP-OLAP database ( academic research )
First they tried to generate C++ code from an SQL query. Later they switched to generating LLVM assembly code, which they found was equally manageable and efficient. Compiling the LLVM assembly to the final machine code is faster than the same for C++.
They use LLVM code only to replace the tight inner loops which occur during query execution.
They realized that the type systems and expression semantics of T-SQL and C are very different.
T-SQL includes many data types such as date/time types and fixed precision numeric types that have no corresponding C data types.
In addition, T-SQL supports NULLs while C does not.
Finally, T-SQL raises errors for arithmetic expression evaluation failures such as overflow and division by zero while C either silently returns a wrong result or throws an OS exception that must be translated into an appropriate T-SQL error.
That is why they introduced an additional step in code generation which generates a “Pure Imperative Tree” from the “Mixed Abstract tree”.
Steps
Parser
Algebraic compiler : They keep a map algebra of about 70 simplification rules which get applied to a query.
Code generator : Generate C++ code.
Other query optimizers employ a domain-specific language to define rules and write a custom compiler to generate code. By contrast, Catalyst exploits Scala language features such as pattern-matching and quasiquotes for the same purposes. It uses the Java compiler to gnerate bytecode which will execute on Spark nodes.
It does both cost-based and rule-based optimization. (Cost-based means it chooses the plan with the least cost; rule-based means it applies pattern matching rules to transform the query execution tree).
Steps
Convert AST to logical plan
Analyzing a logical plan to resolve variable references (i.e. lookup the schema)
Logical plan optimization,
Physical query execution plan
Generate Java bytecode using Scala quasiquotes feature
In Scala, when you prefix a string with a “q” (i.e. val mytree = q”this is a tree”), the Scala compiler internally stores the variable “mytree” as a Syntax Tree rather than a string.
http://docs.scala-lang.org/overviews/quasiquotes/intro.html
Now you can write Scala code to compare trees or transform them. Catalyst uses this feature to store query execution trees and generate Java bytecode from them.
https://databricks.com/blog/2015/04/13/deep-dive-into-spark-sqls-catalyst-optimizer.html
Tables are stored in columnar format and bytecode for vectorized primitives is generated at runtime.
They use the unsafe Java library (sun.misc.unsafe) to do direct in-memory optimizations on vectors. Memory allocated via “unsafe” is not under GC control and not constrained by JVM heap size.
http://www.slideshare.net/Hadoop_Summit/t-435p210-achoiv2
Produces C++ code which is bundled into a shared library.
They run the Vitesse JIT engine after a query plan is created.
They got 2X performance by applying LLVM to compile the expressions found within the query, while the Plan tree was still interpreted using the iterator model.
They got 8X performance by compiling entire query into one JIT procedure. The query nodes got inlined, CPU registers were reused and code had tight inner loops.
They obtained 108X performance by running on multi-core and letting each core work on a distinct data set.
They obtained 180X performance by using a columnar data store with LZ4 and Delta compression.
Slides here: http://goo.gl/Mtg2W6
It dynamically compiles certain portions of the query plan to Java byte code.
See the ExpressionCompiler class which in turn uses PageProcessorCompiler and CursorProcessorCompiler
This class is invoked from the LocalExecutionPlanner
It uses LLVM to compile stored procedures into LLVM IR (intermediate representation) language.
http://llvm.org/devmtg/2013-11/slides/Wanderman-Milne-Cloudera.pdf
D. G. Murray, M. Isard, and Y. Yu. Steno: Automatic Optimization of Declarative Queries. In PLDI, 2011.
K. Krikellas, S. D. Viglas, and M. Cintra. Generating code for holistic query evaluation. In ICDE, 2010.
T. Neumann. Efficiently compiling efficient query plans for modern hardware. Proc. VLDB Endow., 4(9), 2011.
C. Diaconu, C. Freedman, E. Ismert et al., “Hekaton: Sql server’s memory-optimized OLTP engine,” in SIGMOD ’13, 2013.
Armbrust, et al . Spark SQL: Relational Data Processing in Spark. SIGMOD 2015 http://people.csail.mit.edu/matei/papers/2015/sigmod_spark_sql.pdf


|
LabBot
|
A class for displaying data as a moving bar indicator. More...
#import <DRHDataOutputBarView.h>
Instance Methods | |
| (void) | - setCalibratedValue: |
| (void) | - setCalibratedTarget: |
| (void) | - twoPointLinearcalibrationUsing:And: |
Public Attributes | |
| NSInteger const | DRHDataOutputOrientationUp |
| NSInteger const | DRHDataOutputOrientationDown |
| NSInteger const | DRHDataOutputOrientationLeft |
| NSInteger const | DRHDataOutputOrientationRight |
Properties | |
| CGFloat | value |
| The value of the bar which relative to the frame. E.g, 1.0 would specify the bar is full, 0.5 would specificy that the bar is half full. | |
| CGFloat | target |
The position of the target line relative to the frame. E.g, 0.75 would position the taget 3/4 of the way long the bar. Set to zero or less to hide. Default is 0.0 . | |
| CGFloat | targetLineWidth |
The width of the target line. Default is 3.0 . | |
| NSInteger | orientation |
Indicates the orientation of the bar. Values are set by DRHDataOutputOrientation constants. The default is DRHDataOutputOrientationUp . | |
| CGFloat | gain |
Used to calibrate value and target if they are set using the setCalibratedValue: and setCalibratedTarget setter methods. This property is set to 1.0 by default. | |
| CGFloat | offset |
Used to calibrate value and target if they are set using the setCalibratedValue: and setCalibratedTarget setter methods. This property is set to 0.0 by default. | |
| Properties inherited from DRHDataOutputView | |
| NSColor * | fgColour |
| The draw colour of the data output. Deafult is. More... | |
| NSColor * | bgColour |
The draw colour of the data output's background. Deafult is nil . | |
| NSColor * | altColour |
| The alternate colour of drawing the data used by some subclasses. Deafult is. More... | |
| BOOL | alternate |
If YES uses altColour instead of fgColour . Default is NO . | |
A class for displaying data as a moving bar indicator.
This class draws a bar, and optionally a target line, that are specified by class properties.
| - (void) setCalibratedTarget: | (CGFloat) | newTarget |
| - (void) setCalibratedValue: | (CGFloat) | newValue |
| - (void) twoPointLinearcalibrationUsing: | (NSPoint) | firstPoint | |
| And: | (NSPoint) | secondPoint | |
Sets the gain
and offset
properties of the receiver based on a two-point linear calibration between two NSPoint
values.
| firstPoint | The x-value of this point is the raw uncalibrated value, the y-value is the calibrated output between 0.0 and 1.0 . The y-value of this point should be less than the y-value of secondPoint . |
| secondPoint | The x-value of this point is the raw uncalibrated value, the y-value is the calibrated output between 0.0 and 1.0 . The y-value of this point should be more than the y-value of firstPoint . |
| - (NSInteger const) DRHDataOutputOrientationDown |
When the orientation
property is set the bar will ber vertical and 1.0 represents the bottom.
| - (NSInteger const) DRHDataOutputOrientationLeft |
When the orientation
property is set the bar will ber horizontal and 1.0 represents the left.
| - (NSInteger const) DRHDataOutputOrientationRight |
When the orientation
property is set the bar will ber horizontal and 1.0 represents the right.
| - (NSInteger const) DRHDataOutputOrientationUp |
When the orientation
property is set the bar will ber vertical and 1.0 represents the top.


Controls
| Left Click | View Cube Data |
|---|---|
| [W],[A],[S],[D] | Walk around |
| [Space] | Jump |
| Hold [Space] | Fly Up |
| Hold [Shift] | Fly Down |
| [Tab] | Screenshot |
| [Escape] | Release Pointer Lock |
| Use Chrome 27+ or Firefox Aurora / Nightly |
Preview
View existing archives.
Note: Some archives take a while to render, you will experience lower FPS while they are loading.
Got a cool archive? Request it to be added using this form
Create your own.
View your own archive in 3 easy steps with Google BigQuery!
Step 1
Go to Google APIs,
login.
Click "Create Project", if asked.
Under "Services", turn on BigQuery API:
Step 2
Go to githubarchive:github.timeline table and click "Query Table" in the top right corner. Paste this query, change "USERNAME" to your Github username:
SELECT type, created_at FROM [githubarchive:github.timeline] WHERE actor = "USERNAME"
Hit "Run Query" and "Download as CSV".


towards solutions together
Managing micro services around the world bringing people into advanced solutions.
Transform old monolitic systems into numerous adaptive micro-services.
Control your expenses with fine tuning setups and adapt the number of instances to your customers needs.
A database for geo location information, such as place reviews, points of interests or even paths.
Through several applications, allow users to feed more information and share it.
Consider having your website designed as a mobile application. Give more quality functionalities to your customers by having a dedicated application.
With hybrid technologies, anthillsolutions can create a suitable environment between mobile application and desktop website.


Use Pokemon(R) inspired palettes with additional 'ggplot2' scales. Palettes are the colours in each Pokemon's sprite, ordered by how common they are in the image. The first 386 Pokemon are currently provided.
| Version: | 0.1.1 |
| Imports: | grDevices, stats, graphics |
| Suggests: | ggplot2, magrittr |
| Published: | 2016-04-07 |
| Author: | Tim Lucas |
| Maintainer: | Tim Lucas <timcdlucas at gmail.com> |
| License: | MIT + file LICENSE |
| Copyright: | Pokemon, pokedex and all pokemon names are trademarks of Nintendo. |
| URL: | https://github.com/timcdlucas/palettetown |
| NeedsCompilation: | no |
| CRAN checks: | palettetown results |
| Reference manual: | palettetown.pdf |
| Package source: | palettetown_0.1.1.tar.gz |
| Windows binaries: | r-devel: palettetown_0.1.1.zip, r-release: palettetown_0.1.1.zip, r-oldrel: palettetown_0.1.1.zip |
| OS X binaries: | r-release: palettetown_0.1.1.tgz, r-oldrel: palettetown_0.1.1.tgz |
| Old sources: | palettetown archive |
| Reverse suggests: | malariaAtlas |
Please use the canonical form https://CRAN.R-project.org/package=palettetown to link to this page.