My name is Yengin, pronounced (Yen-Gin). I was born in Winnipeg and have also lived in New Zealand. To me, home is a work in progress. Where you come from is much less important than where you're going. Its not just the place where you were born but rather where you become yourself.
Right now, I’m a Computer Science student at the University of Manitoba. I am interested in technology that bring people together, optimize complex decision-making to reduce waste and environmental damage, increase economic efficiency, and universally accessible to everyone.
I have an adventurous side. I enjoy hiking, coach ultimate frisbee, SCUBA dive, rock climb, and go canoeing. These are my outlets for introspection.
I was a biologist in a research-focused environment first with Fisheries and Oceans Canada - Freshwater Institute and then abroad as a field assistant at the University of Auckland in New Zealand and as a scientific diver at Marine Conservation Cambodia in Cambodia.
I love meeting new people and having interesting conversations. If you want to connect, contact me here, or message me directly on any of the social media platforms.


Code Quiz
Try to answer the following question within the time limit, each wrong answer will penalize you by taking off 5 seconds. Your mission is to answer the most question possible and the faster you will be, the higher score you will get. Good Luck!


{{ role }}
Actions allocated to {{ activeRole }}:
{{ activeRole }} cannot perform any actions.
{{ action }}


--- ---
|
TGUI
v0.7-dev
|
Parent class for every widget that has borders. More...
#include <Borders.hpp>
Public Member Functions | |
| virtual void | setBorders (const Borders &borders) |
| Changes the size of the borders. More... | |
| void | setBorders (float leftBorder, float topBorder, float rightBorder, float bottomBorder) |
| Changes the size of the borders. More... | |
| void | setBorders (float width, float height) |
| Changes the size of the borders. More... | |
| virtual Borders | getBorders () const |
| Returns the size of the borders as a tgui::Borders. More... | |
Parent class for every widget that has borders.
|
inlinevirtual |
Returns the size of the borders as a tgui::Borders.
The first element will be the size of the left border, the seconds is the size of the top border, the third is the size of the right border and the the last constains the size of the bottom border.
|
inlinevirtual |
Changes the size of the borders.
| borders | Size of the borders |
Reimplemented in tgui::ComboBoxRenderer, and tgui::ChildWindowRenderer.
|
inline |
Changes the size of the borders.
| leftBorder | Width of the left border |
| topBorder | Height of the top border |
| rightBorder | Width of the right border |
| bottomBorder | Height of the bottom border |
|
inline |
Changes the size of the borders.
| width | Width of the left and right borders |
| height | Height of the top and bottom borders |


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{% for i in range(data | length) %}
{{data[i].hitchhiker}}
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{% endfor %}
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About Me
Education
For four years of my life I went to a High School in Beaverton Oregon, known as Jesuit High School. Jesuit is a private catholic high school of about 1000 teens. Jesuit is known for many things, its athletic department, and its education system. But one thing that I always participated in was technical theatre.
I graduated High School in June of 2017. Since than I have been going to Portland Community College the Rock Creek Campus for the past 1 1/2 years.
I took a couple computer science classes in the last year. I took a little c++ and a little python. In the past 1 1/2 years I have gotten most my pre-requisites done and when done with Epicodus I plan to go to a 4-year college!
Why I'm Here
The Main reason I am hear is because I want to see if I actually want to do computer science as my career choice in life. So far its looking good!!
My Hobbies
There are a couple hobbies that I like doing on daily or a weekly bases
This is a picture of one of my dogs at home. His name is Duke,this was a picture back about 7 years ago. One things I like doing when I have time is playing with the dogs or making sure they arent getting into anything.
One hobby every year that I like doing is going to the Oregon International Airshow. The picture above is from a couple years back.
This is the firework show that marked the beginning of the Oregon International Airshow


stk.molecular.topologies.cage.base module¶
-
class
stk.molecular.topologies.cage.base.
CageTopology
(A_alignments=None, B_alignments=None, edge_alignments=None, bb_positions=None)¶ Bases:
stk.molecular.topologies.base.Topology
An abstract base class for cage topologies.
-
A_alignments
¶ The length of this
list
must be equal to the number of building blocks in the cage. When cages are built one of the fgs of each building block is aligned with an edge during placement. Theint
is the id of the aligned functional group.If
None
then the functional group with id of0
is always aligned.For example,
A_alignments = [0, 2, 1, 2]
In this case there must be 4 building blocks in the cage. The the first building block has its first (
id = 0
) fg aligned. The 2nd building block has the 3rd fg (id = 2
) aligned. The 3rd building block has the 2nd fg (id = 1
) aligned. The 4th building block has the 3rd fg (id = 2
) aligned.Type: list
ofint
-
B_alignments
¶ The length of this
list
should be equal to the number of linkers in the cage. The linkers of a cage can have either 2 functional groups or 3 or more, depending on the topology.When the linkers have 2 functional groups, the
list
should hold either1
or-1
. The value indicates that the linker is aligned parallel or antiparallel with the edge its placed on. For example, in a tetrahedral topology,B_alignments = [-1, 1, 1, -1, 1, -1]
It indicates that the first linker is aligned anti parallel and the second is aligned in parallel, and so on.
If the linkers have 3 or more functional groups, the values in
B_alignments
have the same role asA_alignments
. The only difference is that by default the second fg is aligned, rather than the first.Type: list
ofint
-
edge_alignments
¶ The length of the
list
is equal to the number of building blocks in the cage. Each element is anint
which holds the id of an edge. For example,edge_alignments = [1, 2, 3, 4]
then the first building block is aligned with the edge with
Vertex.id_
of1
, the second building block is aligned with the edge withVertex.id_
2
and so on. For this to work, the edges must have theirVertex.id_
attributes defined.Type: list
ofint
-
bb_positions
¶ A
dict
of the formbb_positions = { bb1: [0, 1, 3], bb2: [2] bb3: [0, 4, 5], bb4: [1, 2, 3] }
where
bb1
andbb2
are theStructUnit3
objects used to initialize the cage andbb3
,bb4
are theStructUnit3
objects used to initialize a cage:cage = Cage([bb1, bb2, bb3, bb4], stk.FourPlusSix(bb_positions=bb_positions))
This means
bb1
sits on the vertices0
,1
, and3
,bb2
sits on vertex2
of the cage, whilebb3
sits on the edges0
,4
and5
andbb4
sits on the edges1
,2
and3
. The vertices and edges can be found in class attributespositions_A
andpositions_B
of each cage topology. Vertex0
therefore refers to the vertex with index0
inpositions_A
and so on.If
bb_positions=None
then building blocks are placed on edges and vertices at random.It is also possible to specify the building blocks via their index, for example:
bb_positions = { 0: [0, 1, 3], 1: [2] 2: [0, 4, 5], 3: [1, 2, 3] }
Here
bb1
was replaced by0
because it has an index of0
during cage construction, recall:cage = Cage([bb1, bb2, bb3, bb4], stk.FourPlusSix(bb_positions=bb_positions))
equally
bb2
is replaced by1
inbb_positions
because it has an index of1
and so on.Type: dict
-
_func_groups
¶ Keeps track of the functional groups in the macromolecule during assembly.
Type: list
ofFunctionalGroup
-
_bb_maps
(macro_mol)¶ Creates a maps from position to building block.
Parameters: macro_mol ( MacroMolecule
) – The macromolecule which needs to have its building blocks mapped to positions.Returns: Each dict
maps a position to the building block which sits on it. The position is refered to its index inpositions_A
orpositions_B
.Return type: tuple
ofdict
-
bonded_fgs
(macro_mol)¶ Joins up the separate building blocks which form the molecule.
Parameters: macro_mol ( MacroMolecule
) – The macromolecule being assembled.Yields: tuple
ofint
– Thefg_ids
of functional groups to be bonded.
-
build
(macro_mol, bb_conformers=None)¶ Assembles
rdkit
instances of macromolecules.This method places an
rdkit
molecule of the assembled macromolecule into themol
attribute ofMacroMolecule
. It also creates theMacroMolecule.bb_counter
andMacroMolecule.bonds_made
attributes.Parameters: - macro_mol (
MacroMolecule
) – TheMacroMolecule
instance which needs to be built. - bb_conformers (
list
ofint
, optional) – The ids of the building block conformers to be used. Must be equal in length to building_blocks and orders must correspond. IfNone
, then-1
is used for all building blocks.
Returns: None
Return type: NoneType
- macro_mol (
-
cleanup
(macro_mol)¶ Performs final clean up actions on an assembled molecule.
Parameters: macro_mol ( MacroMolecule
) – The molecule being assembled.Returns: None Return type: NoneType
-
pair_fgs_with_positions
(scale, macro_mol, vertex)¶ Matches fgs with the closest building block position.
After a building block is placed on a position, each fg which forms a bond must be paired with the location of the building block to which it bonds. This function matches fgs and positions so that each is only present in one pairing and so that the total distance of the pairings is minimized.
This updates of
Vertex.fg_position_pairs
attribute of vertex.Parameters: - scale (
float
) – The amount by which the size of the topology is scaled. - macro_mol (
MacroMolecule
) – The macromolecule being buit. - vertex (
Vertex
) – The position at which all the atoms being paired are located.
Returns: None
Return type: NoneType
- scale (
-
place_mols
(macro_mol)¶ Places all building block molecules on correct coordinates.
The building block molecules are placed in their appropriate positions based on the topology. It does not join them.
Also updates
MacroMolecule.bb_counter
.Parameters: macro_mol ( MacroMolecule
) – The macromolecule being built.Returns: None Return type: NoneType
-
prepare
(macro_mol)¶ Performs ops between placing and reacting building blocks.
Parameters: macro_mol ( MacroMolecule
) – The molecule being assembled.Returns: None Return type: NoneType
-
-
class
stk.molecular.topologies.cage.base.
Edge
(v1, v2, id_=None, custom_position=False)¶ Bases:
stk.molecular.topologies.cage.base.Vertex
Used to represent the edges of Cage polyhedra.
This class stores information about the edges which make up a cage’s structure.
-
direction
¶ This vector represents the orientation of the edge. It is a normalized direction vector which runs from v2 to v1, provided in the initalizer.
Type: numpy.ndarray
-
bonder_centroid
(macro_mol, scale)¶ Calculates the centroid of the fgs on the vertex.
However if
custom_position
isTrue
or macro_mol isNone
, thencoord
is returned.Parameters: - macro_mol (
MacroMolecule
) – The macromolecule being built. - scale (
float
) – The amount by which the size of the topology is scaled.
Returns: The centroid of the bonder atoms.
Return type: numpy.ndarray
- macro_mol (
-
direction
(macro_mol, scale)
-
edge_centroid
(scale)¶ Returns the centroid of the edges connected to the vertex.
Parameters: scale ( float
) – The amount by which the size of the topology is scaled.Returns: An array which holds the x, y and z positions of the centroid of the edges connected to the vertex. Return type: numpy.ndarray
-
edge_coord_matrix
(scale)¶ Return matrix holding coords of edges joined to the vertex.
Parameters: scale ( float
) – The amount by which the size of the topology is scaled.Returns: The matrix of shape [n, 3]
, wheren
is the number of edges connected to the vertex. The row holds the x, y and z coordinates, respectively.Return type: numpy.matrix
-
edge_direction_vectors
(scale)¶ Yields direction vectors between edges connected to the vertex.
Parameters: scale ( float
) – The amount by which the size of the topology is scaled.Yields: numpy.ndarray
– A normalized direction vector running from one edge connected to the vertex to another.
-
edge_plane
(scale)¶ Return coefficients of plane of edges connected to the vertex.
A plane is defined by the scalar plane equation:
ax + by + cz = d.
This method returns the
a
,b
,c
andd
coefficients of this equation for the plane formed by the connected edges. The coefficentsa
,b
andc
describe the normal vector to the plane. The coefficentd
is found by substituting these coefficients along with thex
,y
andz
variables in the scalar equation and solving ford
. The variablesx
,y
andz
are substituted by the coordinate of some point on the plane. For example, the position of one of the connected edges.Parameters: scale ( float
) – The amount by which the size of the topology is scaled.Returns: This array has the form [a, b, c, d]
and represents the scalar equation of the plane formed by the connected edges.Return type: numpy.ndarray
References
-
edge_plane_normal
(scale)¶ Return the normal of the plane formed by the connected edges.
The normal is set such that it always points away from the origin.
Parameters: scale ( float
) – The amount by which the size of the topology is scaled.Returns: A normalized vector which defines the normal pointed away from the origin. Return type: numpy.ndarray
-
place_mol
(scale, linker, alignment, macro_mol)¶ Places a linker molecule on the coordinates of an edge.
It also orientates the linker so that the fgs sit exactly on the edge and the bulk of the linker points away from the center of the cage.
Parameters: - scale (
float
) – The amount by which the size of the topology is scaled. - linker (
StructUnit2
) – The linker which is to be placed and orientated as described in the docstring. - alignment (
int
) –1
for parallel alignment withdirection
and-1
for anti-parallel alignment withdirection
. - macro_mol (
MacroMolecule
) – The macromolecule being constructed.
Returns: The
rdkit
instance holding the linker molecule with the coordinates placed on the edge and orientation set as described in the docstring.Return type: rdkit.Mol
- scale (
-
classmethod
vertex_init
(*vertices)¶ Intializes the
Vertex
from other vertices.This initalizer automatically calculates the position of the vertex from the positions of the vertices provided to the initializer. Its position is set to the centroid of the provided vertices.
The
connected
attributes of all the involved vertices are also updated.Parameters: vertices ( tuple
ofVertex
) – HoldsVertex
objects used for initialization.Returns: The initialized vertex. Return type: Vertex
-
-
class
stk.molecular.topologies.cage.base.
NoLinkerCageTopology
(alignments=None, bb_positions=None)¶ Bases:
stk.molecular.topologies.cage.base.CageTopology
Abstract base class for cage topologies without linkers.
This means that all building blocks have the same number of functional groups.
-
alignments
¶ -
Type: list
ofint
-
_bb_maps
(macro_mol)¶ Creates a maps from position to building block.
Parameters: macro_mol ( MacroMolecule
) – The macromolecule which needs to have its building blocks mapped to positions.Returns: Each dict
maps a position to the building block which sits on it. The position is refered to its index inpositions_A
orpositions_B
.Return type: tuple
ofdict
-
bonded_fgs
(macro_mol)¶ Joins up the separate building blocks which form the molecule.
Parameters: macro_mol ( MacroMolecule
) – The macromolecule being assembled.Yields: tuple
ofint
– Thefg_ids
of functional groups to be bonded.
-
build
(macro_mol, bb_conformers=None)¶ Assembles
rdkit
instances of macromolecules.This method places an
rdkit
molecule of the assembled macromolecule into themol
attribute ofMacroMolecule
. It also creates theMacroMolecule.bb_counter
andMacroMolecule.bonds_made
attributes.Parameters: - macro_mol (
MacroMolecule
) – TheMacroMolecule
instance which needs to be built. - bb_conformers (
list
ofint
, optional) – The ids of the building block conformers to be used. Must be equal in length to building_blocks and orders must correspond. IfNone
, then-1
is used for all building blocks.
Returns: None
Return type: NoneType
- macro_mol (
-
cleanup
(macro_mol)¶ Performs final clean up actions on an assembled molecule.
Parameters: macro_mol ( MacroMolecule
) – The molecule being assembled.Returns: None Return type: NoneType
-
classmethod
connect
()¶ Updates each
Vertex.connected
.Returns: None Return type: NoneType
-
pair_fgs_with_positions
(scale, macro_mol, vertex)¶ Matches fgs with the closest building block position.
After a building block is placed on a position, each fg which forms a bond must be paired with the location of the building block to which it bonds. This function matches fgs and positions so that each is only present in one pairing and so that the total distance of the pairings is minimized.
This updates of
Vertex.fg_position_pairs
attribute of vertex.Parameters: - scale (
float
) – The amount by which the size of the topology is scaled. - macro_mol (
MacroMolecule
) – The macromolecule being buit. - vertex (
Vertex
) – The position at which all the atoms being paired are located.
Returns: None
Return type: NoneType
- scale (
-
place_mols
(macro_mol)¶ Places all building block molecules on correct coordinates.
The building block molecules are placed in their appropriate positions based on the topology. It does not join them.
Also updates
MacroMolecule.bb_counter
.Parameters: macro_mol ( MacroMolecule
) – The macromolecule being built.Returns: None Return type: NoneType
-
prepare
(macro_mol)¶ Performs ops between placing and reacting building blocks.
Parameters: macro_mol ( MacroMolecule
) – The molecule being assembled.Returns: None Return type: NoneType
-
-
class
stk.molecular.topologies.cage.base.
Vertex
(x, y, z, id_=None, custom_position=True)¶ Bases:
object
Used to represent the vertices of cage polyhedra.
This class stores information about the vertices which make up a cage’s structure.
-
coord
¶ The x, y and z coordinates of the vertex, in that order.
Type: numpy.ndarray
-
connected
¶ The
Edge
orVertex
instances which represent the edges or vertices connected to this one.Type: list
of (Edge
orVertex
)
-
fgs
¶ The functional groups placed on the vertex.
Type: list
ofFunctionalGroup
-
fg_position_pairs
¶ A
list
of the formfg_position_pairs = [(fg1, v1), (fg2, v2)]
Where
v1
andv2
areVertex
instances andfg1
andfg2
areFunctionalGroup
instances.Each fg which is paired to a neighboring vertex or edge first. Only after this is the fg-fg pairing performed. The fg-(edge/vertex) pairing is stored here.
Type: list
-
distances
¶ A
list
of the formdistances = [(15.2, fg1, fg2), (18.4, fg3, fg4), ...]
After fgs have been associated with vertices to which they join, the idividual fgs are paired up. To do this the distance between every fg on the paired vertex and the fg which is paired to the vertex is found. This information is stored here the first element of each
tuple
the distance, and the second and third elements represent areFunctionalGroup
instances.Type: list
-
id
¶ An id to identify the vertex. Used by
CageTopology.place_mols()
.Type: object
, optional
-
custom_position
¶ A flag to inidcate if the position of
coord
was derived from connected vertices or set manually. If the position is derived from the vertices then the position of the building block being placed is derived from the bonder atoms in the connected vertices.Type: bool
-
bonder_centroid
(macro_mol, scale)¶ Calculates the centroid of the fgs on the vertex.
However if
custom_position
isTrue
or macro_mol isNone
, thencoord
is returned.Parameters: - macro_mol (
MacroMolecule
) – The macromolecule being built. - scale (
float
) – The amount by which the size of the topology is scaled.
Returns: The centroid of the bonder atoms.
Return type: numpy.ndarray
- macro_mol (
-
edge_centroid
(scale)¶ Returns the centroid of the edges connected to the vertex.
Parameters: scale ( float
) – The amount by which the size of the topology is scaled.Returns: An array which holds the x, y and z positions of the centroid of the edges connected to the vertex. Return type: numpy.ndarray
-
edge_coord_matrix
(scale)¶ Return matrix holding coords of edges joined to the vertex.
Parameters: scale ( float
) – The amount by which the size of the topology is scaled.Returns: The matrix of shape [n, 3]
, wheren
is the number of edges connected to the vertex. The row holds the x, y and z coordinates, respectively.Return type: numpy.matrix
-
edge_direction_vectors
(scale)¶ Yields direction vectors between edges connected to the vertex.
Parameters: scale ( float
) – The amount by which the size of the topology is scaled.Yields: numpy.ndarray
– A normalized direction vector running from one edge connected to the vertex to another.
-
edge_plane
(scale)¶ Return coefficients of plane of edges connected to the vertex.
A plane is defined by the scalar plane equation:
ax + by + cz = d.
This method returns the
a
,b
,c
andd
coefficients of this equation for the plane formed by the connected edges. The coefficentsa
,b
andc
describe the normal vector to the plane. The coefficentd
is found by substituting these coefficients along with thex
,y
andz
variables in the scalar equation and solving ford
. The variablesx
,y
andz
are substituted by the coordinate of some point on the plane. For example, the position of one of the connected edges.Parameters: scale ( float
) – The amount by which the size of the topology is scaled.Returns: This array has the form [a, b, c, d]
and represents the scalar equation of the plane formed by the connected edges.Return type: numpy.ndarray
References
-
edge_plane_normal
(scale)¶ Return the normal of the plane formed by the connected edges.
The normal is set such that it always points away from the origin.
Parameters: scale ( float
) – The amount by which the size of the topology is scaled.Returns: A normalized vector which defines the normal pointed away from the origin. Return type: numpy.ndarray
-
place_mol
(scale, building_block, aligner=0, aligner_edge=0, macro_mol=None)¶ Place a
StructUnit3
building block on the vertex.The orientation of the building block is aligned with 2 parameters. Firstly, the normal of the plane of fgs of the building block is aligned with the normal of the plane formed by the edges connected to the vertex. Because the normal of the plane of fgs always points in the direction of the building block’s centroid, this alignment causes the bulk of the building block molecule to point away from the center of the cage.
Secondly, the building block is rotated so that a fg is aligned perfectly with an edge. This reduces the rms distance between the edges and fgs to some extent, probably.
Parameters: - scale (
float
) – The amount by which the size of the topology is scaled. - building_block (
StructUnit3
) – The building block molecule to be placed on a vertex. - aligner (
int
, optional) – Thefg_id
of the aligned fg. - aligner_edge (
int
, optional) – The index of an edge inconnected
. It is the edge with which aligner is aligned. - macro_mol (
MacroMolecule
, optional) – The macromolecule being built. Used for vertex only cage topologies where the position of some of the vertices is derived from the positions of the fgs on connected vertices.
Returns: The
rdkit
instance holding the building block molecule with the coordinates placed on the vertex and orientation set as described in the docstring.Return type: rdkit.Mol
- scale (
-
classmethod
vertex_init
(*vertices)¶ Intializes the
Vertex
from other vertices.This initalizer automatically calculates the position of the vertex from the positions of the vertices provided to the initializer. Its position is set to the centroid of the provided vertices.
The
connected
attributes of all the involved vertices are also updated.Parameters: vertices ( tuple
ofVertex
) – HoldsVertex
objects used for initialization.Returns: The initialized vertex. Return type: Vertex
-
-
class
stk.molecular.topologies.cage.base.
VertexOnlyCageTopology
(A_alignments=None, B_alignments=None, edge_alignments=None, bb_positions=None)¶ Bases:
stk.molecular.topologies.cage.base.CageTopology
Abstract base class for cage topologies using ditopics.
-
_bb_maps
(macro_mol)¶ Creates a maps from position to building block.
Parameters: macro_mol ( MacroMolecule
) – The macromolecule which needs to have its building blocks mapped to positions.Returns: Each dict
maps a position to the building block which sits on it. The position is refered to its index inpositions_A
orpositions_B
.Return type: tuple
ofdict
-
bonded_fgs
(macro_mol)¶ Joins up the separate building blocks which form the molecule.
Parameters: macro_mol ( MacroMolecule
) – The macromolecule being assembled.Yields: tuple
ofint
– Thefg_ids
of functional groups to be bonded.
-
build
(macro_mol, bb_conformers=None)¶ Assembles
rdkit
instances of macromolecules.This method places an
rdkit
molecule of the assembled macromolecule into themol
attribute ofMacroMolecule
. It also creates theMacroMolecule.bb_counter
andMacroMolecule.bonds_made
attributes.Parameters: - macro_mol (
MacroMolecule
) – TheMacroMolecule
instance which needs to be built. - bb_conformers (
list
ofint
, optional) – The ids of the building block conformers to be used. Must be equal in length to building_blocks and orders must correspond. IfNone
, then-1
is used for all building blocks.
Returns: None
Return type: NoneType
- macro_mol (
-
cleanup
(macro_mol)¶ Performs final clean up actions on an assembled molecule.
Parameters: macro_mol ( MacroMolecule
) – The molecule being assembled.Returns: None Return type: NoneType
-
pair_fgs_with_positions
(scale, macro_mol, vertex)¶ Matches fgs with the closest building block position.
After a building block is placed on a position, each fg which forms a bond must be paired with the location of the building block to which it bonds. This function matches fgs and positions so that each is only present in one pairing and so that the total distance of the pairings is minimized.
This updates of
Vertex.fg_position_pairs
attribute of vertex.Parameters: - scale (
float
) – The amount by which the size of the topology is scaled. - macro_mol (
MacroMolecule
) – The macromolecule being buit. - vertex (
Vertex
) – The position at which all the atoms being paired are located.
Returns: None
Return type: NoneType
- scale (
-
place_mols
(macro_mol)¶ Places all building block molecules on correct coordinates.
The building block molecules are placed in their appropriate positions based on the topology. It does not join them.
Also updates
MacroMolecule.bb_counter
.Parameters: macro_mol ( MacroMolecule
) – The macromolecule being built.Returns: None Return type: NoneType
-
prepare
(macro_mol)¶ Performs ops between placing and reacting building blocks.
Parameters: macro_mol ( MacroMolecule
) – The molecule being assembled.Returns: None Return type: NoneType
-


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Initializes a test suite Reporter.
begin(name)
name: the name of the test suite being reported on
name
LCD reporter example - TBD


Option One
Has some stuff about option one
Option two
Has some stuff about option two
Option three
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File tensor.h¶
↰ Parent directory (src/tensors
)
Definition (src/tensors/tensor.h
)¶
Includes¶
algorithm
(File algorithm.cu)common/definitions.h
(File definitions.h)common/shape.h
(File shape.h)common/types.h
(File types.h)iomanip
iostream
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(File memory_piece.h)sstream
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@(question: models.quiz.question.MultipleChoiceQuestion,
currentAnswer: Option[Either[models.quiz.answer.MultipleChoiceAnswer, models.quiz.answer.MultipleChoiceAnswer]])(implicit user: models.user.User, session: play.api.db.slick.Config.driver.simple.Session)
@import controllers.bank.routes.QuestionBankController
@import helper._
@import com.artclod.play.s
@mainWithBorder("Viewing Question", tag.bankLink(), tag.copyLink(question.id)) {
Below is a mulitple choice question. Read the explanation and pick the correct answer:
@helper.form(QuestionBankController.answerMultipleChoice(question.id), 'id -> "multipleChociceForm", 'class -> "pure-form") {
@for(answerEither <- currentAnswer) {
@answerEither match {
case Right(answer) => {You answered @answer.display that answer was @mathml.correct(answer.correct)}
case Left(answerTmp) => {You answered @answerTmp.display Sorry but the system was unable to determine if that answer was correct :( please try another answer}
}
}
@views.html.quiz.multiplechoice.answerEditor(question, currentAnswer){@tag.bankLink() @tag.copyLink(question.id)}
}
@* ===== Results ===== *@
@defining(question.results(user)) { results : models.quiz.question.MultipleChoiceQuestionResults =>
@if(results.answers.nonEmpty) {
You have answered this questions @results.answers.size time@s(results.answers)
@for(answer <- results.answers) {
- @answer.display this answer was @mathml.correct(answer.correct)
}
}
}
}


If a Java object handle represents an instance of an array object, then it is also the name of a Tcl command that takes the following options: length, get, set, getrange, and setrange. If any other option is chosen, the behavior of the array object command defaults to that of the object command described above. The -noconvert flag can only be used with the get, getrange, and default options. The options for this command behave as follows:
set a [java::new {String[]} {6} {Java scripting is easy in Tcl}]
$a get 3
To retrieve a k-dimensional subarray of an n-dimensional array,
specifiy an indexList with n - k index values. For
example, the following commands result in subArray containing a
1-dimensional char array handle that refers to a[1][0], the internal
value of which is {e f}.
set a [java::new {char[][][]} {2 2 2} {{{a b} {c d}} {{e f} {g h}}}]
set subArray [$a get {1 0}]
set a [java::new {String[]} {6} {Tcl is a good scripting language!}]
$a set 3 great
set a [java::new {String[]} {6} {Java scripting is easy in Tcl}]
$a getrange 1 3
To retrieve a k-dimensional subarray
of an n-dimensional array, specifiy an indexList with n -
k index values. For example, the following commands result in
pair containing two 1-dimensional char array handles that refer
to a[0][1] and a[0][2], the internal values of which are {c d} and {e
f} respectively.
set a [java::new {char[][][]} {2 3 2} {{{a b} {c d} {e f}} {{g h} {i j} {k l}}}]
set pair [$a getrange {0 1} 2]
set a [java::new {String[]} {6} {Tcl is a good scripting language!}]
$a setrange 2 {an excellent}
The Conversions section describes the result and possible error conditions of the object command, including the effect of the optional -noconvert flag.
Copyright © 1997-1998 Sun Microsystems, Inc.


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GitHub


The Virtual Vultures have always been primarily focused on learning the art of formation flying and sharing it with others. We routinely train pilots in the formation fundamentals and techniques. If you are interested in learning from us or just want to meet up and fly with us, you can contact us here or through our Facebook page. We will always make time for people who share our passion, regardless of skill level or experience.
We hope to see you soon in the virtual skies.


Discover how to use our SDKs right into your own web app or mobile app.
Documentation Get Started Example


DroidInfotech specializes in building software products for its customers and has been recognized as a niche player in Product Engineering. The iterative cycle of Designing-Developing-Testing-Deploying software products for web, mobile & back-end in a truly agile fashion.
Product Concept Design
Concept understanding and preparing of personas & scenarios, Creation of wireframes for Concept Realization and Creation of detailed wireframes & Visual design for the software product.
It's important to pick the right technology stack for the product. It should be modern, should have a good skill base in market and most importantly it should serve the purpose right from a UI, middleware / server & third-party integration perspective. Solution Architects at InnovationM understand the space and pick the right technology frameworks and architecture of the product.


IRISNET (Internet-scale Resource-Intensive Sensor Network Service)
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Webcams are everywhere, collecting vast amounts of potentially useful data. However, there are no effective tools for querying the data. The Internet-scale Resource-Intensive Sensor services (IRIS) project is developing a scalable software infrastructure that will enable users with Internet access to data mine the wide world of webcams. IRIS will facilitate the deployment of webcam services that leverage both real-time and historical video feeds from any number of webcams, from other data sources, and from other types of sensor data. Each sensor is locally attached to a computer that is capable of resource-intensive processing such as image recognition. A key design goal is to facilitate dynamic reconfigurability in the sensing agent network.
Imagine driving towards a destination in a busy metropolitan area.  You get back directions to an available parking space satisfying your criteria. Hours later, you realize that your meter is about to run out. You query your PDA to discover that, historically, meter enforcers are not likely to pass by your car in the next hour. A half hour later, you return to your car and discover that although it has not been ticketed, it has been dented! Querying your PDA, you get back images showing how your car was dented and by whom.
This scenario demonstrates the potential utility of sensor-based services such as a Parking Space Finder, Silent (Accident) Witness and Meter Enforcement Tracker. While several research projects have begun to explore the use of networked collections of sensors, these systems have targeted the use of closely co-located resource-constrained sensor "motes". We describe a sensor network system architecture, called IRIS ( Internet-scale Resource-Intensive Sensor services), based on much more intelligent participants. We envision an environment where different nodes on the Internet (standard PCs, laptops and PDAs) have attached sensors such as webcams (video cameras attached to Web-enabled devices). Any sensor-based service can retrieve information from this collection of sensors and provide service to users.
While webcams are inexpensive and easy to deploy across a wide area, realizing useful services requires addressing a number of challenges, including filtering large data feeds to retrieve useful information, answering distributed queries with reasonable response times, combining multiple sources of information, etc. Our goal in IRIS is to create a common, scalable software infrastructure that allows services to address these challenges in a manageable fashion. This would enable rapid development and deployment of distributed services over a worldwide network of sensor feeds.
IRIS is composed of a potentially global collection of Sensing Agents (SAs) and Organizing Agents (OAs). Any Internet connected, PC-class device can play the role of an OA. However, less capable PDA-class devices can act as SAs.
Sensor-based services are deployed by orchestrating a group of OAs dedicated to the service. These OAs are responsible for collecting and organizing the sensor data in a fashion that allows for a particular class of queries to be answered (e.g., queries about parking spaces). The OAs index, archive, aggregate, mine and cache data from the SAs to build a system-wide distributed database for that service.
In contrast, SAs are shared by all services. An SA collects raw sensor data from a number of (possibly different types of) sensors. The focus of our design is on sensors, such as webcams, that produce large volumes of data and require sophisticated processing.
Key features of IRIS include:
OAs upload scripting code to any SA collecting sensor data of interest to the service. This scripting code programs the SA to take its raw sensor feed, perform the specified processing steps, and send the distilled information to the OA. An alternative design could be to send a generic compressed sensor feed from the SA to the OAs and to perform the filtering at the more powerful OAs. Our experiments have shown that the service-specific filtering of the sensor feed at the SA reduces the data transmitted from SAs significantly. For example, the Parking Space Finder only needs a few bytes to encode parking space availability instead of approximately 6KB per image frame for a webcam feed. Filtering at the SA also reduces the overall latency.
A key concern is that because multiple services can share an SA, the more limited computing power of the SA may be overloaded. To alleviate this concern, our scripting code API allows downloaded code from different OAs to cooperate and avoid redundant processing. For example, both the Parking Space Finder service and the Silent Accident Witness service perform steps of filtering for motion detection and for identifying vehicles. We anticipate significant work sharing, because the downloaded codes are all specialized to the processing of the SA's particular sensor feeds.
Central to sensor networks is distributed query processing over streaming data. In IRIS, data such as the latest parking space availability information is stored in XMLdatabases associated with each OA. Data for a particular service is organized hierarchically, with each OA owning a part of the hierarchy. (For example, a Parking Space Finder service may use a geographic hierarchy, e.g., usRegion--state--county--city--neighborhood--block). An OA may also cache data owned by other OAs.
A user's query, represented in the XPATH language, selects data from a set of nodes in the hierarchy. A typical XPATH query is: /usRegion[@id='NE']/state[@id='PA']/county[@id='Allegheny']/city[@id='Pittsburgh']/neighborhood[@id='Oakland' OR @id='Shadyside']/block/parkingSpace[available='yes'] This query requests all available parking spaces in the Oakland or Shadyside neighborhoods of Pittsburgh. An XPATH query contains a (maximal) hierarchical prefix, which specifies a single path from the root of the hierarchy to the lowest common ancestor (LCA) of the nodes potentially selected by the query. IRIS constructs a DNS-style name out of the prefix, IRIS constructs the name {pittsburgh.allegheny.pa.ne.parking.intel-iris.net}, performs a DNS lookup to get the IP address of this OA, and routes the query there.
Upon receiving a query, the LCA OA queries its local XML database, and evaluates the result. If necessary, it gathers missing data by sending subqueries to its children OAs (defined by the hierarchy), who may recursively query their children, and so on. Finally the answers from the children are combined and the result is sent back to the user.
If the query is initially routed to a higher-level node in the hierarchy, most of the time is spent in network communication because of the high latencies between the upper-level nodes. As we come down to the lower-level nodes, the time taken to query the databases dominates the end-to-end query time. This also demonstrates the importance of intelligently routing a query directly as far down the hierarchy as possible.
In IRIS, queries may use the data cached in an OA, even if the new query is not an exact match for the original query. For example, the query may use data for Oakland cached at the Pittsburgh OA, even though this data is only a partial match for the full query. The current prototype of IRIS supports a limited form of such semantic caching.
We believe that IRIS can enable a wealth of new sensor-based services. The next steps we are actively taking include investigating additional services, making the architecture more robust by handling both failures and graceful departures of nodes, improving performance through smarter semantic caching, and providing mechanisms for new SAs to be incorporated into active services.


WITNESS LIST State Recreational Resources Committee (Subcommittee on State Park System) January 29, 1998-9:30A State Park System Review On: Burgdorf, Jayna (TPWD) Sansom, Andrew (TPWD)


WHITE OF THE EYE (director/writer: Donald Cammell; screenwriter: China Cammell/from book "Mrs. White" by Margaret Tracy; cinematographer: Larry McConkey/Al Jones; cast: David Keith (Paul White), Cathy Moriarty (Joan White), Alan Rosenberg (Mike Desantos), Art Evans (Detective Charles Mendoza), Michael Greene (Phil Ross), Danko Gurovich (Arnold White), David Chow (Fred Hoy), China Cammell (Ruby Hoy), Alberta Watson (Ann Mason), Danielle Smith (Danielle White), Pamela Seamon (Caryanne), Mimi Lieber (Liza), 1987-UK)
Reviewed by Dennis Schwartz
The brilliant cinematography in this slasher thriller is what takes it out of the ordinary realm of such films and makes it into a diverting and more artistic venture. Esteemed cult director, Donald Cammell (Performance/Demon Seed/The Wild Side), has never quite lived up to the potential he showed in the masterpiece he co-directed, "Performance." He tragically in April 1996, shot himself through the head, mirroring the bizarre ending scene of "Performance."
In "WHITE OF THE EYE " he shows an artistic eye for odd details that he catches with his sexy camera, as he heads to the Tuscon, Arizona area and follows a gruesome, woman hating, serial killer around. The film opens as an attractive, wealthy housewife leaves Goldwaters Deparment Store and is followed home by a psychopath. Her last phone conversation to a friend is a complaint about her hair cut. Her bad hair day will pale in comparison to what happens to her next, as the unseen psychopath ritualistically slices her up and leaves on the table an ancient mystical Indian sign.
Detective Charles Mendoza (Art Evans) investigating the crime scene, is impressed by the Picasso cubist style of the killer. This is the second such ritualistic killing in Arizona within the year, but this time there is a break in the case, as truck tire tracks are found at the scene and the police are able to say for sure that there were only 44 sets of those expensive tires recently sold in the Arizona area and they have the names of all the owners.
Paul White (David Keith) is an expert soundman, an artist in putting in upgraded stereo equipment for his wealthy clients. The part Indian native of the former mining town of Globe, who has been a good citizen as an adult but who has a criminal record as a juvenile, and is now a suspect because his tires match those at the crime scene, and it is now up to the cops to track down all the other tire owners and narrow their field of suspects.
The story is told in flashback, as it goes back to an earlier time when Paul is asked to fix a damaged car stereo system by a bickering New York City couple heading to Malibu Beach. The attractive Joan (Cathy Moriarty) is ticked off at her violent boyfriend, Mike (Rosenberg), and purposefully damages his prized car stereo system. They find Paul's trailer and he is able to fix the stereo, go hunting mule deer with Mike, and he will walk off with Mike's woman, as it seems there was an immediate attraction between the two.
Mike has disappeared from the scene and it is now 10-years later, and Paul and Joan have a young girl (Danielle Smith), and seem to be madly in love with each other, though Joan is a wee bit jealous that a rich movie actress, who happens to be a stunner, Ann Mason (Alberta Watson), has eyes on her man. Assuming that Paul is having hanky-panky with Ann, as she spies on him and spots his truck at her residence, she lets the air out of his tires.
The next day, Paul is questioned by the detectives, as there was another ritualistic killing of an attractive woman, who happens to be the next door neighbor of Ann Mason. But with Joan explaining what she did, the detectives, though still very suspicious of Paul, let him go for the time being.
The question comes, is Paul being framed for the killings- or is he the killer? The only other logical suspect, whom the police don't know about, is Mike. He has returned to live in an abandoned mine, telling Joan, whom he accidently meets in a gas station, that he is a changed man after spending some hard time in Attica prison, and has come back to Globe to trace his Indian roots.
What is meant by the film's title, refers to an Apache legend about those who look into the eye of violence close-up, which allows the mystical eye to have his eye on you. As a film about mysticism, it fails badly to materialize as anything but nonsense.
For a film that has such a weak story and fails to be absorbing as a character study, this is, nevertheless, a well-crafted visual spectacle, featuring an array of beautifully stylized color co-ordinated scenes and out-of-the-way shots, that have little to do with the story, but overall they create a bizarre atmosphere that fits the brooding mood of the film to a tee. If it is the mystery story itself that you are looking for, I'm afraid you will be disappointed, as it adds up to nothing much. But in those visual shots... there is a real passion that the director has shown for filming a ritualistic killing and highlighting the outward beauty he sees in a woman. It might disappoint some, who think Cammell could have made something more than a slasher film; but, then again, his strength is through his eye, no matter how distorted it may be, and even in this low-rent type of film, his images remain strong and his themes have a strange complexity about them, enabling the film to be oddly effective, even when it shouldn't be.
REVIEWED ON 12/8/99 GRADE: C+
Dennis Schwartz: "Ozus' World Movie Reviews"
http://www.sover.net/~ozus
<EMAIL_ADDRESS>© ALL RIGHTS RESERVED DENNIS SCHWARTZ
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Related links: index of all rec.arts.movies.reviews reviews


“Vātarogābhinīto tvaṁ,
viharaṁ kānane vane;
Paviddhagocare lūkhe,
kathaṁ bhikkhu karissasi”.
“Struck by a wind ailment
while dwelling in a forest grove,
you’ve entered a tough place for gathering alms—
how will you get by, monk?”
“Pītisukhena vipulena,
pharitvāna samussayaṁ;
Lūkhampi abhisambhonto,
viharissāmi kānane.
“Pervading this bag of bones
with abundant rapture and happiness,
putting up with what’s tough,
I’ll dwell in the forest.
Bhāvento satta bojjhaṅge,
indriyāni balāni ca;
Jhānasokhummasampanno,
viharissaṁ anāsavo.
Developing the seven awakening factors,
the faculties and the powers,
endowed with subtle absorptions,
I’ll dwell without defilements.
Vippamuttaṁ kilesehi,
suddhacittaṁ anāvilaṁ;
Abhiṇhaṁ paccavekkhanto,
viharissaṁ anāsavo.
Freed from corruptions,
my pure mind is unclouded.
Frequently reviewing this,
I’ll meditate without defilements.
Ajjhattañca bahiddhā ca,
ye me vijjiṁsu āsavā;
Sabbe asesā ucchinnā,
na ca uppajjare puna.
Those defilements that were found in me,
internally and externally,
are all cut off without remainder,
and will not arise again.
Pañcakkhandhā pariññātā,
tiṭṭhanti chinnamūlakā;
Dukkhakkhayo anuppatto,
natthi dāni punabbhavo”ti.
… Nhātakamunitthero ….
The five aggregates are fully understood,
they remain, but their root is cut.
I have reached the ending of suffering,
now there’ll be no more future lives.”


For Base Value, enter the amount, in gold, but do not include "gp". If left blank, it's treated as 0 gp
Numbers or dice expressions (e.g. 2d4) can be used in the quantity fields, but they are limited. If left blank, default is 1.
This feature is currently under development. There are a couple issues to be aware of:
Treasure generation, as opposed to the other loot randomizers on this page, involves several steps: calculate (or set) your budget, select treasure types, perhaps based on a creature, and select lots from each treasure type until you meet the budget. There will be a feature to randomize selections within your budget for those "I don't care, just pick whatever" situations, in a future revision.


DevelopmentArc is proud to release a new version of it's Core framework. This version is one step closer to our goal of a 1.0 release. This release adds a large new component (Service Request Delegation System) to our suite of systems (micro-architectures) as well as a much needed refactor of the package structure of the library and other assorted bug fixes.
DevelopmentArcTM is released under the MIT License.
DevelopmentArc TM Core .09 can be downloaded from Google Code here. We have released a SWC library to be added directly into your project libs directory. We also provide a ZIP file which contains the SWC, source code and ASDoc generated documentation.
A read-only version of the Core source can be checked out using Subversion. Developers can tie directly into the .09 branch at http://developmentarc-core.googlecode.com/svn/branches/core_v0.9/. HEAD is available but is the location of the newest check-ins from the DevelopmentArc team and we do not guarantee the code is production ready, stable or corresponds with the available documentation.
Please help us by submitting your bugs or feature requests for new or existing functionality. We use the standard Google Code Issue tracking system and you can submit your issues here. We have also created a public email discussion list for support, issues and discussion around DevelopmentArc Core. You can join the list here.


Alma mater
University of Minnesota (B.Sc., 1937) (Ph.D, 1942)
Known for
Green Revolution
World Food Prize
Awards
Nobel Peace Prize (1970)
Presidential Medal of Freedom (1977)
ForMemRS (1987)
Vannevar Bush Award (2000)
Public Welfare Medal (2002)
National Medal of Science (2004)
Congressional Gold Medal (2006)
Padma Vibhushan (2006)
Fields
Agronomy
Plant Pathology
Genetics


Hi! My name is Dennis and I'm a Korean-American product designer based in Washington D.C. Back in school I studied cognitive psychology/HCI which developed my ability to empathize and design for user needs, taking into consideration both a person's cognitive limitations and how emotional context affects behavior.
I spent the past year and a half creating Corridor Coffee. Now currently looking for opportunities to use design thinking and deliver user friendly, value generating digital products. I'd love to hear from you (song recommendations are always welcome 💽)
© 2019 Dennis Kim
(Scroll Here)
Ever since I was a kid I’ve had a considerable curiosity about people and their lives. I love learning about what people do for work and why, how they tick, what makes them excited/frustrated, how their hometown/life experiences shaped who they are today, their goals and aspirations.
In a user research context I believe that creating a more holistic model of the user generally leads to alternative models to think of the problem at hand and more opporunities for creative design solutions. Some methods I use:
User Interviews: With a list of prepared questions and target information I want to find out, my interview approach is to make the user feel comfortable and confident with sharing their viewpoints and information about the product.
Contextual Inquiry: What better way to learn what a user does for work then actually going their workplace and seeing for yourself? In the past I’ve visited emergency rooms to observe charge nurses and doctors, fire department stations, makeup events, and gone out as a volunteer to serve the Harvard Square homeless population.
Usability/Hypothesis Testing: As an experimenter and participant, much of my academic experience has taught me how to conduct quality experiment design to justify assumptions or uncover unexpected outcomes. I try to come up with a testable hypothesis for what works/doesn't work about a digital product and design an experiment to test the hypothesis.
DIGITAL HEALTH PRODUCT DESIGN
As Twiage's first product design intern, I was able to design the company's landing page as well as prototype solutions for their new hospital mobile app.
MOBILE DESIGN FOR NONPROFIT
For the 2017-2018 school year I worked as the lead UX designer on a team of 10 to create a mobile app for the Harvard Square Homeless Shelter.
BRAND DESIGN SMALL BUSINESS
My most recent endeavor involved designing, manifesting, and running a small specialty coffee / matcha shop in Georgetown.
USER INTERFACE DESIGN CLASS
Design Assignments for Tufts Human Factors + Computer Interface Design Course
LAYOUT/WEB DESIGN TUFTS MAGAZINE
Designed multiple print layouts + digital web accompaniments for Tuft's oldest student publication


Run WebSocket
Stop WebSocket
Trade History Demo
Produce to Kafka
Id:
Owner:
Symbol:
Shares:
Price:
Notional:
When:
Commission:
Get the most recent message from mongo


 Ribbit!
 Thought you were someone else! Someone I was waiting to hear from! Croak!


Dr. Naccarato is a Doctor of Chiropractic with a PhD in Psychology and over 28 years and 56,000 hours of experience personally coaching over 80 doctors each week.
There are no gimmicks and no quick fixes. Dr. Naccarato has created a unique program that guides doctors step by step to build a successful practice while maintaining their integrity and dignity.
The only success strategy that really works to bring you lasting success and prosperity is an approach customized to fit you. In this program we honor this truth.
"Dr. Naccarato has helped me greatly with both business and personal development. I would highly recommend him as a personal coach to any doctor looking to improve success in his life."
"Dr. Naccarato has been my coach for almost a decade. He has helped me build a strong, stable, anxiety-free practice. I am most impressed with his impeccable integrity. He will be my coach for as long as I remain in practice."
"Doctor Naccarato has helped me to achieve better balance in my life and practice. He restores ethical chiropractic practice building that is based on moral principles that raise the respect of individual doctors and our profession."


Please right click an element of your web page first, and select one of context menu items that Whiten provides:
- Whiten -> Clean up background
- Whiten -> Remove element
- Whiten -> Remove elements by class
- Whiten -> Remove elements by box
- Whiten -> Others ...
- ---------
- Whiten -> Highlight element
- Whiten -> Highlight elements by class
by Liigo, 2020/03


32 flights diverted from Delhi airport on Sunday morning due to pollution
When asked if it can be said that 'bad weather' is actually the pollution, the spokesperson replied in affirmative
by Press Trust of IndiaThirty-two flights were diverted from Delhi airport on Sunday morning due to low visibility caused by pollution, airport officials said.
"Total 32 flights have been diverted from Delhi airport on Sunday morning due to bad weather," they said.
An Air India spokesperson said, "Due to bad weather, flight operations affected since morning 9 am in T3 airport (Delhi). Twelve flights are diverted to Jaipur, Amritsar and Lucknow."
When asked if it can be said that "bad weather" is actually the pollution, the spokesperson replied in affirmative.


Actions, resources, and condition keys for AWS DataSync
AWS DataSync (service prefix:
datasync
) provides the following service-specific resources, actions, and condition context keys for use in IAM permission policies.
References:
-
Learn how to configure this service .
-
View a list of the API operations available for this service .
-
Learn how to secure this service and its resources by using IAM permission policies.
Topics
Actions defined by AWS DataSync
You can specify the following actions in the
Action
element of an IAM policy statement. Use policies to grant permissions to perform an operation in AWS. When you use an action in a policy, you usually allow or deny access to the API operation or CLI command with the same name. However, in some cases, a single action controls access to more than one operation. Alternatively, some operations require several different actions.
The
Resource types
column of the Actions table indicates whether each action supports resource-level permissions. If there is no value for this column, you must specify all resources ("*") to which the policy applies in the
Resource
element of your policy statement. If the column includes a resource type, then you can specify an ARN of that type in a statement with that action. If the action has one or more required resources, the caller must have permission to use the action with those resources. Required resources are indicated in the table with an asterisk (*). If you limit resource access with the
Resource
element in an IAM policy, you must include an ARN or pattern for each required resource type. Some actions support multiple resource types. If the resource type is optional (not indicated as required), then you can choose to use one of the optional resource types.
The
Condition keys
column of the Actions table includes keys that you can specify in a policy statement's
Condition
element. For more information on the condition keys that are associated with resources for the service, see the
Condition keys
column of the Resource types table.
For details about the columns in the following table, see Actions table .
| Actions | Description | Access level | Resource types (*required) | Condition keys | Dependent actions |
|---|---|---|---|---|---|
| AddStorageSystem | Grants permission to create a storage system | Write | |||
| CancelTaskExecution | Grants permission to cancel execution of a sync task | Write | |||
| CreateAgent | Grants permission to activate an agent that you have deployed on your host | Write | |||
| CreateLocationEfs | Grants permission to create an endpoint for an Amazon EFS file system | Write | |||
| CreateLocationFsxLustre | Grants permission to create an endpoint for an Amazon Fsx Lustre | Write | |||
| CreateLocationFsxOntap | Grants permission to create an endpoint for Amazon FSx for ONTAP | Write | |||
| CreateLocationFsxOpenZfs | Grants permission to create an endpoint for Amazon FSx for OpenZFS | Write | |||
| CreateLocationFsxWindows | Grants permission to create an endpoint for an Amazon FSx Windows File Server file system | Write | |||
| CreateLocationHdfs | Grants permission to create an endpoint for an Amazon Hdfs | Write | |||
| CreateLocationNfs | Grants permission to create an endpoint for a NFS file system | Write | |||
| CreateLocationObjectStorage | Grants permission to create an endpoint for a self-managed object storage bucket | Write | |||
| CreateLocationS3 | Grants permission to create an endpoint for an Amazon S3 bucket | Write | |||
| CreateLocationSmb | Grants permission to create an endpoint for an SMB file system | Write | |||
| CreateTask | Grants permission to create a sync task | Write | |||
| DeleteAgent | Grants permission to delete an agent | Write | |||
| DeleteLocation | Grants permission to delete a location used by AWS DataSync | Write | |||
| DeleteTask | Grants permission to delete a sync task | Write | |||
| DescribeAgent | Grants permission to view metadata such as name, network interfaces, and the status (that is, whether the agent is running or not) about a sync agent | Read | |||
| DescribeDiscoveryJob | Grants permission to describe metadata about a discovery job | Read | |||
| DescribeLocationEfs | Grants permission to view metadata, such as the path information about an Amazon EFS sync location | Read | |||
| DescribeLocationFsxLustre | Grants permission to view metadata, such as the path information about an Amazon FSx Lustre sync location | Read | |||
| DescribeLocationFsxOntap | Grants permission to view metadata, such as the path information about an Amazon FSx for ONTAP sync location | Read | |||
| DescribeLocationFsxOpenZfs | Grants permission to view metadata, such as the path information about an Amazon FSx OpenZFS sync location | Read | |||
| DescribeLocationFsxWindows | Grants permission to view metadata, such as the path information about an Amazon FSx Windows sync location | Read | |||
| DescribeLocationHdfs | Grants permission to view metadata, such as the path information about an Amazon HDFS sync location | Read | |||
| DescribeLocationNfs | Grants permission to view metadata, such as the path information, about a NFS sync location | Read | |||
| DescribeLocationObjectStorage | Grants permission to view metadata about a self-managed object storage server location | Read | |||
| DescribeLocationS3 | Grants permission to view metadata, such as bucket name, about an Amazon S3 bucket sync location | Read | |||
| DescribeLocationSmb | Grants permission to view metadata, such as the path information, about an SMB sync location | Read | |||
| DescribeStorageSystem | Grants permission to view metadata about a storage system | Read | |||
| DescribeStorageSystemResourceMetrics | Grants permission to describe resource metrics collected by a discovery job | List | |||
| DescribeStorageSystemResources | Grants permission to describe resources identified by a discovery job | List | |||
| DescribeTask | Grants permission to view metadata about a sync task | Read | |||
| DescribeTaskExecution | Grants permission to view metadata about a sync task that is being executed | Read | |||
| GenerateRecommendations | Grants permission to generate recommendations for a resource identified by a discovery job | Write | |||
| ListAgents | Grants permission to list agents owned by an AWS account in a region specified in the request | List | |||
| ListDiscoveryJobs | Grants permission to list discovery jobs | List | |||
| ListLocations | Grants permission to list source and destination sync locations | List | |||
| ListStorageSystems | Grants permission to list storage systems | List | |||
| ListTagsForResource | Grants permission to list tags that have been added to the specified resource | Read | |||
| ListTaskExecutions | Grants permission to list executed sync tasks | List | |||
| ListTasks | Grants permission to list of all the sync tasks | List | |||
| RemoveStorageSystem | Grants permission to delete a storage system | Write | |||
| StartDiscoveryJob | Grants permission to start a discovery job for a storage system | Write | |||
| StartTaskExecution | Grants permission to start a specific invocation of a sync task | Write | |||
| StopDiscoveryJob | Grants permission to stop a discovery job | Write | |||
| TagResource | Grants permission to apply a key-value pair to an AWS resource | Tagging | |||
| UntagResource | Grants permission to remove one or more tags from the specified resource | Tagging | |||
| UpdateAgent | Grants permission to update the name of an agent | Write | |||
| UpdateDiscoveryJob | Grants permission to update a discovery job | Write | |||
| UpdateLocationHdfs | Grants permission to update an HDFS sync Location | Write | |||
| UpdateLocationNfs | Grants permission to update an NFS sync Location | Write | |||
| UpdateLocationObjectStorage | Grants permission to update a self-managed object storage server location | Write | |||
| UpdateLocationSmb | Grants permission to update a SMB sync location | Write | |||
| UpdateStorageSystem | Grants permission to update a storage system | Write | |||
| UpdateTask | Grants permission to update metadata associated with a sync task | Write | |||
| UpdateTaskExecution | Grants permission to update execution of a sync task | Write | |||
Resource types defined by AWS DataSync
The following resource types are defined by this service and can be used in the
Resource
element of IAM permission policy statements. Each action in the
Actions table
identifies the resource types that can be specified with that action. A resource type can also define which condition keys you can include in a policy. These keys are displayed in the last column of the Resource types table. For details about the columns in the following table, see
Resource types table
.
| Resource types | ARN | Condition keys |
|---|---|---|
| agent |
arn:$
{
Partition}:datasync:$
{
Region}:$
{
AccountId}:agent/$
{
AgentId}
|
|
| location |
arn:$
{
Partition}:datasync:$
{
Region}:$
{
AccountId}:location/$
{
LocationId}
|
|
| task |
arn:$
{
Partition}:datasync:$
{
Region}:$
{
AccountId}:task/$
{
TaskId}
|
|
| taskexecution |
arn:$
{
Partition}:datasync:$
{
Region}:$
{
AccountId}:task/$
{
TaskId}/execution/$
{
ExecutionId}
|
|
| storagesystem |
arn:$
{
Partition}:datasync:$
{
Region}:$
{
AccountId}:system/$
{
StorageSystemId}
|
|
| discoveryjob |
arn:$
{
Partition}:datasync:$
{
Region}:$
{
AccountId}:system/$
{
StorageSystemId}/job/$
{
DiscoveryJobId}
|
Condition keys for AWS DataSync
AWS DataSync defines the following condition keys that can be used in the
Condition
element of an IAM policy. You can use these keys to further refine the conditions under which the policy statement applies. For details about the columns in the following table, see
Condition keys table
.
To view the global condition keys that are available to all services, see Available global condition keys .
| Condition keys | Description | Type |
|---|---|---|
| aws:RequestTag/${TagKey} | Filters access by the tag key-value pairs in the request | String |
| aws:ResourceTag/${TagKey} | Filters access by the tag key-value pairs associated with the resource | String |
| aws:TagKeys | Filters access by the tag keys in the request | ArrayOfString |


--- layout: page title: 'Biofilm: Pseudomonas' date: 2013-02-18 17:50:32.000000000 -05:00 type: page published: true status: publish categories: [] tags: [] meta: _edit_last: '1' _wp_page_template: full-width-page.php _responsive_layout: default _post_lock_status: unlocked author: login: kenny email<EMAIL_ADDRESS>display_name: kenny first_name: Kenneth last_name: Flynn ---
Pseudomonas aeruginosa is an opportunistic bacterial pathogen shown to have the capacity to cause chronic infections in the lungs of persons with cystic fibrosis (CF). These Pseudomonas lung infections are particularly difficult to treat due to their unpredictable patterns of evolutionary diversification.
How can we deconvolute the evolutionary and ecological dynamics of chronic Pseudomonas infections?
What genetic or ecological changes define significant shifts that affect the function of the diverse population and its pathogenicity to the host
Our approach.
We use a biofilm experimental evolution method that allows us to study evolution in real time, as described previously.
The unpredictability of Pseudomonas ecology.
From K. Flynn: What you see above are representative samples of the phenotypic differences seen through time in replicate populations. These differences in colony development are caused by numerous genetic changes to the genome of this organism. By grouping isolates based on genetic history and phenotypic traits, we are able to identify what traits may underlie persistence as biofilm specialists. This increase in standing genetic variation in these populations likely contributes to the unpredictable fluctuations seen above and during chronic Pseudomonas infections.
Biofilm specialization is related to the decision to move or stay.


{% extends 'root_email_template_new.html' %}
{% block heading %}
Hi {{email}}
{% endblock heading %}
{% ifequal 'deleted' message %}
{% block content_body %}
Your account has been deleted by {{deleted_by}}. You are no longer able to access your account.
{% endblock content_body %}
{% endifequal %}


It’s been a year and more out for me since SRS (and perhaps you, too)
The swelling has long gone down, the pain a vague memory. Life is good. No more genital dysphoria (mostly)
I no longer have to (although I ought to) dilate on a daily basis.
How often then should I dilate? Or, how often then should you dilate?
Let your body tell you. If you’re losing depth and/or width, that’s a sign that your vag isn’t getting enough maintenance so get on it. A sign of losing depth of width is struggling to get the dilators you could previously accommodate, to the depth you could, given a particular width. Or even simply struggling to get the dilator to enter (of course having already used enough lube!!! wince)
Increase the frequency of dilation until you don’t lose depth of width. For myself I did end up dilating less frequently than every other day , which alarmingly made me lose width and depth. That was scary. I restarted my dilation daily and slowly took it to alternate days, although some weeks, I do end up playing it safe and not skipping any days at all.
I hope you’re able to find your own balance between having a life and dilating! Happy dilating!


WITNESS LIST
Finance
March 11, 2015 9:00 AM
FOR:
Smith, Tom Smetty Director (Public Citizen)
ON:
Kimbriel, Todd Interim Executive Director (also providing written testimony) (Dept. of
Information Resources), Austin, TX
Linder, Kelly Assistant State Auditor (State Auditor's Office)
Parks, Ursula Director (LBB)
Wood, Robert Associate Deputy Comptroller for Ops & Support (also providing written
testimony) (CPA)
Young, John Audit Manager (State Auditor's Office), Austin, TX
Registering, but not testifying:
FOR:
Dudensing, Jamie CEO (Texas Association of Health Plans)
Romero, Michelle Associate Director of Advocacy (Texas Medical Association), Austin,
TX
ON:
Amajor, Chuks Director of TPASS (CPA)
Barton, John Deputy Director, TxDOT (Texas Department of Transportation), Austin, TX
Bass, James Chief Financial Officer, TxDOT (Texas Department of Transportation),
Austin, TX
Beaulien, Shirley Chief Financial Officer (Texas Education Agency), Austin, TX
Latta, Karen Senior Manager (Sunset Advisory Commission)
Saldivar, Cesar Audit Manager (State Auditor's Office (SAO)), Austin, TX
Spock, Karl Senior Manager (Sunset Commission), Austin, TX
Providing written testimony:
ON:
Matz, Sarah Director, State Gov. affairs (TechAmerica)


About
Northeastern's Computer Science Mentoring Organization serves
to better connect Northeastern students who are interested in Computer Science.
This club is open to CS majors, combined majors, minors, and non-majors.
Interested in our mentorship program?
Contact us here!
What's up next?
{% for event in site.data.upcoming %}
{{ event.title }}
{{ event.dateTime | date: " %B %-d, %Y @ %I:%M " }}
{{ event.description }}
{% endfor %}
Nothing currently planned - check back soon!
Past Events
{% for event in site.data.upcoming %}
{{ event.title }}
{{ event.dateTime | date: " %B %-d, %Y @ %I:%M " }}
{{ event.description }}
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by AK & Emmett
Line
Bar
Pie
Table
Uniques
Totals
Average
Use this code in Mixpanel's custom applications tab to make this dashboard


Login
Enter your passphrase to login or a new one to create a wallet.
I am an error message
Enter your passphrase to login or a new one to create a wallet.
I am an error message
| Moniker | Color set | Unit |
|---|---|---|
| Bitcoin | 100000 | |
| Gold-coin | 100 |
These are your addresses for receiving payments
| Time | Op | Amt. | Asset |
|---|---|---|---|
| 2014-07-19 13:52 | Sell | 10 | Bitcoin |
| Address: 123jasa994ncoee9q4n | |||
| 2014-07-19 13:52 | Buy | 3.50 | Foo-coin |
| Address: CoPw4ahijciS1C@mp78983PxHDLX4BdQTSHu4nhHC7W6CEssn |
| Time | Operation | Amount | Asset | Address |
|---|---|---|---|---|
| 2014-07-19 13:52 | Sell | 10 | Bitcoin | 123jasa994ncoee9q4n |
| 2014-07-19 13:52 | Buy | 3.50 | Foo-coin | CoPw4ahijciS1C@mp78983PxHDLX4BdQTSHu4nhHC7W6CEssn |
| Price | Quantity | Total |
|---|---|---|
| 3.4 | 10 | 34 |
| Price | Quantity | Total |
|---|---|---|
| - | - | - |


2D, 3D Modelation
For this week i chose the solidworks for model my project final sketch.
I choose the solidworks to make this work because i work with this software a while ago and i like this software and is very powerful.
Before i use the solidworks to make 3D model i drew some skecthes in my notepad.
In Solidworks i make some parts individually for in final i make one assembly total with all parts. In this images i show some steps i use to make one part.
Before i drew in 2D i make a Extrude to make a box that i´m going to work.
In this steps i drew one circle and i make Linear Sketch Pattern to copy one circle in many cicles, in this tool you chose the direction what do you want to do the copy as also you chose the number of circles and spacing between circles.
Before i drew the circles i make Extruded Cut to make some holes.
At the end i choose the material to assign this part.
In this i caught all parts i modeled and amssemble all to make my machine.
Animation
To make the animation i use the Motion study in Solidworks. Is Very simple to make a simple animation, for make the animation you only need activated Autokey this option you only nedd to move the objects for place you want and solidworks put one key in timeline automatically. You can see the timeline is empty. In this images i show the steps to make a simple animation on Motion Study in Solidworks. In this image can be seen the orange bar this bar show in the time we are. I put this bar in 2seconds becase i want the animation to happen to this time.
In this step i move the component to the place i want and the solidworks put a key automattically in time line.
In this step i move two component in simultaneausly and can see in the time line the two component i move and the keys of each components.
This is a final of my animation and all operation i make to this animation.
In this animation i show the simple operation of my machine.


Use this page to upload raw files of any type to /mnt/public/files on the viblio server. You may click on the button below to choose files to upload, or on some browsers, you may be able to drag files from your desktop on drop them on this page.


Needsupply.com
Front End Developer on Agile SCRUM dev team for this Magento e-commerce site. Coded editorials and features to comp spec, worked in custom content management system, and generally maintained the site through sweeping personnel changes.
Tech:
Magento (PHP), Laravel, JavaScript, jQuery, HTML, CSS, SCSS, SQL
Totokaelo.com
Front End Developer on Agile SCRUM dev team for this Magento e-commerce site. Coded editorials and features to comp spec, worked in custom content management system, and generally maintained the site through sweeping personnel changes.
Tech:
Magento (PHP), Laravel, JavaScript, jQuery, Vue.js, HTML, CSS, SCSS, SQL
Jammin' on the James
Jammin' on the James is a lindy hop dance workshop event that happens in Richmond, VA every October. I'm doing a complete redesign of their site to bring it into the 21st century for this year's event. It employs some fun plugins like animate.css, morphtext, sticky.js. It is designed to be fully responsive, for desktop and mobile devices. At the moment, it is running on a Sinatra framework.
Tech:
Ruby, Sinatra, JavaScript, Bootstrap, custom CSS, HTML
Speak
This is a free, online alternative to the sometimes prohibitively expensive Augmentative and Alternative Communication devices that allow nonverbal children (and adults!) to express themselves. It was our capstone project and something I hope to keep working on in the future.
This non-traditional web app relies heavily on Amazon Polly (a text-to-speech AWS), click event handling, UX design, and user customizability.
Tech:
Ruby, Rails, PostgreSQL, JavaScript, jQuery, AJAX, AWS, Bootstrap, custom CSS, HTML
DevKitchen
This restaurant-concept site was created for a mock client who wanted to crowd-source recipes for her restaurant. It's a Ruby on Rails app in which logged-in users can submit recipes to be featured on the restaurant’s menu by the owner. The owner can create and post the menus right on the site. I handled the menu creation feature, user registration and log in, and group management.
Tech:
Ruby, Ruby on Rails, PostgreSQL, JavaScript, Bootstrap, custom CSS, HTML


Lamdu
Reviewed July 18, 2019Lamdu is a Haskell-inspired projectional editor. It features live-evaluated subexpression annotations, localized type errors, and a focus on a fluid editing experience. It is an open-source project, actively developed since 2011.
Product Feel
- 👍 Shows all live intermediate values
- 👍 Fine-granularity ctrl-z is key
- 👍 One of the most usable structural editors
- 👎 Often getting into strange editing modes
Basic Usage
The following video creates a series of simple mathematical expressions in Lamdu.
It demonstrates:
- creating a definition
- using the REPL
- exploring the intermediate results via the subexpression annotations
- filtering a list
- converting a lazy list to an array to preview it
- my struggle to get
*2
to apply to an argument and not the result of the function - changing the display of a function to infix and OOP-style
- filtering via a first class function
- abstracting out an expression into a global variable
The following video builds a simple HTTP server in Lamdu.
It demonstrates:
- creating string values and their concatenation
- my struggle getting the correct return type
- exploring the definition of
httpOk200
- browsing all the request data for past HTTP requests
- automatic type conversion of a string into Text Bytes
The following explores and modifies a large Lamdu project, a conference website server.
It demonstrates:
- exploring from the top-level expression down many different definitions and sub-definitions
- renaming an untitled
(empty)
expression - renaming a shadowed name (identified with numbered subscripts)
Live data
It's extremely rare to see live-evaluated subexpression annotations, particularly in languages with a textual representation. Some non-visual languages put the results of whole lines off to the side, but Lamdu is one of the first to publish a working implementation of underlined evaluation of all intermediate subexpressions. This goes a long way towards making functional programming understandable for beginners.
100% Keyboard
Unlike many projectional editors, Lamdu is navigable without every touching the mouse. Everything (and I mean everything) can be done via keyboard. It features a context-aware shortcut help menu to help you learn their hotkeys. However despite their attention-to-detail, I still found it quite difficult to use as you can see me fumbling in the above videos. Crafting a fluid projectional editor is still an unsolved problem but they have made significant strides.
Refactoring
As demonstrated in the above videos, internally variables have ID’s, so changing their names is a superficial change. This means no merge conflicts on renaming, formatting, stylistic differences, or moving code. There are no files, folders or line numbers to worry about.
Named Parameters
Lamdu's function features named parameters, like keyword arguments in Python. They add clarity compared to their equivalents in Haskell, but also add clutter.
Type suggestions
Their type errors take advantage of information unavailable to traditional textual languages, such as the order in which you type an expression. This allows it to infers your intent. For example, if you type “Hello” first it guesses that the type error is with the 5
:
But if you added the 5
first, it would now see an error with your "Hello"
Wishes
- Caching previous HTTP request runs to show live data when editing
- Autocomplete suggestions to be WYSIWYG (instead of the star and green color to indicate where expressions and the cursor will go)


{% extends "base.html" %} {% block app_content %}
No scan data for {{ domain }} currently available! Check back later.


Know the importent features that are used for the prediction of the crop.
Give us values of your Soil composition in return you will get the suitable crop name for your agricultural land.
Click here to enter an intractive dashboard which contains information about crops.


An advertizing cycling banner page!!! This banner is about athletic-sport companies and each foto is clickable (redirects you to the site of the company)


This year-long, part-time, NHS-based course trains people to teach the eight-week MBCT/MBSR programmes. It is open to both NHS staff and people who work outside of the NHS. The training runs from February to December each year, and includes an opportunity to teach an entire MBCT or MBSR course alongside one of Sussex Mindfulness Centre's highly experienced mindfulness teachers.
Graduates are eligible to apply for BAMBA registration
Graduates of the training, who have taught two groups of the same curriculum, are eligible to apply to the British Association for Mindfulness Based Approaches' (BAMBA's) national register of mindfulness teachers. The training costs £3,950, plus a £500 residential retreat. There are usually some funded or part-funded training places available for Sussex Partnership NHS Foundation Trust staff.
The course handbook below provides more details:
- 2024 Course Handbook
- 2024 Application Form For Sussex Partnership Staff
- 2024 Application Form For External Applicants
Applications for 2024 are now open
Applicants who are external to Sussex Partnership NHS Foundation Trust (SPFT) are welcome to submit their applications early and to request an earlier interview date.
Meet the teachers and find out more
Attend one of our teacher training information sessions on the following dates:
- Monday 3 July 10 - 11am
Register to attend one of these sessions by emailing<EMAIL_ADDRESS>For further information about the training, please contact<EMAIL_ADDRESS>or call our Sussex Mindfulness Centre Administrator on 0300 304 0689. Regular, online, information sessions will be held about SMC’s trainings throughout the year. Please email<EMAIL_ADDRESS>if you'd like to book a place on one.


Shorty: URL Shortener
Create personalized short-links
Some error message
Some success message
To access the admin panel, you must first login.
Username
Password
Wrong Username or Password!
Logout successful!
Add the destination URL of your short link
Please add an (optional) name for your short link
Abbreviation
Destination
Operations
hhu
https://hhu.de


Coding Bootcamp
Coding Bootcamp
Tuition: $11,063
Length: 9-12 weeks
hours+/week
88% Job placement
Other Learning options
Learning on your own
New development companies use an online tool called Slack
Slack.com
Github.com
Codepen.io
JSbin.com
Create communities around their products
Easy access to other users working with the same tools
Allows you to ask questions of those building the software
Stackoverflow.com
Post questions that other professionals can answer
Books go more in-depth than online courses
safaribooksonline.com


"I Saw Mommy Kissing Yog-Sothoth" and other Cthulhuian Yuletide classics
by Gareth BranwynOh tidings of madness and woe. Gather 'round the Necronomicon, little cultists, and let's all sing these beloved holiday odes to Elder Gods. All the classics are here: "I Saw Mommy Kissing Yog-Sothoth," "Freddy the Red-Brained Mi-Go," "All I Want for Solstice is my Sanity," and "Awake Ye Scary Old Ones." And who can ever forget that rubber-room holiday favorite "Away in a Madhouse?"
These songs were all created by members of the H.P. Lovecraft Historical Society. You can hear more via this YouTube link.
[H/t Geeks Are Sexy]


Select a ROM file in z64 format (Only NTSC ROMS are supported)
The tool will patch the ROM (This might take a few seconds)
You will receive a download with the patched ROM
Is this legal?
Yes! The ROM file never leaves your computer.
Patching is entirely done locally and I do not distribute any Nintendo 64 ROM files.
It is the user's responsibility to provide a legit ROM.
Controls
Controller 1
Start + B: Level Select
Start + A: Start Timer
Start + C-Left/C-Right: Store/Load Position
Start + C-Up/C-Down: Store/Restore Actors
Controller 2
Start: Open/Close menu
Navigate menu with D-Pad Up/Down and A/B
Values can be incremented/decremented with D-Pad Left/Right


In this demo we take the well-known game of Sudoku, and demonstrate how developers can use HTML5 and JavaScript to create an efficient algorithm to solve these puzzles. The algorithms draw heavily on the Chakra engine’s support for ECMAScript 5 standard array operations to rapidly solve many Sudoku games. You can also manually solve Sudoku puzzles.
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Designing and implementing software to control the underwater ROV prototype being created by our Mechanical Engineering team.
Remote-controlled movement capabilities via tether to control station.
Autonomous lateral stabilization within 1 meter from reference.
Ability to communicate sensor and video data to control station.
Operational at depths up to 10 meters (IPX8 waterproof standard).
Micro-computer running Debian Linux. We utilize its faster processing power for tasks requiring low latency such as manual motor control and relaying live video feed.
The ATmega328p micro-controller's AVR architecture allows us to easily read sensor data through various interfaces. Isolates sensor reading/filtering from other processes for more consistent sampling.
We will be using the OpenROV platform to test our software while the Mechanical Engineering team builds our first prototype.
As we continue to develop and test our system, updates will be posted to my robotics blog.


{% extends 'base.html' %} {% block title %} contact {% endblock %} {% block extrahead %} {% endblock %} {% block content_wrapper %}
A social project of mine. I schedule a private meeting with one
person every week.
How do I chose those people?
By one of three ways:


The following is a DID with requirements for xAPI data that can be used when procuring any type of xAPI content.
DATA ITEM DESCRIPTIONTitle: EXPERIENCE API (XAPI) DATA |
|
|
Number: TBD |
Approval Date: TBD |
|
Use/relationship: Experience API (xAPI) Data will be used for describing, reporting, and visualizing one’s experience or performance within a formal or informal learning activity. Additional information is available at the DoDI xAPI Fungible Reference, https://adlnet.gov/policy/fungible. a. Information to be recorded through xAPI data will include interactions and usage with e-learning content, performance support applications, and other related types of training content. b. This DID contains the format, content, and intended use information for the data product resulting from DoD Instruction 1322.26 (Distributed Learning) and the work task described by the contract, and is applicable to the acquisition of any military learning and training content that requires xAPI for data collection. Requirements: 1. Reference documents. The applicable issue of the documents cited herein, including their approval dates and dates of any applicable amendments, notices, and revisions, shall be as specified in the contract. 2. Format. The Experience API format that uses JavaScript Object Notation (JSON) will be used to represent learner experience data. All xAPI data must be conformant to the requirements identified in the xAPI Specification and applicable xAPI Profiles. If an object or property is listed as “optional” in the xAPI Specification, but that same object or property is listed as a requirement in a Profile, then the Profile takes precedence. 3. Content. The content will utilize existing xAPI Profiles to maximize interoperability and data portability. All content developed to track xAPI data will implement the requirements defined in the appropriate xAPI Profile documentation for each content type. 4. Log Files. The content of the log files will show evidence of successful communication of the xAPI statements to a Learning Record Store (LRS) and shall include any error codes. The content of the log files will also show evidence that the appropriate xAPI Profiles were referenced. The log files that show evidence of the successful xAPI statements storage and retrieval can be of any text format as long as the statements in the log file are the original xAPI JSON value. End of DID# |


+++ title = "Milo" lat = 37.724293 lon = 15.116672 +++
No, I don't mean the chocolate-flavoured energy drink: I mean Milo, the small mountain village on the eastern edge of Sicily, between towering Mount Etna (Europe's highest active volcano) and the gorgeous Ionian coast. I slept at a campsite just outside of Milo this evening, and I rode through the village the following morning.


B.Tech. III (CO) Semester – 5 |
L |
T |
P |
C |
CO315: PROBABILITY RANDOM PROCESS AND STATISTICAL INFERENCE (EIS – I) |
3 |
0 |
0 |
3 |
(12 Hours) |
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Sets, Random Experiments, Events, Probability: Conditional Probability, Bayes’ rule, Random Variables, Probability Distributions and their properties; Binomial Distribution, Bernoulli Trials, Normal Distribution, Poisson Distribution, Joint Distributions, Expectation, Functions of Random Variables, Moments, Moment Generating Functions, Law of Large Numbers, Central Limit Theorem. |
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(06 Hours) |
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Statistical Inference, Random Samples, Sampling Distribution, Sample Mean, Variance and other statistics, Estimation Theory: Unbiased Estimates, Point Estimates and Interval Estimates, Confidence Interval, Maximum Likelihood Estimates |
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(08 Hours) |
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Statistical Decisions, Statistical Hypotheses and Significance, Type I and Type II Errors, Level of Significance, Test Involving Normal Distribution and Chi-square Distribution, One-Tailed and Two-Tailed Tests, Estimation Theory and Hypotheses Testing |
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(16 Hours) |
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Random Walk, Brownian Motion, Poisson process, Mean Square Estimation, Entropy, Queuing Theory, Discrete Time Markov Chains, Continuous Time Markov Chains, Q-matrix, Birth-death processes, Quasi birth death processes, Applications: Performance Analysis of Computer Network, Model Based Computer Vision. |
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(Total Contact Time: 42 Hours) |
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BOOKS RECOMMENDED |
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1). Sheldon Ross,” Probability models for computer science”,7/E,Prentice Hall,2005 |