Before Change
start_time = time.time()
collect_call()
for _ in range(train_steps_per_iteration):
loss_info_value, _, global_step_val = train_step_call()
time_acc += time.time() - start_time
if global_step_val % log_interval == 0:
After Change
for _ in range(train_steps_per_iteration):
loss_info_value = train_step_call()
time_acc += time.time() - start_time
global_step_val = global_step_call()
if global_step_val % log_interval == 0:
logging.info("step = %d, loss = %f", global_step_val,
loss_info_value.loss)


Hateful EIGHT: The Northern IPA
8.7% ABV
A classic new england staple that your dad will probably like. I messed up the math so its extra alcoholic. We only brewed eight of them. Permanently Sold Out (forever).
ENFP. Medium tall. Outside voice all the time. Cuts his own hair. Enthusiast.
Comes in a variety of hairstyles. Sneaky in a good way. Saxophone extraordinary. Has 3 trucks. Good climber. Better friend.
there's absolutely nothing legal about this at all
A classic new england staple that your dad will probably like. I messed up the math so its extra alcoholic. We only brewed eight of them. Permanently Sold Out (forever).
Inspired by standards of living in the Soviet Union, this citrus surprise has also been discontinued. But for how long?
Inspired by bees, you shouldn't drive after drinking this strawberry-touched, never-oaked, plastic-aged honey beverage. We have like three gallons of it left.


--- layout: post title: "No Title" ---
After you’ve been running for 8+ hours every little thing becomes an incredible luxury; at mile 21 I drank a cup of flat Mountain Dew and I swear it tasted like unicorn tears. At mile 43 I ate a PB&J sandwich and it was like eating the entrails of a fallen angel.
The Oatmeal’s Matthew Inman ran an ultra marathon.
This is one of my favourite things about road cycling. At the end of a tough 6 or 7 hour ride you revert to your most basic instincts.


{% extends 'mainapp/home.html' %} {% block content %}
You can able to access to all the Notes.


Portfolio Construction Models have one primary method: $[CreateTargets(),M:QuantConnect.Algorithm.Framework.Portfolio.PortfolioConstructionModel.CreateTargets]. This method takes the algorithm object and a list of $[Insight,T:QuantConnect.Algorithm.Framework.Alphas.Insight] objects. You should seek to answer the question "how many shares/contracts should I buy based on the insight predictions I've been presented?"
Like all Algorithm Framework models, the Portfolio Construction Model also receives the $[OnSecuritiesChanged(),M:QuantConnect.Algorithm.Framework.Portfolio.PortfolioConstructionModel.OnSecuritiesChanged] event, which can optionally be used to perform actions when there are security additions or removals. If you are inheriting from the $[PortfolioConstructionModel,T:QuantConnect.Algorithm.Framework.Portfolio.IPortfolioConstructionModel] base class, this is an optional method.
// Portfolio construction scaffolding class; basic method args. class MyPortfolioConstructionModel : PortfolioConstructionModel { // Create list of PortfolioTarget objects from Insights List<IPortfolioTarget> CreateTargets(QCAlgorithmFramework algorithm, Insight[] insights) { } // OPTIONAL: Security change details void OnSecuritiesChanged(QCAlgorithmFramework algorithm, SecurityChanges changes) { // Security additions and removals are pushed here. // This can be used for setting up algorithm state } }
# Portfolio construction scaffolding class; basic method args. class MyPortfolioConstructionModel(PortfolioConstructionModel): # Create list of PortfolioTarget objects from Insights def CreateTargets(self, algorithm, insights): pass # OPTIONAL: Security change details def OnSecuritiesChanged(self, algorithm, changes): # Security additions and removals are pushed here. # This can be used for setting up algorithm state. # changes.AddedSecurities: # changes.RemovedSecurities: pass


Definition: One or more people navigate a vehicle into a designated space
Explication: Personal and passenger vehicles such as cars, trucks, motorcycles, boats, and planes are typically kept in a designated space while not in use. The driver of the vehicle must navigate the vehicle going either forward or reverse into the designated space. Personal land vehicles are most often parked in a garage (either attached or adjacent to one's house), in a paved, stone, or dirt drive-way next to one's house, on the street where vehicles are closely aligned parallel to the curb, or in a parking lot where painted lines indicate where one's vehicle is to be parked.
Many retail establishments, stores, malls, and other businesses have parking lots where customers and employees may park their vehicles while shopping or working. These typically contained painted lines and/or painted parking curbs that indicate a space where patrons are supposed to park their vehicles. Cities and towns often have paid parking spaces either metered on-street parking or in a parking garage or lot. Users of these parking spaces and facilities must pay in order to park their vehicles. Water vehicles such as boats and jet skis are often parked at a dock -- a human made structure spanning between land and a body of water. Water vehicles are navigated into a designated space at a dock, often between wood pylons, and are typically secured to the dock with ropes. When parking a helicopter, it may be flown to and landed in its parking space. When parking a fixed-wing aircraft, the aircraft is normally stopped and shut down near its parking space and then pushed into position (small light airplanes may be pushed entirely by hand, but in the case of larger aircraft a towbar is attached to the axle of the nose wheel or tail wheel and the towbar may be pushed/pulled by hand or may be attached to a tractor sort of vehicle if the plane is too heavy to be moved by hand.


--- layout: archive title: Zulip Chat Archive permalink: /stream/144837-PR-reviews/topic/.23427.20opens.html ---
This is a very mild refactor of the type of open sets of a topological space. Any comments welcome.
It also adds some equivalent formulations of a basis. Those proofs might require some obfuscation to be mathlib ready.
I could also take those out, if people prefer that.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


[§526-8] Disclaimer of interest by trustee. If a trustee disclaims an interest in property that otherwise would have become trust property, the interest does not become trust property. [L 2000, c 43, pt of §1]


France Earthquake: Four injured as tremors felt across country's south east
An 5.4 magnitude quake has struck in France's southeast in what authorities say is the largest tremor to hit the mainland since 2003
by Talia Shadwell, https://www.mirror.co.uk/authors/talia-shadwell/Southeastern France has been struck by an unusual 5.4 magnitude earthquake- the strongest tremour to hit the mainland in nearly two decades.
Four people were injured by the tremor, which was reportedly felt from Lyon to Montpellier when it struck just before noon, local time.
The quake struck the Ardèche region and did not cause any major damage, the French Central Seismological Office (BCSF) in Strasbourg said in a statement, according to Euronews .
The tremor was felt mainly in the Drôme and Ardèche regions and pictures show quake damage to some buildings in the eastern city of Le Teil.
Early reports suggest it is the strongest quake to hit mainland France since 2003, according to French media.
Have you been affected by the earthquake in France? Email<EMAIL_ADDRESS>It was reported to have been felt most intensely around Montélimar where a person was seriously injured by falling scaffolding.
Three other people were slightly injured in the Ardèche region "following a panic attack", the Drôme prefecture said on Twitter.
Le Monde reports the quake was a jolt of rare intensity for France, which gets around 600 earthquakes, but only 10 to 15 are usually felt a year.
According to the French Seismological Central Bureau, it was the strongest quake to hit mainland France in a magnitude 5.4 jolt struck in 2003 in the Vosges region.
The French news site reported that the quake's epicentre was a little over 10km from the Cruas nuclear power plant in Ardèche and about 30km from the site of the Tricastin power plant, and another, Orano, which processes nuclear fuel.
Authorities shut down all three reactors in order to carry out preventative checks.
However they did not show any immediate signs of damage, according to a statement from the operator, EDF.
The Nuclear Safety Authority confirmed that the earthquake had caused "no apparent damage" to the reactors, but requested that EDF to continue examining them before restarting them.


Register for Summer Camp!
Things to Note:
- Covid Form must be signed and brought to the first day of camp, otherwise that camper will not be allowed to join in the coding fun
- Money is Due 2 weeks in advance via cash/check or venmo
- 2 Weeks notice is required if there were to be a withdrawl of camper to get your money back
Child's Age:
Submit


Units of Measurement
There are commands to enter measurement units into your equations. Type for example \kg, \lbm, \m, \s, \kW, \day... Commands for measurement units are case sensitive!
Special cases: \deg (° - degree), \’ (minute of arc), \’’ (second of arc), \degC (°C), \ohm (resistance), \mn (minute)
Shortcuts for some compound units are also available: \mps (m/s), \radps (rad/s), \Apm (A/m), \kgpm (kg/m), \Vpm (V/m), \Nm (Nm), \Ns (Ns)
How to enter: kg/m3? Write the following command \kgpm, and then press ALT+3.
Measurement units are displayed in a bit pale color.


---
layout: default
title: Unsupervised Projection Models
---
Unsupervised Projection Models
Unsupervised Projection Models these methods fracture the input feature space using randomly drawn hyperplanes independently of the data distribution. Given the random nature of the learning procedure they are the fastest models at training time but suffer from the disadvantage of requiring long hashcodes and many hashtables to attain a reasonable level of retrieval effectiveness.
{% assign publicationsList = site.data.morantaxonomy | sort: "bibkey" %}
| Name | Codebook | Architecture | Optimisation |
{% for publication in publicationsList %}{% if publication.categories contains "independent" %}
{% assign pubDetails = site.publications | where:"bibkey", publication.bibkey %}
| {{pubDetails[0].authors}}, {{pubDetails[0].year}}. {{pubDetails[0].title}} |
{{publication.codebook}} |
{{publication.type}} |
{{publication.optimisation}} |
{% endif %}{% endfor %}


Upcoming Events
Vision
Unnat Bharat Abhiyan is inspired by the vision of transformational change in rural development processes by leveraging knowledge institutions to help build the architecture of an Inclusive India.
Mission
The Mission of Unnat Bharat Abhiyan is to enable higher educational institutions to work with the people of rural India in identifying development challenges and evolving appropriate solutions for accelerating sustainable growth. It also aims to create a virtuous cycle between society and an inclusive academic system by providing knowledge and practices for emerging professions and to upgrade the capabilities of both the public and the private sectors in responding to the development needs of rural India.
Goals
1)To build an understanding of the development agenda within institutes of Higher Education and institutional capacity and training relevant to national needs, especially those of rural India.
2) To re-emphasize the need for fieldwork, stake-holder interactions and design for societal objectives as the basis of higher education.
3) To stress on rigorous reporting and useful outputs as central to developing new professions.
4) To provide rural India and regional agencies with access to the professional resources of the institutes of higher education, especially those that have acquired academic excellence in the field of science, engineering and technology, and management.
5) To improve development outcomes as a consequence of this research. To develop new professions and new processes to sustain and absorb the outcomes of the research.
6) To foster a new dialogue within the larger community on science, society and the environment and to develop a sense of dignity and collective destiny.
How To Participate ?
You are welcome to participate in the Unnat Bharat Abhiyan in any of the following capacity as per your present status, competence and interest:
1) As a prospective Mentoring Institute
2) As a Participating Institute
3) As a Subject Expert
4) As a Voluntary Organization
5) As a Developmental Agency
6) As a Philanthropist or a CSR Promoter
8) As NSS Member
9) As an Enthusiastic Volunteer
UBA Cell of IIT Palakkad
IIT Palakkad has joined UBA in 2018 as a participating Institute. It become the Regional Co-ordinating Institute of north Kerala districts in 2019. IIT Palakkad has started working on science awareness and reachability by organizing science lecture series for common people names “Pale blue dot public lecture series”. Along with education, it is also working on renewable energy, water management, waste management, and agriculture.


{% extends "layout.html" %} {% block title %}Edit Vehicle{% endblock %} {% block content %}
Select a different image to upload (jpg, png, gif, 4 MB max size):


Developer of this landing page: Sergei
It was actually my first big team project, thanks to my team for their effort and great attitude!
MY GITHUBIt's an open license student project, we'd be glad to have your feedback.
OPEN GITHUBIt was actually my first big team project, thanks to my team for their effort and great attitude!
MY GITHUBDuring the week we spent doing this project Remi was our wise and seasoned mentor. Our work would be much harder without him!
REMI'S GITHUBLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
RODRIGO'S GITHUBLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
MELQUI'S GITHUBLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
DOM'S GITHUBLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
APETSI'S GITHUB


We artists are a different breed of people. We're a happy bunch. When you do it your way you can go anywhere you choose. Go out on a limb - that's where the fruit is. Just make little strokes like that. This is where you take out all your hostilities and frustrations. It's better than kicking the puppy dog around and all that so. It's life. It's interesting. It's fun.
Just think about these things in your mind and drop em' on canvas. Nothing wrong with washing your brush. Happy painting, God bless. Decide where your cloud lives. Maybe he lives right in here.
Let's put a touch more of the magic here. Absolutely no pressure.  Isn't it fantastic that you can change your mind and create all these happy things?  Any little thing can be your friend if you let it be.


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Passive progress indicators represent sequential steps in processes outside of user control.
Use passive progress indicators when users must be aware of sequential progress that they are not responsible for.
Don't use passive progress indicators for tasks that require user interaction. Use waterfall progress indicators or wizards instead.
Don’t use passive progress indicators to represent independent steps or statuses that are not sequential.
Don't use passive progress indicators simultaneously for multiple items in lists.
You can provide additional details about completed or current steps. Use step details to provide extra context to users, but avoid too many details or the implication that users should take action.
Be concise in step labels. For completed steps, use past tense verbs ("Submitted," "Approved") and include datestamps in parentheses. Only include timestamps if the extra detail is necessary. For pending steps, use present tense verbs or gerunds ("Submitting", "Awaiting").
Use step details sparingly, and be concise.
The progress indicator nav button component allows users to navigate the steps in modal wizards. We recommend against using it in waterfall pages and passive progress indicators.


Interrupt controllers on the x86 platform are responsible for receiving interrupt signals from devices, mapping the signal to an IDT vector, and then interrupting one or more CPUs in the system with the IDT vector. The x86 platform has some extra quirks, however. First, due to limitations with the original interrupt controllers and busses used on the PC-AT, separate programmable interrupt routers were added to the platform to sit in between PCI interrupt signals and the PC-AT interrupt controllers. Second, as the x86 platform continued to progress, an entirely new set of interrupt controllers, known as Advanced Programmable Interrupt Controllers (APICs), were introduced. In order to preserve backwards compatibility, systems with APICs also still include the PC-AT interrupt controllers and either system can be used to handle interrupts on modern systems. It is even possible to use both at the same time though doing so is discouraged.
The original PC-AT included two 8259A Programmable Interrupt Controllers (PICs) chained together. As with many other aspects of the PC-AT, this setup became part of the de facto standard for the x86 platform. Each 8259A has eight interrupt input signals that are assigned to eight consecutive IDT vectors. Two PICs thus yields sixteen total interrupt inputs. On the PC-AT these signals were known as ISA IRQs 0 through 15. However, the second 8259A (known as the slave PIC) is connected to the third input pin on the first 8259A (known as the master PIC). Thus, ISA IRQ 2 is not available for device interrupts, and there are really only fifteen interrupt inputs available for device interrupts.
The original PC-AT also used an ISA bus for its devices. ISA interrupts are edge triggered and are asserted by having the device raise the signal from low to high. This inhibits sharing of ISA interrupts by multiple devices, so each ISA device requires a dedicated interrupt input on the 8259As. All PC-AT compatible systems included an ISA timer which used IRQ 0, a keyboard controller that used IRQ 1, and a real time clock which used IRQ 8. The optional floating point co-processor used IRQ 13 if it was present. When PCI was introduced, most PC-AT compatible systems included two serial ports which used IRQs 3 and 4, a floppy controller which used IRQ 6, a line printer port which used IRQ 7, a PS/2 mouse port which used IRQ 12, and two IDE controllers which used IRQs 14 and 15. This left only IRQs 5, 9, 10, and 11 for PCI interrupts to use.
To make matters even more complicated many systems included other ISA devices such as additional serial or printer ports or sound cards. Each of these additional ISA devices also required a dedicated IRQ. Sound cards, for example, often used IRQ 5. Thus, the set of IRQs available for use by PCI interrupts was not fixed. Rather, simply adding or removing an ISA peripheral could change the set across reboots. To deal with this complication, programmable interrupt routers were added.
A programmable interrupt router is used to route PCI interrupt signals to interrupt inputs on another interrupt controller. A router contains several input signals and output signals. Each output signal is hooked up to an input on an interrupt controller. Each input signal can be routed to one of the output signals. Multiple input signals can be routed to the same output signal. Multiple PCI interrupt signals can be routed to a single input signal.
System software, such as the BIOS or operating system, is responsible for programming the interrupt router. Programming the router consists of routing each input signal that is in use to an output signal. For example, a PC-AT compatible system might have the output pins from the programmable interrupt router hooked up to the interrupt lines for IRQs 3, 4, 5, 7, 9, 10, and 11 on the 8259A PICs. If IRQs 3, 4, and 7 are in use by ISA devices, then each input pin on the interrupt router must be routed to one of the IRQs 5, 9, 10, or 11. Note that routing a single input pin (also known as a PCI Link Device) to an IRQ routes all of the PCI interrupts connected to that input pin to the IRQ. That is, one can't arbitrarily route individual PCI interrupts at will. Instead, one can only route a group of PCI interrupts that are connected to an input pin. This grouping is set in the hardware and cannot be altered by system software. Also, if a system has more input pins than available IRQs, then at least some of the input pins will be routed to the same IRQ resulting in the union of all the PCI interrupts on those input pins sharing the same IRQ.
An example of using a programmable interrupt router in combination with the 8259A PICs can be found in Figure 1. On the left are six PCI slots. The INTA# pin from each slot is connected to one of the input pins on the interrupt router, which is labeled ``PIR.'' Notice that some of the PCI interrupts are wired to the same input pin on the interrupt router. For example, the first two interrupts are both connected to the LNKA input pin. The interrupt router also has four output pins that are connected to input pins on the two 8259A controllers corresponding to IRQs 5, 9, 10, and 11. Suppose that LNKA is routed to O0, LNKB is routed to O1, LNKC is routed to O2, and LNKD is routed to 00. Then the interrupts for PCI slots 0, 1, and 5 would be routed to IRQ 5. The interrupt for PCI slot 2 would be routed to IRQ 11, and the interrupts for PCI slots 3 and 4 would be routed to IRQ 10.
Many x86 systems, including most recent systems, include a second set of interrupt controllers known as APICs. In these systems, each CPU includes a local APIC which receives interrupt messages and uses them to assert interrupts on the CPU. The chipset includes one or more I/O APICs which are responsible for converting device interrupt signals into messages that are delivered to one or more local APICs.
One of the biggest differences between the 8259A PICs and I/O APICs is that the pins on I/O APICs are completely independent. With the 8259A PICs, the eight input pins are mapped to eight consecutive IDT vectors, and all of the interrupts are sent to the same CPU. I/O APICs, on the other hand, do not have any controller-wide settings. Instead, each pin is programmed independently. Each pin is assigned its own IDT vector by the operating system and can be mapped to one or more CPUs. I/O APICs can also contain a variable number of pins. Typically an I/O APIC contains 16, 24, or 32 input pins.
PCI interrupt signals are routed to I/O APIC interrupt pins in several different ways. The earliest APIC systems include a single I/O APIC with 16 input pins that simply replicate the functionality of the two 8259A PICs. In these systems, the 16 input pins are used for the 16 ISA IRQs, and PCI interrupts are routed onto the ISA IRQs using a programmable interrupt router. Most APIC systems, however, use dedicated I/O APIC input pins for PCI interrupt signals. In these systems, the first 16 pins on the first I/O APIC are used for the 16 ISA IRQs. PCI interrupt signals are connected to other input pins on the first I/O APIC (if it contains more than 16 input pins) as well as input pins on additional I/O APICs (if present). Some very recent systems have begun routing some of the PCI interrupt signals to a programmable interrupt router whose output pins are connected to a set of I/O APIC input pins that are dedicated to PCI interrupts.
Figure 2 contains an example of a system with a 24-pin I/O APIC where the PCI interrupts are connected directly to input pins on the I/O APIC. As with the previous figure, there are six PCI slots on the left, and the INTA# pin from each slot is connected to one of the input pins on the I/O APIC. A system may still have shared PCI interrupts even when using APICs if multiple interrupt lines are connected to the same I/O APIC input pin. For example, the first two interrupts for PCI slots 0 and 1 are both connected to I20 input pin. The other interrupts are all routed to their own input pin: PCI slots 2, 3, 4, and 5 are routed to input pins I19, I18, I17, and I16, respectively.


|
FlatBuffers
An open source project by FPL.
|
A Builder is used to construct one or more FlatBuffers. More...
A Builder is used to construct one or more FlatBuffers.
Typically, Builder objects will be used from code generated by the flatc
compiler.
A Builder constructs byte buffers in a last-first manner for simplicity and performance during reading.
Internally, a Builder is a state machine for creating FlatBuffer objects.
It holds the following internal state:
Public Member Functions | |
| def | __init__ (self, initialSize) |
Initializes a Builder of size initial_size . More... | |
| def | CreateByteVector (self, x) |
| CreateString writes a byte vector. More... | |
| def | CreateString (self, s, encoding='utf-8', errors='strict') |
| CreateString writes a null-terminated byte string as a vector. More... | |
| def | EndVector (self, vectorNumElems) |
| EndVector writes data necessary to finish vector construction. More... | |
| def | Finish (self, rootTable) |
Finish finalizes a buffer, pointing to the given rootTable . More... | |
| def | FinishSizePrefixed (self, rootTable) |
| def | Head (self) |
| Get the start of useful data in the underlying byte buffer. More... | |
| def | Output (self) |
| Return the portion of the buffer that has been used for writing data. More... | |
| def | PrependBool (self, x) |
Prepend a bool to the Builder buffer. More... | |
| def | PrependByte (self, x) |
Prepend a byte to the Builder buffer. More... | |
| def | PrependFloat32 (self, x) |
Prepend a float32 to the Builder buffer. More... | |
| def | PrependFloat64 (self, x) |
Prepend a float64 to the Builder buffer. More... | |
| def | PrependInt16 (self, x) |
Prepend an int16 to the Builder buffer. More... | |
| def | PrependInt32 (self, x) |
Prepend an int32 to the Builder buffer. More... | |
| def | PrependInt64 (self, x) |
Prepend an int64 to the Builder buffer. More... | |
| def | PrependInt8 (self, x) |
Prepend an int8 to the Builder buffer. More... | |
| def | PrependUint16 (self, x) |
Prepend an uint16 to the Builder buffer. More... | |
| def | PrependUint32 (self, x) |
Prepend an uint32 to the Builder buffer. More... | |
| def | PrependUint64 (self, x) |
Prepend an uint64 to the Builder buffer. More... | |
| def | PrependUint8 (self, x) |
Prepend an uint8 to the Builder buffer. More... | |
| def | PrependUOffsetTRelative (self, off) |
| Prepends an unsigned offset into vector data, relative to where it will be written. | |
Public Attributes | |
| Bytes | |
The internal bytearray for the Builder. More... | |
| finished | |
| A boolean determining if the Builder has been finalized. More... | |
| def python.flatbuffers.builder.Builder.__init__ | ( | self, | |
| initialSize | |||
| ) |
Initializes a Builder of size initial_size
.
The internal buffer is grown as needed.
| def python.flatbuffers.builder.Builder.CreateByteVector | ( | self, | |
| x | |||
| ) |
CreateString writes a byte vector.
| def python.flatbuffers.builder.Builder.CreateString | ( | self, | |
| s, | |||
encoding = 'utf-8' , |
|||
errors = 'strict' |
|||
| ) |
CreateString writes a null-terminated byte string as a vector.
| def python.flatbuffers.builder.Builder.EndVector | ( | self, | |
| vectorNumElems | |||
| ) |
EndVector writes data necessary to finish vector construction.
| def python.flatbuffers.builder.Builder.Finish | ( | self, | |
| rootTable | |||
| ) |
Finish finalizes a buffer, pointing to the given rootTable
.
| def python.flatbuffers.builder.Builder.Head | ( | self | ) |
Get the start of useful data in the underlying byte buffer.
| def python.flatbuffers.builder.Builder.Output | ( | self | ) |
Return the portion of the buffer that has been used for writing data.
This is the typical way to access the FlatBuffer data inside the builder. If you try to access Builder.Bytes
directly, you would need to manually index it with Head()
, since the buffer is constructed backwards.
It raises BuilderNotFinishedError if the buffer has not been finished with Finish
.
| def python.flatbuffers.builder.Builder.PrependBool | ( | self, | |
| x | |||
| ) |
Prepend a bool
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependByte | ( | self, | |
| x | |||
| ) |
Prepend a byte
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependFloat32 | ( | self, | |
| x | |||
| ) |
Prepend a float32
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependFloat64 | ( | self, | |
| x | |||
| ) |
Prepend a float64
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependInt16 | ( | self, | |
| x | |||
| ) |
Prepend an int16
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependInt32 | ( | self, | |
| x | |||
| ) |
Prepend an int32
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependInt64 | ( | self, | |
| x | |||
| ) |
Prepend an int64
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependInt8 | ( | self, | |
| x | |||
| ) |
Prepend an int8
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependUint16 | ( | self, | |
| x | |||
| ) |
Prepend an uint16
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependUint32 | ( | self, | |
| x | |||
| ) |
Prepend an uint32
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependUint64 | ( | self, | |
| x | |||
| ) |
Prepend an uint64
to the Builder buffer.
| def python.flatbuffers.builder.Builder.PrependUint8 | ( | self, | |
| x | |||
| ) |
Prepend an uint8
to the Builder buffer.
| python.flatbuffers.builder.Builder.Bytes |
The internal bytearray
for the Builder.
| python.flatbuffers.builder.Builder.finished |
A boolean determining if the Builder has been finalized.


Implement a class named LogEntry, which will hold relevant information for a report. (Severity, Date and Time, Message)
Define an interface named ILog, with the following actions:
Write different implementations for your ILog interface:
Implement a general Logger class which will hold a certain ILog, and expose writing, reading and clearing actions.
Every application needs error handling. Implement the following custom errors:
Create a console application project, which receives as input the user's name, and then will present him with four options:
NOTES:
* Write every action performed by this application to the log.
* When "Administration" is selected, display every log entry written so far.
* In case of an exception, present the user with a proper message.


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
Using a sharp knife, trim the sea bass fillets into a square shape, then cut into the skin side to lightly score.
Rub the fillets with olive oil and season with salt and a pinch of white pepper and ground coriander.
Heat a frying pan until hot and add the sea bass, skin-side down. Fry for three minutes, then turn and cook for a further 1-2 minutes, or until completely cooked through.
For the fennel pesto, place the fennel into a food processor and blend to a fine purée.
Add the dill, pine nuts, ground almonds and parmesan and pulse to combine.
Add the olive oil and blend to a porridge-like consistency. Season, to taste, with salt and freshly ground black pepper.
For the tomato salsa, place the tomatoes into a bowl and add the lemon juice, sesame oil, Tabasco sauce and coriander leaves. Stir gently to combine.
To serve, place a spoonful of fennel pesto into the centre of each plate. Place a sea bass fillet on top of each and spoon the salsa around. Garnish with a few pea shoots and serve.


--- layout: default title: guicarneiro.com description: Software engineering sharing some learnings and adventures. image: /images/citysky.jpg --- {% include about.html %}


1. Make sure the latest version of ipf.m
is in the Matlab path. Use the Matlab load or
File > Import
data command to get your data into
the Matlab workspace assingle vector, a pair of vectors
(x and y), or a matrix with the
independent variable (x) in the first column and the dependent
variable (y) in the second column (e.g.
"mydata").
2. Type ipf(y); or ipf(x,y); or ipf(mydata);
3. Matlab displays the data in the Figure window, with the
entire signal in the lower panel and a zoomed-in section in the
top panel. (In the figure below, the data are from the demo
script Demoipf.m.
To use those data, download Demoipf.m, place it in the Matlab
path, and type "Demoipf" at the command prompt; the "true"
values of the peaks without noise are printed out in the command
window for comparison to your results). Note: Make sure you
don't click on the “Show Plot Tools” button in the toolbar
above the figure; that will disable normal program
functioning. If you do; close the Figure window and start
again.
4. Use the left and right cursor keys to
pan back and forth across the signal...
To pan faster, use the < and
> keys. To pan by one point, use the [ and ]
keys.
Use the up and down cursor
keys to zoom in and out.
To zoom faster, use the / and ' keys.
5. To fit a peak, isolate and center that peak in the upper
window, ....
6. ... select the number of peaks by pressing a number key
between 1 and 9 (1 in this case), the peak shape (G
= Gaussian in this case), and press F (for Fit).
The best-fit line is shown in red in the upper panel, superimposed
on the data points, along with the peak position, height, and
width of the best fit model. The bottom panel displays the
residuals (difference between the best-fit line and the data). The
current number of peaks, the shape, and the percent fitting error
are shown at the bottom of the window. Press the R key to
print out the table of results in the command window.
7. Press the F key again to
compute another fit with slightly different starting first
guesses. This demonstrates how stable the fit is with
respect to variations in starting points (first guesses). Press R to print a report of the best-fit peak
parameters in the command window.
The percent fitting error are refreshed at the bottom of the
window.
Twenty different peaks shapes are available by keystroke
(e.g. L=Lorentzian, U=exponential pulse, S=sigmoid
(logistic function), etc). Press K to see a list of all
commands. You can also select the shape by number from an even
larger menu of shapes by pressing the - (minus) key.
8. Here's another example using the same signal: to fit the
group of three overlapping peaks near x=800, press the 3
key, use the pan and zoom to isolate that group and try to line
up the peaks with the magenta dotted vertical line markers, then
press F.
Each time you press F the fit is repeated with
slightly different starting first guesses. Keep your eye on
the fitting error and stop when the error is low. The
green lines in the upper panel show the individual
model components; the red line is the sum of those
components.
9. If the fit seems unstable, press the X key to perform
10 silent fits and display the one with the lowest fitting
error. Press R to print a report of the best-fit peak
parameters in the command window.
Percent Fitting Error 1.6439% Elapsed time =
1.3387 sec. Peak#
Position
Height
Width Area
1 800.15
3.0067
29.995 96.001
2 849.71
1.9867
39.633 83.814
3 899.4
1.0122
51.476 55.462
10. If the peaks don't line up under the magenta dotted
vertical lines, you can manually specify the first-guess peak
positions: press C, then click on your estimates of the
peak positions in the upper graph, once for each peak. A fit is
automatically performed after the last click. Peaks are numbered
in the order clicked.
11. In the figure below, using data from the demo script Demoipf2.m, the peaks are superimposed
on a gradual curving baseline. To correct for the baseline, use
the T key to cycle between the four baseline correction
("autozero") modes: None, Linear, Quadratic,
and Flat. Pan and zoom each group of peaks so that the
signal returns to the local baseline at the edges of the
selected region in the upper panel, then press F. In the
sequence shown below, a pair of peaks near x=600 is selected and
fit, first without baseline subtraction, then with linear,
and then quadratic, baseline correction. The latter two
modes work best in this case.
The current baseline correction mode is displayed at the
top of the window.
12. Alternatively, you may use multipoint background correction
to subtract a linearly-interpolated baseline for the entire
signal: press the Backspace key, type in the desired
number of background points (14 in the example below) and press
the Enter key, then click where you estimate the
baseline to be in the lower panel, starting at the left of the
lowest x-value and ending to the right of the highest x-value.
(For greatest precision, you can maximize the figure window
before this operation). After the last click, the baseline is
subtracted; then you can continue with curve fitting. (If you
mess up, press the \ key to restore the original
background and start over). When you are done, you can measure
the peaks without baseline subtraction.
The y-axis label of the bottom panel changes accordingly.
13. Some peak shapes have an extra variable
parameter that modifies the shape: the Voigt profile,
Pearson, exponentially-broadened Gaussian (ExpGaussian),
exponentially-broadened Lorentzian (ExpLorentzian), bifurcated
Gaussian, bifurcated Lorentzian, or Gaussian/Lorentzian blend.
For those shapes, you control that extra variable parameter with
the A and Z keys and adjust it to minimize the
fitting error. The current value is displayed at the bottom of
the window. In this example, the single peak near x=2800 in the
file "DataMatrix3" is fit, first with a Gaussian and
then with an exponentially broadened Gaussian (E
key), adjusting the extra parameter (the time constant)
to minimize the fitting error.
>> load DataMatrix3
>> ipf(DataMatrix3)
14. Press Q to print out a report in the command window.
Peak Shape = Exponentially-broadened Gaussian
No baseline correction
Number of peaks = 2
Time Constant = 33.1919
Fitted x range = 1663.5 - 2050.5 (dx=387)
(Center=1857)
Percent Fitting Error = 0.090216% Peak#
Position
Height
Width Area
1
1800.4
1.8632
60.057 119.11
2 1900.6
0.48346
59.62 30.67
15. To test the stability of your fit with respect to random
noise, press the N key a few times. That will perform
fits on subsets of data points (called "bootstrap samples").
If the N key gives reasonable-looking fits with peak
parameters that vary from trial to trial, then you can determine
the variability of the peak position, height, width, and area by
pressing the V key, which will calculate the standard
deviation of all the peak parameters of all the peaks in 100
such bootstrap sub-samples (this may take a minute or so). You
will be asked for the number of trials per bootstrap sample;
start with 1 and increase it if the fit is not stable:
Number of fit trials per bootstrap sample (0 to cancel): 1 Peak
#1
Position
Height
Width Area Bootstrap Mean:
1200.004
1.9967714 100.31494 213.20131 Bootstrap STD:
0.1832
0.0059565 0.37247
0.7652 STD based on IQR:
0.27681
0.0075577 0.53384
1.1063 Percent RSD:
0.015266
0.29831
0.3713 0.35891 %STD based on IQR:
0.015067
0.2985
0.37216 0.35992 Elapsed time is 3.060255 seconds. ..and so
on for Peak #2 and the other peaks if a multi-peak fit.
On the other hand, if the N key gives wildly
different fits, with highly variable fitting errors and
peak parameters, then the fit is not stable, and you
should try to increase the number of trials when asked (but of
course that will increase the time it takes to complete). If
that does not help, use another model or a better data set.
16. Press K
to display the complete set of keystroke commands. Click here
for more details.


The pyglet.image.load function returns an AbstractImage. The actual class of the object depends on the decoder that was used, but all images support the following attributes:
The anchor point defaults to (0, 0), though some image formats may contain an intrinsic anchor point. The anchor point is used to align the image to a point in space when drawing it.
You may only want to use a portion of the complete image. You can use the get_region method to return an image of a rectangular region of a source image:
image_part = kitten.get_region(x=10, y=10, width=100, height=100)
This returns an image with dimensions 100x100. The region extracted from kitten is aligned such that the bottom-left corner of the rectangle is 10 pixels from the left and 10 pixels from the bottom of the image.
Image regions can be used as if they were complete images. Note that changes to an image region may or may not be reflected on the source image, and changes to the source image may or may not be reflected on any region images. You should not assume either behaviour.


Lemme Smash Meme.
(That You Can Pet)
Sends A Random One Each Time
Cute Gif Of Cat Jumping On Someone's Face
If you mention someone, text will be added saying that you turned into a cat and jumped on them.
Funny Cat Gif
Cute Gif Of A Cat Making A Funny Gesture
Mmmmm...
Adorable Fox Gif
No Breaks!
For When Someone Is Being Lewd In Chat
For When Someone Just Doesn't Understand
Good Picture To Cheer Someone Up
Good Meme To Make Someone Say, "Wtf?"
For When Someone Is Spoiling All The Fun
Scared/Shy Gif
Will Say You Are Triggered
If you mention someone, text will be added saying that you are triggered at them.
"Everyone in the world is a little potato.  This is a prophecy."


public class Overlay
An overlay that will show when an class ExpandableFab
is clicked in order to partially or fully
obscure the screen's content, allowing the class ExpandableFab
and class FabOption
s to become more
apparent.
Developer Notes:
If you would like the Overlay to cover the entire screen, layout_width and layout_height must both be set to match_parent (assuming the parent ExpandableFabLayout has no size restrictions).
Overlays must be defined within an class ExpandableFabLayout
to function properly.
To ensure that Overlays cover screen content but NOT the ExpandableFab widget itself, ensure the Overlay is the first child of ExpandableFabLayout via XML, or the first view passed to ExpandableFabLayout's addView/addViews methods via code.
Implementation Notes:
Since the Kotlin 'internal' modifier translates to 'public' in Java, the JvmSynthetic annotation is used on those functions and properties to hide them from the published API for Java clients. A proper solution to this issue would be a package-private visibility modifier, but Kotlin has yet to implement it (https://youtrack.jetbrains.com/issue/KT-29227). Until then, the JvmSynthetic annotations should remain in order to present the proper published API to both Java & Kotlin clients.
public Overlay(@NotNull android.content.Context context, @Nullable Orientation orientation)
Used to create an Overlay programmatically (do not use the other constructor Overlay(context, attributeSet) - it is for use by the Android framework when inflating an Overlay via XML). This constructor keeps all optional properties of an Overlay at their default values, though you can always change these values after instantiation by using the appropriate setter methods (with the exception of orientation, which cannot be changed after instantiation).
See documentation for an exhaustive list of all optional properties and their default values.
Please review the Notes documented at the top of the class for guidelines and limitations when using Overlay.
public Overlay(@NotNull android.content.Context context, @NotNull android.util.AttributeSet attributeSet)
Called by the system when creating an Overlay via XML (don't call this directly). To create an Overlay programmatically, use the Overlay(context, orientation) constructor.
@NotNull public Orientation getOrientation()
The enum Orientation
this Overlay is viewable in. Default value is Orientation.PORTRAIT.
enum Orientation
public int getOverlayColor()
The color of the overlay. Default value is white.
Usage of this property is preferred over the inherited setBackgroundColor method.
public void setOverlayColor(int value)
The color of the overlay. Default value is white.
Usage of this property is preferred over the inherited setBackgroundColor method.
public float getOverlayAlpha()
The opacity of the overlay as a positive float, where 0 is completely transparent and 1 is completely opaque. Default value is 0.78431f.
Usage of this property is preferred over the inherited set/getAlpha methods.
public void setOverlayAlpha(float value)
The opacity of the overlay as a positive float, where 0 is completely transparent and 1 is completely opaque. Default value is 0.78431f.
Usage of this property is preferred over the inherited set/getAlpha methods.
public long getOpeningAnimationDurationMs()
The duration (in milliseconds as a positive long) of the animations that will be played when this Overlay is being shown from a hidden state (when the ExpandableFab is opening). Default value is 300L.
public void setOpeningAnimationDurationMs(long value)
The duration (in milliseconds as a positive long) of the animations that will be played when this Overlay is being shown from a hidden state (when the ExpandableFab is opening). Default value is 300L.
public long getClosingAnimationDurationMs()
The duration (in milliseconds as a positive long) of the animations that will be played when this Overlay is being hidden from a visible state (when the ExpandableFab is closing). Default value is 300L.
public void setClosingAnimationDurationMs(long value)
The duration (in milliseconds as a positive long) of the animations that will be played when this Overlay is being hidden from a visible state (when the ExpandableFab is closing). Default value is 300L.
public void setOnClickListener(@Nullable android.view.View.OnClickListener onClickListener)
Registers a callback to be invoked when this Overlay is clicked. The default behavior the Overlay will be executed before this custom callback.


We provide multiple layout options so that you can choose a great website. We provide layouts for blogs, portfilios, landing pages, E-Commerce stores, resumés, and more!
We offer fully responsive websites. Our websites work on every electronic device.
Ex: Phone,Laptop,Desktop,Tablet, etc.
Our websites are bug free and we offer monthly maintenance for an additional fee.
Email us specifying which template you would like for your website and what you want on it. Once you do that, we will then give you a quote based on what you want for your website. Our contact information is here
For an extra fee, we will provide you with a domain name and maintenance.
For an aditional fee, we will host your website for you.
CEO @ Packer Collegiate Institute
Lead Web Developer @Packer Collegiate Institute
Web Developer @ Duke University
Web Developer @Boston College
Web Developer @ HS for Math Science and Engineering
Web Developer @ Bronx Science
Our team is hard working and dedicated to making the best website possible for you.


public abstract class AbstractModel extends java.lang.Object implements Model
| Constructor and Description |
|---|
AbstractModel() |
| Modifier and Type | Method and Description |
|---|---|
long |
createPlayerIdentity() |
AuthorizationPromise |
getAuthorizationPromise(java.lang.Long identity)
Get an AuthorizationPromise
|
ItemInstance.EquipmentInstance |
getEquipmentInstance(long id) |
ItemPrototype.EquipmentPrototype |
getEquipmentPrototype(long staticID) |
ItemInstance |
getItemInstance(long id) |
ItemPrototype |
getItemPrototype(long staticID) |
Player |
getPlayer(java.lang.Long id)
Get the player object for a given identity
|
Player |
loadPlayer(AuthorizationPromise promise)
Load a user when the identity is sent for the first time to the game server
|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
createAuthorizationPromise, createCharacter, isAuthorised, setProficiency
public long createPlayerIdentity()
public ItemPrototype getItemPrototype(long staticID) throws AccessException
getItemPrototype
in interface Model
AccessException
public ItemPrototype.EquipmentPrototype getEquipmentPrototype(long staticID) throws AccessException
getEquipmentPrototype
in interface Model
AccessException
public ItemInstance getItemInstance(long id) throws AccessException
getItemInstance
in interface Model
AccessException
public ItemInstance.EquipmentInstance getEquipmentInstance(long id) throws AccessException
getEquipmentInstance
in interface Model
AccessException
public AuthorizationPromise getAuthorizationPromise(java.lang.Long identity)
Model
getAuthorizationPromise
in interface Model
public Player getPlayer(java.lang.Long id)
Model
public Player loadPlayer(AuthorizationPromise promise) throws AccessException
Model
loadPlayer
in interface Model
AccessException


Video game designers usually work as part of a team to make games. We come up characters, story, concepts, and gameplay. Most designers have to work with other programmers and artists to create scripting language and the artistic vision for a video game.


CSPICE_ROTMAT calculates the rotation matrix generated by
a rotation of a specified angle about a specified axis applied
to a matrix. This rotation is thought of as rotating the
coordinate system.
Given:
m1 the matrix to apply the rotation. In matrix algebra, the
components of the matrix are relative to one particular
coordinate system. Applying cspice_rotmat changes the
components of 'm1' so that they are relative to a rotated
coordinate system.
[3,3] = size(m1); double = class(m1)
angle the angle in radians through which to rotate the original
coordinate system.
[1,1] = size(angle); double = class(angle)
iaxis the index for the axis of the original coordinate system
about which to perform the rotation by 'angle'.
'iaxis' = 1,2 or 3 respectively designates the x-, y-,
or z-axis.
[1,1] = size(iaxis); int32 = class(iaxis)
the call:
mout = cspice_rotmat( m1, angle, iaxis)
returns:
mout matrix resulting from the application of 'angle' to the
input matrix 'm1'.
[3,3] = size(mout); double = class(mout)
If
[angle]
iaxis
denotes the rotation matrix by 'angle' radians about 'iaxis',
(see the Rotations Required Reading document) then 'mout' is
given by the following matrix equation:
mout = [angle] * m1
iaxis
Any numerical results shown for this example may differ between
platforms as the results depend on the SPICE kernels used as input
and the machine specific arithmetic implementation.
%
% Rotate the 3x3 identity matrix by 90 degrees about
% the y axis.
%
%
% Create the 3x3 identity matrix.
%
ident = eye(3);
%
% Rotate 'ident' by Pi/2 about the Y axis.
%
r = cspice_rotmat( ident, cspice_halfpi, 2 )
MATLAB outputs:
r =
0.0000 0 -1.0000
0 1.0000 0
1.0000 0 0.0000
None.
For important details concerning this module's function, please refer to
the CSPICE routine rotmat_c.
MICE.REQ
ROTATION.REQ
-Mice Version 1.1.1, 10-MAR-2015, EDW (JPL)
Edited I/O section to conform to NAIF standard for Mice documentation.
-Mice Version 1.1.0, 24-JAN-2009, EDW (JPL)
Corrected the function definition name. This wrapper had a
the function name "cspice_rotate" instead of "cspice_rotmat."
-Mice Version 1.0.0, 17-JAN-2006, EDW (JPL)
rotate a matrix
|


Add or update work
Name
Price
Duration
Description
Target customer
Retail
Corporate
Cancelable by customer?
Yes
No
Save


2020 Genesis G90 To Make U.S. Debut At Los Angeles Auto Show
The flagship sedan will finally reach the States this November.
by Jacob OlivaIt has been almost a year since Genesis has revealed the refreshed version of the KDM-spec G90 sedan and limousine. It's the brand's answer to Mercedes' Maybach and it isn't without merit, really.
While we previously reported that the new G90 won't make its U.S. debut soon, it seems like Hyundai's luxury brand is ready to grace the Western market with its flagship sedan. In a report by CarBuzz, the mentioned refreshed versions of the G90 will finally make their U.S. launch – and it's this month at the Los Angeles Auto Show.
Gallery: Genesis G90 facelift (KDM Spec)
In CarBuzz's report, the Korean automaker has confirmed that the Genesis flagship will be shown to the public on November 20th at the famous motor show in California. Of note, the new G90 has been offered to other markets other than the U.S., so this November reveal is warranted, to say the least, given the importance of luxury brands in the American market.
As for its new look, the refreshed G90 will, of course, don the new triangular grille, along with the split headlights and taillights. While the design is a far cry from the old G90, the engine is expected to remain the same for the revamped model.
Meanwhile, Genesis Is Preparing To Launch Its Crossovers As Well:
Under the hood of the new G90 will be the same 3.3-liter twin-turbo V6 that produces 365 horsepower (272 kiloWatts) and 379 pound-feet (514 Newton-meters) of torque. The 5.0L V8 should also make a comeback, making 419 hp (313 kW) and 383 lb-ft (520 Nm) torque.
As for the pricing, well, we all have to wait until November 20th before we get to know how Genesis will price its flagship model. Of course, you can bet your bottom dollar that we'll be on top of that towards the end of the month.
Source: CarBuzz


VarkCrona
#stayhome
Personal Information
Name
Phone No
Age
Gender
-
Male
Female
Country
State
Medical Information
Travel History (14 Days)
-
Yes
No
Contact History (with COVID 19 Patient)
-
Yes
No
Drug History
-
Yes
No
Surgical History of Transplant
-
Yes
No
Smoker
-
Yes
No
Symptoms
Mild
Dry Cough
Fever, chills or sweating
Shortness of breath (not severe)
Sore throat
Myalgia (Body pain, muscle pain)
Gastrointestinal symptoms (Diarrhea, vomiting)
Severe
Shortness of breath (more difficult to breathe)
Coughing blood (about 1 tablespoon of blood)
Critical
Gasping for air, really difficult to breathe (Hypoxia)
Bluish discoloration of skin and lips (Cyanosis d/t hypoxia)
Neurological symptoms (confusion, unconsciousness, difficult to wake up, seizures, severe and prolonged dizziness)
Shock symptoms (cold, pale, clammy skin, unconsciousness, difficult to wake up)
Medical Family History (Blood Pressure, Critical Respiratory disease, cancer, HIV/AIDS, Hypertension, Diabetes Mellitus, Renal disease or liver disease)
-
Yes
No
Self Medical History (Blood Pressure, Critical Respiratory disease, cancer, HIV/AIDS, Hypertension, Diabetes Mellitus, Renal disease or liver disease)
-
Yes
No
Are you anxious or stressed with all that is happening regarding COVID 19?
-
Yes
No
Do you have existing mental health conditions?
-
Yes
No
Are you open to speaking to a Specialist regarding Anxiety and related mental health issues?
-
Yes
No
Next


Your score:
0
The Flying Witch
Click on a card to find a flying witch!
Instructions:
1. Guess, under which card is a flying witch?
2. When you find it, it starts flying
3. Click on the image, to get more points
4. You have 1 minute to make your score!
START AGAIN
59
:
99


[gecode-users] Gecode doesn't compile
Javier Mena
javimena at gmail.com
Mon Oct 24 17:04:00 CEST 2005
Hi, I've try to compile gecode in Debian using gcc 3.3 but it didn't work.
Are there problems with compilation? or should I use gcc-4?
--
Javier Andrés Mena Zapata
Systems Engineer (Student)
University of Valle
Cali - Colombia
_______________________________________________
Gecode users mailing list
users at gecode.org
https://www.gecode.org/mailman/listinfo/gecode-users
More information about the gecode-users
mailing list


With Next.js you can turn any React page into an AMP page, with minimal config, and without leaving React.
You can read more about AMP in the official amp.dev site.
To enable AMP support for a page, and to learn more about the different AMP configs, read the API documentation for next/amp
.
For more information on what to do next, we recommend the following sections:


§302A-431.9 Veterans high school diploma for armed services veterans and others. (a) The department shall establish a program to award a veterans high school diploma to qualified veterans who did not receive a high school diploma as a result of compulsory induction into active service in the armed services of the United States.
(b) For purposes of this section, a "qualified veteran" is a person who:
(1) Was a resident of the State;
(2) Was compulsorily inducted into the armed services of the United States between:
(A) December 1, 1941, and August 30, 1945;
(B) June 1, 1950, and July 31, 1953; or
(C) August 1, 1964, and January 31, 1973;
while attending or enrolled in a high school in the State; provided that the department may consider extending these time periods through rules adopted under chapter 91; and
(3) Did not complete a high school curriculum and receive a high school diploma.
(c) The department shall also award a veterans high school diploma to any person whose high school education was interrupted due to wartime practices such as internment during World War II.
(d) Qualified persons shall submit to the department, on forms that the department shall prescribe, information establishing eligibility for the award of a veterans high school diploma under this section. [L 2007, c 101, §2]
Note
Section repealed June 30, 2020. L 2012, c 133, §§38, 75; L 2015, c 124, §2.


Before Change
gene_overlap_start += read.reference_start
gene_overlap_stop += read.reference_start - 1
start_index = np.where(read[:, 0] == gene_overlap_start)[0][0]
stop_index = np.where(read[:, 0] == gene_overlap_stop)[0][0]
segment_that_overlaps_gene = read[start_index:stop_index+1]
if gene_id not in gene_calls:
// We make an on-the-fly gene call dict. See the NOTE in
After Change
gene_overlap_start, gene_overlap_stop = next(utils.get_constant_value_blocks(gene_id_per_nt_in_read, gene_id))
gene_overlap_start += read.reference_start
gene_overlap_stop += read.reference_start - 1
start_index = next(utils.find_value_index(read[:, 0], gene_overlap_start))
stop_index = next(utils.find_value_index(read[:, 0], gene_overlap_stop))
segment_that_overlaps_gene = read[start_index:stop_index+1]
if gene_id not in gene_calls:


Urban Vibes
INTRODUCTION
Urban Morphology reveals the driving forces behind the change in built form of cities and analyses persistent urban elements and socio-cultural essences embedded in them. As a broader discipline, it is aimed at understanding psychological and physical demands, socio-cultural preferences, economic objectives or technology requirements and advancement of future cities. Urban vibrancy, on the other hand, is a study observing the organic and indivisible connection and communication between urban entities, including people, which is externally manifested by dynamic changes in the dispersion and concentration of activities in the spatial dimension and the continuity and fluctuation of activities in the temporal dimension. Dense street networks, small and medium-sized blocks, diverse and intense buildings and land uses are some of the main indicators of a vibrant urban space.ANALYSIS METHODOLOGY
As the main focus of this study – which is one of the methods of analysis for our studio project on measuring and promoting urban vibrancy in Poblenou District – morphological metrics will be addressed as main parameters, since they serve to foster and prolong urban vibrancy. Those metrics, in fact, have been used only for measuring the vibrancy of the built environment. As another layer of analysis, in order to measure the vibrancy of the ground level, site visits have been conducted in the light of the predetermined parameters. In the last phase of the analysis, footfall and twitter data were used to better interpret physical and relational inspections on built environment and ground level.GROUND LEVEL VIBRANCY
Within the scope of Urban Panopticons, object detection is used to observe and measure vibrancy on the ground level, which is the second stage of our analysis in order to complete the analysis in a much more practical way compared to the site visits. The observations to be made on vibrancy of ground level are divided into 4 main titles:For the mixture of uses, bike lanes, occupation of cars, pedestrian pathways and other occupants of the street section, such as restaurant tables/chairs, were considered.
For the existence of items; benches, trees, playgrounds and other specialized items, such as outdoor sport equipment, were observed.
For the frontage activeness, observations were made on two sides of the street section, separately and they are graded from highest (active in-between) to lowest (impermeable) activeness levels. For the mixture of activities; people’s behaviors have been observed mainly for walking, doing sports, standing and eating/drinking on the street.
YOLOV5 QUALIFICATION
By using Yolov5, we are able to detect some of these parameters (people, bikes, cars, motorcycles, traffic lights/signs, umbrellas, chairs, benches etc.) explained before since they are perfectly matching. And to start object detection from videos, all possible objects are classified under three main categories which are people, mobility and urban equipment.YOLOV5@POBLENOU
For the analysis of our area we identified 4 streets that we are going to work with: Rambla del PobleNou, Carrer de Bilbao, Carrer de Taulat and Carrer de Perello (divided in 2 parts). Rambla del PobleNou is chosen for the number of people that it attracts daily since it is the central pedestrian street of the area. Carrer de Bilbao is a street parallel to Rambla, so it is chosen to understand and compare the Urban Vibrancy levels of two streets similar in size and direction but with different amenities and services. FInally, Carrer de Taulat and Carrer de Perello were chosen as two smaller streets perpendicular to Rambla and Carrer de Bilbao, to understand how the two big streets are affecting them.PLOTTING THE VIBES
We started by detecting objects from the video of Rambla del PobleNou using Yolov5 identifying our setup elements. The Categories are marked by color. We also created an animation of an histoplot showing the count of each category per frame. The final plotting from our python script includes the video with the detection points and the histoplot, showing “the pulse” of the street.LEFT AND RIGHT DETECTION
After performing these measurements for the roads, and while the total road analysis shows us how vibrant a road is in total, we still need to investigate the relationship between the vibrancy of the ground level and the built environment. For this reason, we divided our video frame into 2 parts, left and right. In this way, we were able to add a new level of analysis and understand the differences between the two sides of the street by relating them to the elements of the built environment, such as amenities, services, etc.MAPPING THE RESULTS
Once the video has been run through Python and Yolov 5. We processed the information of the CSV files output from python to Grasshopper, with the aim of mapping, visualizing and comparing the results with the morphological characteristics of Poblenou.Below are the results obtained on the right and left of the street on the Rambla of PobleNou. The height of the spectrum describes the amount of people detected in each frame and the color gradient describes the amount of urban elements detected in the same frame.
For the Rambla, it is interesting to see that the spatial distribution of people and urban elements is continuous, except for the crossing points.
But we can also see the difference between the two sides, the spectrum of the right side is less vivid than the left one and at the same time most of the aggregation spaces, including restaurants are on the left side.
The situation is different for Carrer del Bilbao if we compare it with Rambla. One of the reasons is surely the use of the street, mainly oriented to cars, which reduces its permeability. The concentration of people is in fact more fragmented, and this is also due to the reduced presence of active services at that time of day.
On Carrer de Taulat we can see a strong discontinuity. but from which we can detect a high presence of people only near restaurants or benches.
DEEP SORT
Whilst our analysis and visualizations gave us some important information, we wanted to go a step further and use open Source implementation of DeepSort to increase the accuracy and to count the number of objects with a specific id. In this way, the same person is not counted multiple times through the whole process of detecting. With DeepSort we worked with 3 streets, Rambla de PobleNou, Carrer de Bilbao and Carrer de Taulat, where there were more people appearing in the video.NEXT STEPS
Whilst our analysis and visualizations gave us some important information, we wanted to go a step further and use open Source implementation of DeepSort to increase the accuracy and to count the number of objects with a specific id. In this way, the same person is not counted multiple times through the whole process of detecting. With DeepSort we worked with 3 streets, Rambla de PobleNou, Carrer de Bilbao and Carrer de Taulat, where there were more people appearing in the video.Urban Vibes,is a project of IAAC, Institute for Advanced Architecture of Catalonia developed at Master in City & Technology in 2020/21 by students: Arina Novikova, Kshama Patil, Sinay Coskun, Simone Grasso, Stephania-Maria Kousoula and faculty: Also Sollazzo, Iacopo Neri, Soroush Garivani


| DOSE: |
|
oral |
Datura |
(seeds) |
| |
2 joints/cigs |
smoked |
Datura |
(leaves) |
Hello. My first experience with Datura Stramonium at the age of 17 was very strange, and life-changing. It all started one day with me and some friends visiting this very experienced drug user, lets call him Steve. Steve was about 2 or 3 years older than me. He told us that he had found some jimson weed near the local community college in the area we all lived in. He offered us to try some jimsonweed with him, but they were too scared and said not today.
I was surprised because the 2 guys I showed up with were very experienced and had tripped on LSD and mushrooms with me many times before. At that moment, when they turned down the offer, I thought I would be brave and said I would try it. At the moment of my acceptance of ingesting the jimson weed with Steve, I had done no research whatsoever on datura, and didn't even know the chemical name or the dangers of this drug called 'jimson weed'.
  When we got into the car, Steve pulled out 2 really fat joints of dried datura leaves. Just as I had not declined the ingestion of the datura seeds, I smoked joyfully the 2 fat joints with Steve until they were ashed away and gone.
After hanging out with all my friends for a little while, I decided to go home and go to bed, a little disappointed that I was not tripping or hallucinating yet from the very large dose of datura that day. Sometime during the night, I woke up, and started hallucinating. I began talking on a non-existent phone in my room for many minutes in my room, and I heard a voice on the other line. The rest of the night was blurry, partly from amnesia I later found out, but when day break came, and it was light outside and in my room, the real hallucinations began to reveal themselves to me. The first thing that happened that morning was I noticed that I was smoking a cigarette in my room, and knowing at the same time that my house is non-smoking.
Later on, I began to see one of my friends from high school that sat at my lunch table. He was sitting on my bed, and we began talking, and I told him all about how Steve gave me jimson weed and that I was hallucinating really bad at the moment. While talking to my friend that wasn't really there, my mother came into my room and said 'Who are you talking to?' After looking at her, and realizing her question, I looked back at where my friend was sitting on my bed, and was bewildered because he was not there anymore. This really confused me, and at that moment, I realized that I was having full-blown hallucinations. I told my mother I was talking to myself to placate her, then she closed my door.
After this run-in with my mother, I tried to be more quiet and composed as to not worry her.(After my mother heard me tell my friend on the bed that I got the jimsonweed from Steve, my mother called Steve's mother, and told her all about what had happened. Steve's mother told Steve, then one day at high school, Steve showed up and slammed me against the wall, because he thought I ratted him out. I explained to him exactly what had happened, and that my mother had overheard. He then understood and apologized.)
 Later on, I glanced at my bed and saw 2 very beautiful girls that also sat at my lunch table that year in high school. They eventually dissipated into thin air like the cigarettes and my other friend. After all of these visions, I thought to myself that I better check my eyes and see if they are red and/or dilated, so I went in front of the mirror and looked into it. Without even catching a glimpse of my face, my current history teacher was in place of my image, and he said 'Hey Andy! How's it going?' This really frightened me, so I sat down for a little and took a few deep breathes.
A little later I walked out to the kitchen for a drink of water. While in the kitchen, I looked over to the fridge, and saw my brother was standing there in his boxers and a t-shirt, and looking into a food-stocked fridge. I had noticed that with my other hallucinations, if I looked away from the actual hallucination that was in my vision, and looked back at the place where the vision was, the hallucination would disappear. Just to make sure this image of my brother was real, I looked away for a split-second, and looked back quickly. I was amazed to see my brother was gone and the fridge door was completely closed. It was at this moment that I felt something was really wrong. My parents decided that the best thing to do was to go to the hospital.
While they were taking me there, I was fully awake and clear-minded, except for 15 seconds during the trip where I had total amnesia. My parents later said that for 15 or so seconds I thought my dad and mom in the front seats were the 2 guys that took me to Steve's house the night before, and that I began talking to my parents as if they were my friends. Directly after this slight amnesia, I snapped out of it and everything was normal the rest of the day, and I had no recollection of this 10-15 second memory loss. When I got to the hospital, my father waited in the waiting room, and I was placed with my mother in a small room generally made for psychiatric inpatient holding in the emergency room. While waiting in this small room with the door ajar, I heard the sound of a heart monitor beeping like normal.
After a few seconds, the beeping noises turned into one solid continuing tone of BEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEEP. After hearing this continuing tone, a few nurses and a doctor rushed to the room, but it seamed that the person died, because then I heard a few people crying, and all the beeping noises stopped. This experience was very surreal, because my mother had also heard and saw what happened to this person in the ER. A nurse eventually came into my room, and told me that I had ingested a strong poison, and that I should be OK because I was displaying no more symptoms of hallucinations. The nurse told me to never do this drug again. She offered me some medication to help me sleep, but I declined, and my parents and I went home.
This experience with Datura was very strange, rewarding in a small aspect of life, and very dangerous.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


{% extends "base.html" %} {% block content %}
EmeraldBox is a boilerplate framework for developing python web applications with database access. The framework is based on Flask, a python microframework based on werkzeug, jinja2 and good intentions.
Your server is currently running. However you only have basic functions to the site.
Feel free to modify the contents and add stuffs to complete it.
Please register issues at our GitHub issue tracker and we'll deal with it as soon as we have time.
Thank you for using EmeraldBox
EmeraldBox an open source python web framework by Fauzan Emmerling.
You can follow his twitter @femmerling
{% endblock %}


--- layout: post title: OpenDNS Blog, Happy 25th .com! - The First Domains categories: [] tags: - geek - internet status: publish type: post published: true meta: _original_post_id: '' _original_import_author: John Duprey author: ---
The first ten registered .com domains:Symbolics.com - March 15, 1985
BBN.com - April 24, 1985
Think.com - May 24, 1985
MCC.com - July 11, 1985
DEC.com - Sept. 30, 1985
Northrop.com - Nov. 7, 1985
Xerox.com - Jan. 9, 1986
SRI.com - Jan. 17, 1986
HP.com - March 3, 1986
Bellcore.com - March 5, 1986


Symbol Index for "Actual Property"
Symbol Index for diagram
"Actual Property"
Actual Outcome (Class)
Actual Property (Class)
AP/Deduction (Generalization Node)
basis (Association)
Hypothesis (Class)
Observed Property (Class)
Projected Property (Class)
property for (Association)
Property To Be Established (Class)
SPr/Time (Generalization Node)
Subject Property (Class)
Unknown Property (Class)


UFC News: Donald Cerrone keen to get his hands on Conor McGregor
by Soumik DattaLast night, UFC President Dana White confirmed that a Welterweight bout between the returning Conor McGregor and Donald 'Cowboy' Cerrone will main event UFC 246.
Ariel Helwani has now revealed that Cerrone is excited about the prospect of getting his hands on 'The Notorious One'.
'Cowboy' gives his take on facing Conor McGregor
Donald Cerrone is one of the most active fighters on the UFC roster, having constantly accepted fights in both the Lightweight and Welterweight divisions of the company.
On the back of a loss to Justin Gaethje, Cerrone is now ready to move up to the Welterweight division and face McGregor in January. Ahead of the fight, Ariel Helwani spoke to Cerrone's manager, Josh Jones, who revealed that 'Cowboy' is eager to step inside the Octagon with the Irishman.
When is UFC 246?
UFC 246 is scheduled to take place on the 18th of January, 2020 and the main event of the card will feature Conor McGregor going head-to-head with Donald Cerrone.


@jjmerelo
git commit -am "Reviews abstract refs #2"
git commit -am "Intro revised closes #3"
CONTRIBUTING.md
data
script
report
paper


Natural Gas and Petroleum Systems
It is EPA's standard process to update the Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHG Inventory) when relevant new and improved data are available. In recent years, as improved data have become available, EPA has updated methods and data sources for calculating greenhouse gas emissions for several key sources in the natural gas and petroleum sectors. See below for materials regarding EPA estimates of greenhouse gas emissions from natural gas and petroleum systems.
Archives: Previously Posted Memos and Other Information on Stakeholder Engagement
- 2016 Inventory (released April 2016 and covers 1990-2014)
- 2015 Inventory (released April 2015 and covers 1990–2013)
- 2014 Inventory (released April 2014 and covers 1990–2012)
- 2013 Inventory (released April 2013 and covers 1990–2011)


This tutorial walks you through the process of setting up a dataset for classification, and train a network on it while visualizing the results online.
First we need to import the necessary components from PyBrain.
from pybrain.datasets import ClassificationDataSet
from pybrain.utilities import percentError
from pybrain.tools.shortcuts import buildNetwork
from pybrain.supervised.trainers import BackpropTrainer
from pybrain.structure.modules import SoftmaxLayer
Furthermore, pylab is needed for the graphical output.
from pylab import ion, ioff, figure, draw, contourf, clf, show, hold, plot
from scipy import diag, arange, meshgrid, where
from numpy.random import multivariate_normal
To have a nice dataset for visualization, we produce a set of points in 2D belonging to three different classes. You could also read in your data from a file, e.g. using pylab.load().
means = [(-1,0),(2,4),(3,1)]
cov = [diag([1,1]), diag([0.5,1.2]), diag([1.5,0.7])]
alldata = ClassificationDataSet(2, 1, nb_classes=3)
for n in xrange(400):
for klass in range(3):
input = multivariate_normal(means[klass],cov[klass])
alldata.addSample(input, [klass])
Randomly split the dataset into 75% training and 25% test data sets. Of course, we could also have created two different datasets to begin with.
tstdata, trndata = alldata.splitWithProportion( 0.25 )
For neural network classification, it is highly advisable to encode classes with one output neuron per class. Note that this operation duplicates the original targets and stores them in an (integer) field named ‘class’.
trndata._convertToOneOfMany( )
tstdata._convertToOneOfMany( )
Test our dataset by printing a little information about it.
print "Number of training patterns: ", len(trndata)
print "Input and output dimensions: ", trndata.indim, trndata.outdim
print "First sample (input, target, class):"
print trndata['input'][0], trndata['target'][0], trndata['class'][0]
Now build a feed-forward network with 5 hidden units. We use the shortcut buildNetwork() for this. The input and output layer size must match the dataset’s input and target dimension. You could add additional hidden layers by inserting more numbers giving the desired layer sizes.
The output layer uses a softmax function because we are doing classification. There are more options to explore here, e.g. try changing the hidden layer transfer function to linear instead of (the default) sigmoid.
See also
Description buildNetwork() for more info on options, and the Network tutorial Building Networks with Modules and Connections for info on how to build your own non-standard networks.
fnn = buildNetwork( trndata.indim, 5, trndata.outdim, outclass=SoftmaxLayer )
Set up a trainer that basically takes the network and training dataset as input. For a list of trainers, see trainers. We are using a BackpropTrainer for this.
trainer = BackpropTrainer( fnn, dataset=trndata, momentum=0.1, verbose=True, weightdecay=0.01)
Now generate a square grid of data points and put it into a dataset, which we can then classify to obtain a nice contour field for visualization. Therefore the target values for this data set can be ignored.
ticks = arange(-3.,6.,0.2)
X, Y = meshgrid(ticks, ticks)
# need column vectors in dataset, not arrays
griddata = ClassificationDataSet(2,1, nb_classes=3)
for i in xrange(X.size):
griddata.addSample([X.ravel()[i],Y.ravel()[i]], [0])
griddata._convertToOneOfMany() # this is still needed to make the fnn feel comfy
Start the training iterations.
for i in range(20):
Train the network for some epochs. Usually you would set something like 5 here, but for visualization purposes we do this one epoch at a time.
...
trainer.trainEpochs( 1 )
Evaluate the network on the training and test data. There are several ways to do this - check out the pybrain.tools.validation module, for instance. Here we let the trainer do the test.
...
trnresult = percentError( trainer.testOnClassData(),
trndata['class'] )
tstresult = percentError( trainer.testOnClassData(
dataset=tstdata ), tstdata['class'] )
print "epoch: %4d" % trainer.totalepochs, \
" train error: %5.2f%%" % trnresult, \
" test error: %5.2f%%" % tstresult
Run our grid data through the FNN, get the most likely class and shape it into a square array again.
...
out = fnn.activateOnDataset(griddata)
out = out.argmax(axis=1) # the highest output activation gives the class
out = out.reshape(X.shape)
Now plot the test data and the underlying grid as a filled contour.
...
figure(1)
ioff() # interactive graphics off
clf() # clear the plot
hold(True) # overplot on
for c in [0,1,2]:
here, _ = where(tstdata['class']==c)
plot(tstdata['input'][here,0],tstdata['input'][here,1],'o')
if out.max()!=out.min(): # safety check against flat field
contourf(X, Y, out) # plot the contour
ion() # interactive graphics on
draw() # update the plot
Finally, keep showing the plot until user kills it.
ioff()
show()


Language
Defining anything will involve some subjectivity. The goal of semantic is not to create code that is free from prescription, but to create code that tends to avoid arbitrary decisions if a conventional choice presents itself.
The following are some guidelines which help avoid some common pitfalls in writing UI element definitions.
Neutral Base Form
In order to make UI components be able to exist in most websites, the prototype version of an element should be neutrally styled using greytones and neutral colors. This will allow other elements to be more robust giving other developers freedom to make decisions about color and style when adapting your element for their website.
Namespacing
All css code must live inside a namespace. By default all ui elements use the class "ui". This prevents rules from altering styles of other content in the page. This also helps differentiate between UI elements and parts of an element
Tags inside of a ui element do not need to be prefixed with ui. They can simple descend from the element.
Commonality
Try to use the most obvious names for classes. If you're not sure, prototype the element, then ask a friend or two what they would call it.
Precision
Classes should be defined in one word, if the concept cannot be reduced to a single word then consider factoring it into multiple sub classes
Use real words
Abbreviations are useful for taking notes, but css definitions should attempt to use consistent, common language.
Non prescriptive
Avoid requiring any specific tags in your definitions. This will allow developers to choose which tags they would like to use with an element.
Sometimes however it makes sense to allow for common tags to be used in place of classnames for brevity. Paragraph tags, links, labels, and tables may be useful to use in a UI element definition without classnames.
Be cautious though, for example, requiring a form definition to use a form tag limits a developers ability to nest form elements inside other forms. The same is true for anchor tags
Writing Variations
Same but not the same
Multiple elements may contain similar variations that function slightly different.
For example it may be useful for various elements to float left or right. At first it may seem most useful to write a helper class that floats all UI element types when given a certain class name, but the way which an element may be floated might vary depending on the type of element.
Inversion
Elements are often inverted to stand out on dark backgrounds. Consider creating a variation of your element defines how the element can invert its colors.
Keep in mind you might have to increase the contrast between shades of your element when inverting colors, its much easier to detect in a design between multiple shades of a light color than a dark one.


Dream Store (GitHub Link )
This is a small scale project for Online shopping system. The basic idea is that customer’s can buy products using online. The administrator can enter the name and password and can create an account and then generate the receipt of the products purchased.
The aim of this project is on the online shopping application. It is developed using HTML5, JAVA script, CSS. The application is very Useful where the buyer can directly buy the products from home via internet on mobile or system. The application reduces lot of work load for customer as well as owner. The transaction of money is completed in real time system. Some of the online shops are EBAY, Amazon. By this online shopping the product is directly delivered to customer home.
Products
Login Page
Payment Option
Typing Speed Test (GitHub Link )
Project description
Implementation
Calculation


--- layout: default title: "Value Investing Modeling" author: "Rafael Nicolas Fermin Cota" date: "`r Sys.Date()`" ---
I first learned about value investing in Professor George Athanassakos' class at Ivey in 2005. It was only with the passage of time that I realized that my valuations were becoming messy spreadsheets with little holding them together other than loose assumptions and formulations. Worse, I had no faith in my own numbers, recognizing how easily I could move my intrinsic valuation by changing a number here and a number there.
The price tag we put on a business can only be as precise as the process that delivers it. The truth is that it is human nature to try to be in control and use numbers that serve us well in that pursuit. Since I was not comfortable with accounting, I realized I needed a smart framework to control the assumptions used in my valuations. This realization led me to start coding dynamic, data driven application systems for fundamental analysis.
In the past four years, my students have won all four major value investing awards at the Ben Graham Centre for Value Investing. It took us almost ten years of relentless work, but we managed to create something - something which could be held to the highest standards.
Below are the sample valuation methods that I have shared with my students throughout this journey:


Coal is our nation's most abundant energy resource. According to the U.S. Energy Administration, the United States is home to the largest recoverable reserves of coal in the world. They estimate that we have enough coal to last several hundred years, based on current consumption levels.
Because of its relatively low cost and abundance, coal is used to create about half of the electricity generated in the United States. This availability and price stability play an important role in helping Duke Energy support economic growth in the regions it serves with a reliable and affordable supply of electricity.
But all coal is not created equal. The chemical makeup of coal varies across the country and transportation costs to deliver coal to our power plants are significant drivers of which type of coal is burned at what facility. These factors and others help determine what emissions are produced during combustion and, therefore, what kind of control technologies are needed at each facility.
Duke Energy has an aggressive fleet modernization program underway that has upgraded the larger coal units with sophisticated air quality controls while we begin retiring older, less efficient coal units.
Electricity from Coal
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Coal is one of the most affordable and largest domestically produced sources of energy in the United States. It is used to generate a substantial amount of our electricity – about 37%. The challenge? Finding ways to burn it more sustainably. Historically, a wide variety of environmental impacts are associated with generating electricity from coal.
Since 1923, Duke Energy has designed and built our own coal-burning plants. And for more than three decades, we have operated one of the nation’s most efficient fossil generating systems. This means lower operating costs and lower electric rates for our customers.
We are committed to producing and delivering electricity in an environmentally responsible, cost-efficient and reliable manner – and take our responsibility to the environment very seriously. We work diligently to ensure our coal-fired plants comply with all state and federal environmental permits and we regularly monitor our facility operations with robust samplings of water and aquatic life. We also carefully manage coal combustion residuals and potential impacts to air, water and land.
In addition to modernizing our current plants, we are committed to building new ones that are cleaner and more efficient. We also effectively manage air emissions through a diverse mix of fuels to generate electricity. Using the latest emission-reduction technologies at our facilities, our emission levels of nitrogen oxide, sulfur dioxide and carbon dioxide are below the latest industry averages.
1. Heat is created
Before the coal is burned, it is pulverized to the fineness of talcum powder. It is then mixed with hot air and blown into the firebox of the boiler. Burning in suspension, the coal/air mixture provides the most complete combustion and maximum heat possible.2. Water turns to steam
Highly purified water, pumped through pipes inside the boiler, is turned into steam by the heat. The steam reaches temperatures of up to 1,000 degrees Fahrenheit and pressures up to 3,500 pounds per square inch, and is piped to the turbine.3. Steam turns the turbine
The enormous pressure of the steam pushing against a series of giant blades turns the turbine shaft. The turbine shaft is connected to the shaft of the generator, where magnets spin within wire coils to produce electricity.4. Steam turns back into water
After doing its work in the turbine, the steam is drawn into a large chamber in the basement of the power plant. In this important step, millions of gallons of cool water from a nearby source (such as a river or lake) are pumped through a network of tubes running through the condenser. The cool water in the tubes converts the steam back into water that can be used over and over again in the plant.The cooling water is returned to its source without any contamination, and the steam water is returned to the boiler to repeat the cycle.
Frequently Asked Questions
-
-
The same rich chemical composition making coal a valuable energy resource also creates byproducts. These include nitrogen oxides and sulfur dioxide. Duke Energy recognizes that continuing to reduce power plant emissions is vital to improving air quality in the United States, and we have made significant improvements in reducing air emissions in the last decade.
You can learn more about Duke Energy’s commitment to air quality and the environment in our latest Sustainability Report.
Each coal-fired plant has stringent water quality permits to ensure local waterways are protected. Duke Energy also carefully manages coal combustion residuals, such as fly ash and gypsum, and looks for opportunities to recycle these into other products to reduce the volume landfilled on site. -
Duke Energy has been using coal to produce electricity in the Carolinas since 1911. Those first coal-fired plants (in Greensboro, N.C., and Greenville, S.C.) only supplemented the company’s use of hydroelectricity. In the 1920s, the growing demand for electricity began to outstrip the availability of hydroelectric generation.
Duke Energy began a shift to using coal as its primary energy source when Buck Steam Station, in Spencer, N.C., began producing electricity in 1926. With a station capacity of 369 megawatts of electricity, Buck could produce six times more electricity than the company’s largest hydroelectric generating station at the time, Wylie Hydroelectric Station, with a generating capacity of 60 megawatts.


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| Package | idv.cjcat.stardust.common.actions |
| Class | public class Action |
| Inheritance | Action StardustElement |
| Subclasses | Action2D, Action3D, Age, AlphaCurve, CompositeAction, DeathLife, Die, ScaleCurve |
An action is associated with an emitter. On each Emitter.step()
method call,
the action's update()
method is called with each particles in the emitter passed in as parameter.
This method updates a particles property, such as changing the particle's position according to its velocity,
or modifying the particle's velocity based on gravity fields.
Default priority = 0;
| Property | Defined by | ||
|---|---|---|---|
| active : Boolean
Denotes if the action is active, true by default.
| Action | ||
| mask : int
The action will affect a particle only if it's active and the bitwise AND of the action's mask and the particle's mask is non-zero,
1 by default.
| Action | ||
| name : String | StardustElement | ||
| needsSortedParticles : Boolean [read-only]
Tells the emitter whether this action requires that particles must be sorted before the
update() calls. | Action | ||
| onAdd : ISignal [read-only]
Dispatched when the added to an emitter.
| Action | ||
| onPriorityChange : ISignal [read-only]
Dispatched when the action's priority is changed.
| Action | ||
| onRemove : ISignal [read-only]
Dispatched when the removed from an emitter.
| Action | ||
| priority : int
Actions will be sorted by the associated emitter according to their priorities.
| Action | ||
| skipThisAction : Boolean
Reset to false on each emitter step.
| Action | ||
| supports2D : Boolean [read-only]
Whether this action supports 2D.
| Action | ||
| supports3D : Boolean [read-only]
Whether this action supports 3D.
| Action |
| Method | Defined by | ||
|---|---|---|---|
|
Action()
| Action | ||
|
getElementTypeXMLTag():XML
| Action | ||
|
getRelatedObjects():Array
[Abstract Method] Returns the related objects of the element.
| StardustElement | ||
|
getXMLTag():XML
Returns the root tag of the XML representation.
| StardustElement | ||
|
getXMLTagName():String
| Action | ||
|
parseXML(xml:XML, builder:XMLBuilder = null):void
| Action | ||
|
postUpdate(emitter:Emitter, time:Number):void
[Template Method] This method is called once after each
Emitter.step() method call,
after the update() calls with each particles in the emitter. | Action | ||
|
toXML():XML
| Action | ||
|
[Template Method] Acts on all particles upon each
Emitter.step() method call. | Action |
| active | property |
public var active:Boolean
Denotes if the action is active, true by default.
| mask | property |
mask:int
[read-write]The action will affect a particle only if it's active and the bitwise AND of the action's mask and the particle's mask is non-zero, 1 by default.
This can be used to mask out specific particles that you do not wish to be affected by an action.
Implementation public function get mask():int
public function set mask(value:int):void
| needsSortedParticles | property |
needsSortedParticles:Boolean
[read-only]
Tells the emitter whether this action requires that particles must be sorted before the update()
calls.
For instance, the Collide
action needs all particles to be sorted in X positions.
public function get needsSortedParticles():Boolean
| onAdd | property |
onAdd:ISignal
[read-only]Dispatched when the added to an emitter.
Signature: (emitter:Emitter, action:Action) Implementation public function get onAdd():ISignal
| onPriorityChange | property |
onPriorityChange:ISignal
[read-only]Dispatched when the action's priority is changed.
Signature: (action:Action) Implementation public function get onPriorityChange():ISignal
| onRemove | property |
onRemove:ISignal
[read-only]Dispatched when the removed from an emitter.
Signature: (emitter:Emitter, action:Action) Implementation public function get onRemove():ISignal
| priority | property |
priority:int
[read-write]Actions will be sorted by the associated emitter according to their priorities.
This is important, since it doesn't make sense to first update a particle's position according to its speed, and then update the velocity according to gravity fields afterwards. You can alter the priority of an action, but it is recommended that you use the default values.
Implementation public function get priority():int
public function set priority(value:int):void
| skipThisAction | property |
public var skipThisAction:Boolean
Reset to false on each emitter step.
If set to true in a update()
method call,
this action is skipped by the emitter during that emitter step.
| supports2D | property |
supports2D:Boolean
[read-only]Whether this action supports 2D.
Implementation public function get supports2D():Boolean
| supports3D | property |
supports3D:Boolean
[read-only]Whether this action supports 3D.
Implementation public function get supports3D():Boolean
| Action | () | constructor |
public function Action()
| getElementTypeXMLTag | () | method |
public override function getElementTypeXMLTag():XML
Returns
XML |
| getXMLTagName | () | method |
public override function getXMLTagName():String
Returns
String |
| parseXML | () | method |
public override function parseXML(xml:XML, builder:XMLBuilder = null):void
Parameters
xml:XML |
|
builder:XMLBuilder (default = null )
|
| postUpdate | () | method |
public function postUpdate(emitter:Emitter, time:Number):void
[Template Method] This method is called once after each Emitter.step()
method call,
after the update()
calls with each particles in the emitter.
All setup operatoins before the update()
calls should be done here.
emitter:Emitter — The associated emitter.
|
|
time:Number — The timespan of each emitter's step.
|
| toXML | () | method |
public override function toXML():XML
Returns
XML |
| update | () | method |
public function update(emitter:Emitter, particle:Particle, time:Number):void
[Template Method] Acts on all particles upon each Emitter.step()
method call.
Override this method to create custom actions.
Parametersemitter:Emitter — The associated emitter.
|
|
particle:Particle — The associated particle.
|
|
time:Number — The timespan of each emitter's step.
|


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