DirectDemod: Getting Started¶
Installation¶
DirectDemod is written in python3 and uses the following libraries:
Mandatory:
- scipy
- numpy
- matplotlib
- PIL
- colorsys
Optional: (Only used for map overlay for NOAA images)
- pyorbital
- Basemap
- cartopy
Please make sure you have all the mandatory libraries installed.
Clone the repo into a folder and run “python main.py”. If you get a usage statement, you are good to go. The usage statement has all the commands that can be given to the program.
Specific applications¶
Following are the application specific guides. Assuming you already know how to record RTLSDR data to a .wav or a .dat file.
To decode NOAA image¶
If you want to decode a NOAA IQ data into images you can run the command:
python main.py -c 137000000 -f 137100000 -d noaa “file.wav”
here 13700000 is the centre frequency of the input file. 137100000 is the frequency of the satellite. “-d noaa” tells the program to use a noaa decoder on this. You should change these to match the file you have. When you run this, it will continuously print the status of decoding.
If you are skeptical if these settings are right and just want to test a portion of your file you can use the -s and -e options. For example if I want to just decode the file from 1000000 sample number to 2000000 sample number I can use the command,
python main.py -c 137000000 -f 137100000 -s 1000000 -e 2000000 -d noaa “file.wav”
This is especially helpful to just do a small test run to make sure it has found the signal.
This will just generate a black and white image, and a color image if right channels are detected. You can have a look at other commands from the usage statement.
In case the signal is not found or is very noisy you can do the following trouble shooting:
- sometimes I and Q channels migt be swapped, so use the -q flag to try to un-swap and try decoding.
- e.g. python main.py -c 137000000 -f 137100000 -q -d noaa “file.wav”
- If the signal is very noisy, you can play around with the bandwidth of the main filter by using the -b option
- e.g. python main.py -c 137000000 -f 137100000 -b 1000000 -d noaa “file.wav”
- Try opening the file in a gui like SDRSHARP and make sure you can see and hear the characteristic NOAA waterfall. Note down the frequency and make sure you are providing accurate inputs to the program.
To get sync locations in IQ recordings¶
Currently the program has implementations of NOAA, Meteor M2 and Funcube (similar cubesats) so that accurate sync locations within the file could be found.
Similar to NOAA image extraction, if you provide the flag -sync, the program will generate a .csv file with the corresponding sync locations. For Funcube or Meteor satellites, the process is similar, but no need to pass -sync flag, the .csv file will be automatically generated.


(Right-click ‘view image’ or ‘open image in new tab’ to see a larger image.)
Steve as a child (6 years old) (1955)
Steve as a child (7 years old) (1956)
Steve as a PhD student at the University of Cambridge (adept at an essential Cambridge skill, punting) (1972)
Steve as a PhD student at IGPP, UCSD (1975)
Steve as a PhD student at IGPP, UCSD (1975)
Steve as a young professional, working at SCUBED (Vancouver Island)
Steve as a young professional, working at SCUBED
Steve with his young children (1981)
Steve when he joined SDSU (1987).
Researching precarious rocks with Jim Brune (mid-1990s)
Graduation of Steve’s MA student, Jennifer Lewis (SDSU, 2000 (left to right) Gary Girty, Jeff Lewis and Jennifer Lewis, Steve Day)
Researching the Hector Mine Earthquake, Twenty-Nine Palms Marine Base, CA (2000)
ACES Workshop, Hakone, Japan (with Bernard Minster and Tom Jordan, 2000)
at the SDSU Geology Department Field Trip, Death Valley, CA (April 2007)
at the SDSU Geology Department Field Trip, Death Valley, CA (April 2007)
Proof of Collaboration with Universidad Nacional Autónoma de México (2008)
Steve in August 2014


Software developer interested in Artificial Intelligence projects. End-to-End product development.
Participating in projects like Rebuild, Fandango and VideoMOS.
Developing Frontend using AngularJS.
Backend development oriented to APIs using Flask and OpenAPI.
Computer Vision and AI Project participation using Keras, TensorFlow and OpenCV.
Software development for Computer Vision and Artificial Intelligence projects.
NRG 5 Developed a predictive maintenance state-of-the-art solution using drone imagery and deep learning algorithms.
AVVPark Automatic occupancy detection system for parking using CCTV Cameras processed with OpenCV and TensorFlow.
ScopIA Media Microservices based on Deep Learning for multiple applications: Gender Detection, Content Moderation and Object Detection.
Note: Publications related to NRG-5 project accessible at the correspondent section.
WordPress and PHP Web development. Customer service and technical support.
Learned core concepts for Machine Learning and Deep Learning development such as Time Series Analysis, Statistical Modelling, Optimization, Image processing and Reinforcement Learning.
Oriented to Signal Processing and specialized in Image & Sound Processing.
Final's degree project about parking occupancy detection, lead to my experience at Visiona IP. Proposed to mention of honor.
3+ years using Python in most of my projects.
Extensive knowledge of third-party libraries and testing with Pytest.
2+ years using OpenCV for multiple projects.
Video/streaming processing and serving along with complex image-level algorithms.
2+ years using Docker for virtualization and productization of algorithms.
Optimization of images as a main objective. Kubernetes beginner level.
3+ years developing in collaborative projects.
Git Flow branch workflow used in daily basis
Managed projects with several submodules and significant git complexity
1+ year using Gitlab CI/CD pipeline alongside Docker images to automate testing code process.
Beginner level in Jenkins.
1+ year using Scrum Methodology.
Versatily in terms of tools: Trello, Jira, Asana, Slack and more
1+ year using MongoDB in most of my projects.
SQL databases used with frequency in Website Development.
Published on MDPI Sensors Journal. Part of AVVDrone and predictive mainteinance solutions. Deep Learning and Computer vision project to prevent accidents on critical infraestructures by detecting changes on security flights performed by drones.
Get the content
Published by Wiley and edited by John Davies and Carolina Fortuna.
Our contribution to this book is the description of how Deep Learning and IoT can be combined for inspecting critical infraestructures. Moreover, a use case is detailed from the NRG5 project.
Related to the predictive maintenance solution for the NRG 5 Project. Automatic change detection system using aerial images.
Combined OpenCV and Deep Learning to detect changes on automatic security routes.
Base of the future development of AVVPark. Combining image processing to detect and segment parking lots and Deep Learning to detect the occupancy status of each lot.
Get the contentMy skills can be applied to create complete applications with multiple purposes.
From AI/ML model creation to its productization using APIs and Docker.
Projects I have been part of since the begginng of my professional career
Pedestrian and Vehicle detection using Object Detection DL Models. Thermical image analysis using traditional image processing
Deep Learning, Computer VisionAutomatic Parking Occupancy Detection System using TensorFlow, Keras and OpenCV
Deep Learning, Computer VisionVideo Content Quality Monitoring using Artificial Intelligence
Video Quality, Artificial Intelligence, APIsMicroservices with different purposes based on Artificial Intelligence algorithms
Deep Learning, MicroservicesIntrusion and Risk Detection using Drone Imagery processed using TensorFlow and OpenCV
Deep Learning, Computer VisionComplete statistical report about relevant statistics extracted from 2017-2018 LaLiga Santander Season
R, Statistical AnalysisHere I will post my articles about different topics, commonly related to Artificial Intelligence, Computer Vision or Software Development.
You can contact me for challenging and exciting offers!
Please do not hesitate to contact me if you have any proposal or interest!


A test table with merged cells
Averege
Red eyes
height
weight
Males
1.9
0.003
40%
Females
1.7
0.002
43%
ФИО
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This section graphs how the distance between Lychrel numbers change as we look at higher values, up to a value of 100,000 in this case.
We can see that the gap between Lychrel numbers decreases as they get larger. This is indicative of an increasing
frequency of Lychrel numbers as we approach higher values.
We would next like to remove (as many a possible) seed numbers, but this gets rapidly complex as I shall explain
further down. As there are many conflicting definitions of "seed" numbers out there on the internet, I have decided
to use the one which both makes computing them much simpler and personally makes more sense to me in terms of
isolating the properties that lead to a number not converging under the Lychrel algorithm.
For this demonstration I have defined "seed" numbers to be any number for which the Lychrel process never results in
a palindrome, but cannot be formed by applying a partial Lychrel process to a smaller Lychrel number. This does
however includes numbers that converge into the same series (i.e. 196 and 295 both go to 887 on one step). It is my
view that this is the most practical way to define a seed number as it allows us to investigate all numbers
which lead into an infinite Lychrel series. To avoid confusion I will from here on refer to them as
producer numbers as they 'produce' an infinite Lychrel series.
Joyfully, this also makes the computation of seed numbers less complex as we can use an O(n²) algorithm rather
than an O(n³) algorithm. While this is not a ʰᵘᵍᵉ issue, it could become a problem if I computed datasets
larger than the few thousand values I have processed here.
This graph looks largely the same as the previous one. For the dataset of the first 6020 Lychrel numbers, taking only the producer numbers eliminated less than 100 data points.
Next I decided to try expanding the definition of seed numbers to exclude the higher of two palindromes (i.e. 196 remains in the data set but 196 is removed. At the time this made some intuitive sense as a dataset worthy of investigation but I have explained below why I do not think it does not hold particular insight.
As you can see above, the decline on this graph does not behave in quite the same way as the previous ones, with a quite a number of oddities.
The chart spikes back up dramatically in two regions it had not before:
I think this is because at these regions the reverse of these integers have already occurred (i.e. 56063 has already occurred as 360605 has been removed). This then becomes especially true in the 90000s as all Lychrel numbers that don't end in a 9 or a 0 have already had their reverse occur and have thus been stripped, leading to an increased gap between producers. The dip occuring over the 80000s I cannot determine an intuitive explanation for, my best theory is that Lychrel numbers occuring here seem to more often end in a 9 or 0 than in other regions above 50000 and thus they begin to occur closer together.
I do not believe there is much insight to extract regarding the nature of Lychrel numbers from this definition of seed numbers, yet is interesting to investigate why the graph behaves as it does. Despite this I still advise that the main point of analysis should be on the characteristics of the aforementioned 'producer' numbers.
Much like the previous section, this section details the behaviour of the spacing between Lychrels up to a value of 1,000,000. Ten times higher than the previous section!
Despite investigating to a much higher value, this graph looks remarkably similar to the last section. The pattern of decay is very similar, with large jumps happening at around the same points (i.e. a change at 30,000 coincides with a change at 30,000). I would not be surprised if this behaviour continued as we looked at graphs up to 10,000,000 or 100,000,000 and so on. The most major difference I can note is that towards the extreme end of the Lychrels, there are many more instances of very small distances between Lychrel numbers (i.e. distances of 5 or less).
I have included the lower palindrome graph to again demonstrate the similar form this set has to the set of only 100,000. Noting the peak at 900,000 mirrored by the peak at 90,000. Interestingly, the peak at 50,000 does not seem to be replicated by a similar peak at 500,000.
I had thought that there could be some certain occurrence of digits that would lead to non-convergence. I'll allow the graphs to speak for themselves on this one.
From this distribution of the first 1000000 iterations of the n-step palindrome process, it seems unlikely that a
higher prevalence of any given number is responsible of 196's stubbornness to converge on a palindrome.
It would appear that 0 or 9 is slightly more common in this sequence. This does make some sense as that final 9's do
cause carrying to occur which disrupts the Lychrel process, but again I am unsure if this is of significance.
A more rigorous investigation will to be investigate the patterns of more seed Lychrel numbers and non-seed numbers.
It appears that above 1000 steps the distribution of integers remains largely unchanged, at least up to 100,000
steps. Thus unfortunately I must conclude that there is no particular integer which is 'at fault' for the
non-convergence of 196.
It is appropriate to point out here that up to the 193rd Lychrel derived by applying the process to 196, there is no
single common digit that appears in all previous derived Lychrels. That is, of the digits 1-9 each is found missing at least
once from a derived Lychrel. Even more interestingly, it would also appear for the 194th derived Lychrel and above, every
digit always appears in every derived Lychrel i.e. of the digits 1-9 none are missing from any derived Lychrel. The
code for this insight can be found
here.
While this method of distribution analysis ultimately yielded no results, another method (which shall be discussed
later) did yield some interesting results.
At the very end of my investigations, I reinvestigated the frequency of digits but instead of looking at just 196 I instead looked at the digits appearing in the first 115,752 Lychrel numbers (up to 1,000,000). This told more of a story as you can quite clearly see in the graphs below.
This distribution looks at all Lychrel Numbers up to 1000000, it would appear that there there is a positive
correlation with the value of the integers and the likelihood for a number to be a Lychrel. It would appear that
there are twice as many 9s as there are 0s over the first 115,752 Lychrel numbers. This behaviour makes some sense to me the higher a digit is the more carrying will occur during addition, disrupting the Lychrel process.
As usual I am unsure if there is much significance in this, but it does reveal some of the properties that make a Lychrel number.
The code for the production of
distance graphs
and
both
distribution graphs
are also available.


JORDAN SHAPIRO
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|
Drake
|
This class is similar to the std::pair class.
However, this class uses a pair of homogeneous types (std::pair can use heterogeneous types) and sorts the first and second values such that the first value is less than or equal to the second one). Note that the sort is a stable one. Thus the SortedPair class is able to be used to generate keys (e.g., for std::map, etc.) from pairs of objects.
| T | A template type that provides operator< and supports default construction. |
#include <drake/common/sorted_pair.h>
Public Member Functions | |
| SortedPair ()=default | |
The default constructor creates first() and second() using their respective default constructors. More... | |
| SortedPair (T &&a, T &&b) | |
| Rvalue reference constructor, permits constructing with std::unique_ptr types, for example. More... | |
| SortedPair (const T &a, const T &b) | |
| Constructs a SortedPair from two objects. More... | |
| template<class U > | |
| SortedPair (SortedPair< U > &&u) | |
| Type-converting copy constructor. More... | |
| template<class U > | |
| void | set (U &&a, U &&b) |
| Resets the stored objects. More... | |
| const T & | first () const |
Gets the first (according to operator< ) of the objects. More... | |
| const T & | second () const |
Gets the second (according to operator< ) of the objects. More... | |
| void | Swap (drake::SortedPair< T > &t) |
Swaps this and t . More... | |
Implements CopyConstructible, CopyAssignable, MoveConstructible, MoveAssignable | |
| SortedPair (const SortedPair &)=default | |
| SortedPair & | operator= (const SortedPair &)=default |
| SortedPair (SortedPair &&)=default | |
| SortedPair & | operator= (SortedPair &&)=default |
Friends | |
| template<class HashAlgorithm > | |
| void | hash_append (HashAlgorithm &hasher, const SortedPair &p) noexcept |
| Implements the hash_append generic hashing concept. More... | |
|
default |
|
default |
|
default |
| SortedPair | ( | T && | a, |
| T && | b | ||
| ) |
Rvalue reference constructor, permits constructing with std::unique_ptr types, for example.
| SortedPair | ( | const T & | a, |
| const T & | b | ||
| ) |
Constructs a SortedPair from two objects.
| SortedPair | ( | SortedPair< U > && | u | ) |
Type-converting copy constructor.
| const T& first | ( | ) | const |
Gets the first (according to operator<
) of the objects.
|
default |
|
default |
| const T& second | ( | ) | const |
Gets the second (according to operator<
) of the objects.
| void set | ( | U && | a, |
| U && | b | ||
| ) |
Resets the stored objects.
| void Swap | ( | drake::SortedPair< T > & | t | ) |
Swaps this
and t
.
|
friend |
Implements the hash_append generic hashing concept.


About this Plugin
The aurelia-mongodb-stitch-authentication plugin allows a user to quickly connect to his MongoDB Stitch
application.
Since this plugin is not that advanced yet, it only provides the Email/Password authentication with MongoDB Stitch.
Example Client
This example client shows how to use this plugin, all things considered I have created an simple Aurelia application with two views and the aurelia-mongodb-stitch-authentication plugin included.
Files
A short explanation of which files are used for what:
Login Files (login.html, login.ts):
In this example, the login files are the main files used to use the plugin. Especially the 'login.ts' file. It uses injected functions form the 'auth-service.ts' file which is the main file of the plugin itself.
appID (appID.json)
The 'appID.json' file is used to set the 'applicationID' for MongoDB Stitch. If this ID is not set, you will not be able to login your Stitch user.


| Corporate Games Pistol Shoot - 2004 | ||||||||||||||
| Results for May 12th, 2004 | ||||||||||||||
| Click on the Stage # to view the Course of Fire. | ||||||||||||||
| Place | Name | Organization | Shoot Total | Total Points Down |
Stage 1 |
String 1 |
Points Down | Stage 2 |
String 1 |
String 2 |
Points Down |
Stage 3 |
String 1 |
Points Down |
| 1 | Stilwell, Michael | Nu Skin | 68.94 | 12 | 24.16 | 22.16 | 4 | 35.20 | 12.45 | 19.25 | 7 | 9.58 | 9.08 | 1 |
| NC | Zaccardi, Pat | Range Masters | 74.55 | 18 | 26.40 | 24.90 | 3 | 37.84 | 13.40 | 16.94 | 15 | 10.31 | 10.31 | 0 |
| 2 | Taylor, Joshua | Nu Skin | 74.71 | 10 | 24.65 | 23.15 | 3 | 36.34 | 16.23 | 19.61 | 1 | 13.72 | 10.72 | 6 |
| 3 | Adams, Kyle | Provo City Power | 93.20 | 14 | 30.22 | 26.72 | 7 | 48.41 | 22.62 | 22.29 | 7 | 14.57 | 14.57 | 0 |
| 4 | Jones, Brad | Nu Skin | 94.04 | 31 | 36.18 | 36.18 | 0 | 37.92 | 12.17 | 15.75 | 20 | 19.94 | 14.44 | 11 |
| 5 | Yei, David | Provo City | 99.78 | 27 | 31.07 | 27.07 | 8 | 49.82 | 22.39 | 19.43 | 16 | 18.89 | 17.39 | 3 |
| 6 | Larsen, Tom | Novell | 104.07 | 43 | 35.32 | 31.82 | 7 | 52.41 | 19.94 | 17.47 | 30 | 16.34 | 13.34 | 6 |
| 7 | Marlow, Dave | Nu Skin | 105.70 | 27 | 44.39 | 37.89 | 13 | 47.89 | 19.41 | 21.48 | 14 | 13.42 | 13.42 | 0 |
| 8 | Finlinson, Jason | Provo City | 107.02 | 12 | 44.33 | 38.33 | 12 | 45.31 | 22.45 | 22.86 | 0 | 17.38 | 17.38 | 0 |
| 9 | Richards, Rhead | Nu Skin | 108.54 | 29 | 44.62 | 40.12 | 9 | 44.73 | 17.45 | 20.28 | 14 | 19.19 | 16.19 | 6 |
| 10 | Bolinder, Jim | Nu Skin | 113.52 | 31 | 53.44 | 43.94 | 19 | 45.08 | 17.31 | 22.77 | 10 | 15.00 | 14.00 | 2 |
| 11 | Daniels, Robert | IHC | 119.49 | 81 | 53.28 | 26.78 | 53 | 51.24 | 16.72 | 20.52 | 28 | 14.97 | 14.97 | 0 |
| 12 | Smith, Jason | Provo City Power | 124.40 | 43 | 48.80 | 47.80 | 2 | 56.52 | 16.95 | 19.07 | 41 | 19.08 | 19.08 | 0 |
| 13 | Johnson, Bruce | IHC | 134.61 | 34 | 54.93 | 50.93 | 8 | 58.07 | 20.79 | 26.28 | 22 | 21.61 | 19.61 | 4 |
| 14 | Ostler, Darrell | Novell | 135.52 | 27 | 54.59 | 51.59 | 6 | 52.49 | 18.46 | 24.03 | 20 | 28.44 | 27.94 | 1 |
| 15 | Hutchison, Dean | Provo City Parks | 135.61 | 27 | 49.14 | 45.14 | 8 | 68.73 | 33.64 | 26.59 | 17 | 17.74 | 16.74 | 2 |
| 16 | Nielson, Mike | IHC | 153.07 | 99 | 60.02 | 32.52 | 55 | 64.89 | 22.62 | 30.77 | 23 | 28.16 | 17.66 | 21 |
| 17 | West, Dave | Provo City Power | 155.46 | 6 | 70.68 | 70.18 | 1 | 58.81 | 30.63 | 25.68 | 5 | 25.97 | 25.97 | 0 |
| 18 | Cather, Dan | Provo City | 171.62 | 55 | 57.48 | 46.98 | 21 | 83.20 | 36.36 | 29.84 | 34 | 30.94 | 30.94 | 0 |
| 19 | Johnson, Ken | Provo City Power | 203.40 | 38 | 78.50 | 71.00 | 15 | 83.89 | 29.23 | 48.16 | 13 | 41.01 | 36.01 | 10 |
| 20 | Hardy, Brett | Provo City Power | 217.92 | 43 | 79.21 | 77.21 | 4 | 110.85 | 26.62 | 64.73 | 39 | 27.86 | 27.86 | 0 |
| Notes: | ||||||||||||||
| NC | -
Not Considered for medal placement. Although hosting the
competition, Range Masters was not formally registered as a competing company. For that reason, Pat did not qualify for a medal. |
|||||||||||||
| X | - Indicates that the Points Down value contains some type of penalty (Procedural = 6 PD, "Hit on Non-Threat" = 10 PD, or 'Miss-On-Steel ' = 10PD). | |||||||||||||
| Special recognition is
given to those who acted as Safety Officers for the competition. Note that all SOs are members of the Utah County based Utah Defensive Pistol League (UDPL): |
||||||||||||||
| Ken Collins | Kent Redford | Kyle Adams | Mike Stilwell | |||||||||||
| Noel Redford | Pat Zaccardi | Steve Redford | ||||||||||||


Run commands or entrypoint can be changed from the settings menu in the editor page.
To do so, click the cog icon in the bottom right of the index page and select the Edit run commands button.
Here you can change the run commands and entrypoint for your current project or reset the run commands back to their original state.


Manny Pacquiao's two-man shortlist for boxing return next spring
Filipino legend Pacquiao, who was last seen beating Keith Thurman and also defeated Adrien Broner in 2019, will be out of action until April or May next year
by Martin Domin, https://www.facebook.com/mirrorfightingManny Pacquiao will fight either Mikey or Danny Garcia when he returns to the ring next year.
The eight-weight world champion recorded impressive victories over Adrien Broner and Keith Thurman in 2019.
And despite being 40, he has no plans to retire with his next fight pencilled in for April or May.
Pacquiao will be free from his political obligations in the Philippines Senate next spring as he looks to continue his legendary career.
Mikey Garcia has not fought since he lost to Errol Spence on his welterweight debut earlier this year but plans to continue at 147lb.
His namesake Danny has alternated victories and defeats in his last four fights, including losses to Thurman and Shawn Porter.
Mikey Garcia has long campaigned to fight Pacquiao with his uncle Peter telling Fight Hype recently: “Whenever he doesn’t have a fight, he spars two times a week…but since two weeks ago, he’s been coming five times a week.
“My grandpa said, ‘He’s going to get a date soon. He doesn’t come on Tuesdays when he doesn’t have a fight coming up.’ It’s still in negotiations.
“He decided last year after he fought Robert Easter, when he started calling out Errol Spence. All of us thought, ‘yeah, it’s a fight [against Pacquiao] he could take, if we could get ready for, it was a fight that he could possibly win.
"There was a fight that was not easier. I’m not saying Pacquiao is an easier fight, but it’s more easier in terms of size. He’s a smaller guy.
"He’s moved up a lot of weight. Errol’s a guy that has to cut weight. He’s a big guy at welterweight. The style is a lot more difficult."
Pacquiao's decision to focus on either Garcia means Britain's Amir Khan will once again miss out on a shot at his former sparring partner.


ASME is an internationally renowned organization known for setting codes and standards for mechanical devices. It is a not-for-profit membership organization that enables collaboration, knowledge, sharing, career enrichment, and skills development across all engineering disciplines, toward a goal of helping the community develop solutions to benefit lives and livelihoods. From college students to project managers, corporate executives, researchers and academic leaders, ASME’s members are as diverse as the engineering community itself. ASME serves wide-ranging technical community through quality programs in continuing education, training and professional development, codes and standards, research, conferences and publications, government relations and other forms of outreach.ASME has over 130,000 members in over 150 countries. ASME standards are used in 100 countries.
The seniors also reminisce the old memories when ASME was founded by the efforts of the Head of Department, Prof.(Dr.) Darshak Desai, our faculty advisor, Prof.(Dr.) Hemant Thakkar and fellow students
The GCET American Society of Mechanical Engineers Student chapter was started on 2nd August 2012 by our own Harsheel Panchsaara. The sole purpose of this chapter is to give the budding engineers of G.H Patel College of Engineering and Technology a platform for their technical as well as mental development. On 2nd August 2012 with the initial support from Gaardi ASME Student Section, Rajkot and the support of Dr. Darshak Desai, Head of Mechanical Department and our Dr. Hemant Thakkar, faculty advisor of ASME Student Chapter, we are able to successfully establish a ASME Student Chapter.
We conducted our workshops at the 2017- Mechanical and Mechatronics batches on 4th September 2017. Our Member Development Head Mandar Kesarker gave the talk about what ASME is, how it benefits us students and how to utilise the ASME membership


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--- layout: default title: Fiddy Fiddy 2017 ---
In 2017 all of our wines were destemmed cold soaked for 4 days. Yeast was pitched and the wines were fermented on skins with stems. Wines were pressed after 4 months on skins. They were racked 3 times but not filtered.
As with the other 2017 vintages we wanted to explore how the cabernets played together and once we had our 2nd press we had equal amounts of liquids. The next logic step was to blend them. Wine was aged in glass for 12 months with no oak.


BULLY A film review by Steve Rhodes Copyright 2001 Steve Rhodes RATING (0 TO ****): *** 1/2
BULLY, by Larry Clark (KIDS), tells a shocking and true story about a group of Florida teenagers who committed premeditated murder against another teen. Without pulling any punches, the movie shows the kids in reckless behavior from unprotected sex to drugs to violence. This unrated movie -- it would be NC-17 -- is a powerful anti-drug film since it shows what is possible if you live your life stoned. It also speaks volumes about the story's oblivious parents, who could charitably be called "less than helpful" to their kids.
Shot handsomely on film, not video, this indie picture has a polish and an accessibility that KIDS, which I hated, lacked. And the scenes of the teens engaging in one wild sex act after another -- including one with hot wax -- are undeniably erotic. Clark seems hell bent on making as realistic a movie as possible, and almost none of the characters are sympathetic. The only significant exception is Claudia (Jeanne Orr), a teen who works at the local Pizza Hut and is smart enough to have nothing to do with the murder. The victim, Bobby Kent (Nick Stahl), is easily the most despicable character of them all.
As the story begins, we are introduced to Marty Puccio (Brad Renfro), a shy surfer.  Bobby has been ridiculing and abusing Marty since they were kids. Bobby thinks nothing of hitting Marty so hard that he could break his nose. Although Bobby beats up on Marty regularly, Bobby is an equal opportunity abuser. He also likes choking and raping girls just for cheap thrills. And cheap thrills seem to be what the kids in this story crave. Sex with strangers and lots of pot and acid just never seem to be enough to stave off their boredom. The movie is careful to cast average to attractive looking actors who appear to be the spitting images of the kids at your local mall.
Marty gets what could be his first real girlfriend in Lisa Connelly (Rachel Miner). Since she doesn't like the way that Bobby treats him, she suggests that they kill Bobby. And when she says "they," she means basically any acquaintances of theirs who happen to be handy, some of whom don't even know Bobby. These include, Ali Willis (Bijou Phillips), Donny Semenec (Michael Pitt), Heather Swallers (Kelli Garner), "Hitman" (Leo Fitzpatrick) and Derek Dzvirko (Daniel Franzese). None of them seems to have a moral bone in his or her body, and they live lives without consequences. The actors who play the characters deliver such flawless performances that they don't even appear to be acting. It is chilling watching them.
In a telling scene, Heather tries to give some advice to Ali. "What do you mean?" Ali asks. "I don't know," Heather honestly replies.  They aren't even capable of helping each other.
When the time comes for the crime itself, these kids evidence all of the planning skills that you would expect of social misfits who live their lives wasted. After the murder has been committed, they keep secrets about as well as a bunch of preschoolers. Other movies, such as THE RIVER'S EDGE, have covered similar material, but few have done it better and more realistically than BULLY, a movie that you won't soon forget.
One of the movie's last images is of Marty's brother wearing an ironic "DARE to Say No to Drugs and Violence" T-shirt as he looks sadly on what has happened to Marty. It is a fitting ending visual. (Be sure and stay until the credits have completely finished in order to get some updated information on the teenagers involved.)
BULLY runs a fast 1:46. It is not rated but would be NC-17 for pervasive drug usage, strong sexuality, violence and full-frontal nudity. It would be acceptable for college students and older.
The film is playing in nationwide release now in the United States -- probably for just a short run. In the Silicon Valley, it is showing at the Camera Cinemas.
Web: http://www.InternetReviews.com Email<EMAIL_ADDRESS>Want free reviews and weekly movie and video recommendations via Email? Just send me a letter with the word "subscribe" in the subject line.
========== X-RAMR-ID: 28881 X-Language: en X-RT-ReviewID: 236509 X-RT-TitleID: 1108900 X-RT-SourceID: 703 X-RT-AuthorID: 1271 X-RT-RatingText: 3.5/4
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Related links: index of all rec.arts.movies.reviews reviews


+++ title = "Adam's barmitzvah: shabbat dinner" slug = "adams-barmitzvah-shabbat-dinner" date = 2007-10-12T10:00:00+10:00 tags = ["kosher", "family", "oy-vey", "judaism", "barmitzvah"] locations = ["united-states/boston"] draft = false summary = """
Adam's barmitzvah celebrations began tonight, at the Goldstein house, with a fully-catered shabbat dinner. Big crowd — much of the extended family arrived this evening, mainly from New York and Philadelphia — and plenty of new (and very distantly-related) relatives to meet. The food was great, and it flowed from the kitchen in copious quantities. A very nice, heimische start to the simcha.
""" +++Adam's barmitzvah celebrations began tonight, at the Goldstein house, with a fully-catered shabbat dinner. Big crowd — much of the extended family arrived this evening, mainly from New York and Philadelphia — and plenty of new (and very distantly-related) relatives to meet. The food was great, and it flowed from the kitchen in copious quantities. A very nice, heimische start to the simcha.
{{< galleryphoto "2007-10-12-10-00-00--the-children-and-young-adults-from-tonight-back-row.jpg" >}} {{< galleryphoto "2007-10-12-10-01-00--the-adults-from-tonight-back-row-random-good-humoured.jpg" >}} {{< galleryphoto "2007-10-12-10-02-00--adam-s-birthday-cake-decorated-as-a-golf-course.jpg" >}}


monkfish catch survey trawl caught seasonal Monkfish stations NEFSC Fig dredge surveys (BT:M) data depths waters Fish {border-style Management abundance temperatures (D:M) bycatch model px;} relative #ffffff;} Fishery Georges changes scallop temperature Table area fall Research average observed summer using distribution Area Bank CFF fish sampled station study < CAII Northeast areas depth distributions final gear numbers New deeper included movements spring used (–) AIC CAI Closed analysis commercial fixed Sea adult based length meters month number tows trip Atlantic England Essential Fisheries ICES Kolmogorov-Smirnov Lophius NOAA Sci. Science Set-Aside catches conducted effects fishing months package px; range stock terms tow {font-family (two-sample (–, Amendment Habitat Scallop depth, font-size juvenile migrations season spring, test, year (> Animal Council. Gulf Mar Sciences Tweedie United counts did distributed double; dredges effect fishery high important inshore low management month, plotted ratio shallow shown southern species studies variables winter, ./journal.pone..t Bigelow Data Information June March Plan, Seasonal Smolowitz States Station assess assessment border-color border-width common deep frequency function higher increasing meters, models northern ranged reported research shifts solid; spatial survey, temperature, three-year values winter {font-style {font-weight .). .E- Adult American Aquat Assessment August Average Coonamessett Environmental Farm Final Grant Life Maine NANMF NANMF, November Number Report. Ronald SFMA Sci Spring Writing access additional adjusted assessments. bold closed cm) coast continental courier; course covered cumulative early edge effectively em; examined fall. fish), genetic greater limited modeled monkfish, months, need occurred offshore open patterns positive pt;} recent response ring shift significant similar small south study. surveys, swept temperature. temperatures, vessel vessels widely


Since the dawn of time - book-keepers have been forced to use old and user un-friendly software. Now is the time for change!


NP
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An event informative app created for teens by teens.


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Gwent Police is appealing for information after a woman in her 30s was sexually assaulted in Cripps Avenue, Tredegar, Blaenau Gwent.
The incident took place between 10.30pm on Saturday, June 15, and 12.30am on Sunday, June 16.
The woman is being supported by specialist officers.
The force wants to trace a man with a distinctive tattoo on his left forearm.
An artist's impression of the tattoo was released by Gwent Police on Thursday, with officers urging the man or anyone who recognises the tattoo to get in touch.
Officers are also keen to hear from anyone who may have dash-cam, CCTV or doorbell camera footage from the Cripps Avenue and Cefn Golau area around the time of the incident.
Gwent Police Detective Inspector Leigh Holborn is leading the investigation.
"As part of our enquiries, we are eager to trace the man with this distinctive left arm tattoo who may hold vital information to our investigation," he said.
"We would urge him or anyone who recognises this tattoo to get in contact.
"We continue to appeal for information and would urge anyone who may have seen anything to come forward that could help with the investigation.
"We are particularly interested in hearing from anyone who may have dash-cam footage, CCTV or doorbell camera footage from the Cripps Avenue/Cefn Golau area around the time of the incident."
After the incident, Gwent Police issued the following advice to residents:
• If you’re out at night, try to avoid dark or dimly lit areas and stick to main paths.
• When you’re heading out somewhere, try to let someone know where you’re going and how long you’ll be out for.
• Always make sure you have a charged mobile phone with you in case of an emergency.
• If you see someone acting suspiciously or if something just doesn’t feel right, call 101 or dial 999 in an emergency.
• If you feel uneasy, ask a passer-by for help or head towards a nearby shop. If you are in immediate danger, shout for help or if you have an alarm, use it to make as much noise as possible.
Anyone with information or footage that could help with the enquiry is asked to call Gwent Police on 101, quoting log 309 of 07/08/19.
Alternatively, Crimestoppers can be contacted anonymously on 0800 555 111 or visit https://crowd.in/8Ncxqk.
Gwent Police can also be contacted via direct message on its Facebook and Twitter social media pages.


Application Form
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Country Of Interest
Nigeria,Abuja
Ghana , Tema
Ghana ,Accra
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Our webside uses and interactive methodology of teaching Maths using tle latest web technologies. Your learning experience with us is guaranteed to be intuitive and fun. You will have fun while learning. This is the secret of our outstanding results. Check reviews from our students.


| Home | Trees | Indices | Help |
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|---|
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Generic containers, data structures and language extensions.
This module has several functions:
In order to ensure cross-interpreter compatibility, checking for string instances in CSB must always be implemented like this:
>>> isinstance("s", string)
because "basestring" is not available in Python 3. Also, metaclass definitions other than abstract classes must be implemented as follows:
>>> MyClassBase = metaclass(MetaClass, base=BaseClass) >>> class MyClass(MyClassBase): pass
See also the notes about compatibility in csb.io.
| Classes | |
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AbstractContainer Defines the behavior of a high-level object, which can hold an array of elements. |
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| AbstractIndexer | |
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AbstractNIContainer Same as the AbstractContainer, but provides access to the child elements through AbstractNativeIndexer._getinternal instead of the
standard __getitem__.
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BaseCollectionContainer Base class which defines the behavior of a read-only collection container. |
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BaseDictionaryContainer Base class which defines the behavior of a read only key-value collection container. |
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CollectionContainer Write-enabled Collection Container. |
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| CollectionIndexError | |
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Container Generic implementation of AbstractContainer. |
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DictionaryContainer Write-enabled Dictionary Container. |
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| DuplicateKeyError | |
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Enum A collection of efficient static methods for working with enum classes. |
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| EnumBase | |
| EnumItem | |
| EnumMemberError | |
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EnumMeta Metaclass for enum types. |
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| EnumValueError | |
| InterruptibleThread | |
| InvalidKeyError | |
| ItemNotFoundError | |
| OrderedDict | |
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Proxy Base class implementing the proxy pattern. |
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| REMatchProxy | |
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ReadOnlyCollectionContainer This is a write-once container, which is filled with items only at object construction. |
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ReadOnlyDictionaryContainer This is a write-once container, which is filled with items only at object construction. |
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| Stack | |
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enum Base class for all enumeration types. |
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typedproperty Property decorator for convenient creation of typed, encapsulated fields. |
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validatedproperty Property decorator with predefined getter/setter and value checking or casting in the setter. |
| Functions | |||
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__package__ =
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| Function Details |
Perform a deep copy of obj using cPickle. Faster than copy.deepcopy() for large objects.
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Return True if
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Return a new class with parent class |
| Home | Trees | Indices | Help |
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| Generated by Epydoc 3.0.1 on Tue Jul 4 20:19:04 2017 | http://epydoc.sourceforge.net |


If you click on a label this action will be applied:
's': push from left to server
'f': push from right to server
'd': left, right pull from server


ALIGN SQUARE LOGO
ALIGN WIDE LOGO
Scales to Export
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125% 150% 200% 400%
Windows 8
80% 140% 180%
Windows Phone
240%
Wide images
Splash screen
620x300
Wide logo
310x150
Square images
Square 44x44 logo
44x44
Square 71x71 logo
71x71
Logo
150x150
Badge logo
24x24
Large tile
310x310
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50x50
Include background color in Store logo
Windows Phone and Windows 8
Small tile
70x70
Small logo
30x30
Splash screen
480x800
Hex color


Select the number of shares that you wish to recover your secret from. This can be anywhere between 2 to 6. Make sure that this corresponds to the same number of shares that was initially selected when creating the shares
Next, you'll be asked to enter the terms for each share. To do so, you can use the terms that are suggested or use our mnemonic secure keyboard. A share can consist of 24 terms. Make sure that you put the terms in the right order too
After one share has been entered successfully, you’ll be asked to enter the next one until all shares have been entered


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/.60decidable_eq.60.20got.20removed.20from.20.60field.60.html ---
So discrete_field
used to imply decidable_eq
. @Chris Hughes' PR changed that. Was that intentional? I'm currently just adding decidable_eq
assumptions everywhere.
This was intentional. It's consistent with the rest of the classes, we don't have decidable rings or anything. The convention is that we don't have decidable_eq
assumptions for theorems that require it for the proof but not the statement, we just go classical, so I think most of the theorems should be classically provable still and don't require the assumption.
Since a total division function gives decidable equality at least in the propositional sense, there isn't much loss in having decidable_eq
as part of field
. It might not be possible to prove decidable_eq
from the totality of division, but the only obstacle is predicativity.
See, for example, https://arxiv.org/pdf/1606.04126.pdf where Kihara and Pauly give a computable reduction of "robust division" for reals to LPO.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Xson-Shopping Palace is ficitious Company
It is a solely made for academic purposes
XSON has no relationship with Google, and does not intend to harm the copyright of anyone
Pictures are taken from an internet source
For further queries, contact DPS Rohini- Xino (Computer Club)


1) Arrays represent multiple data items of the same type using a single name.
2) Arrays allocate memory in contiguous memory locations for all its elements.
Hence there is no chance of extra memory being allocated in case of arrays.
This avoids memory overflow or shortage of memory in arrays.
3) In arrays, the elements can be accessed randomly by using the index number.
4) Two-dimensional arrays are used to represent matrices.
1) The number of elements to be stored in an array should be known in advance.
2) Allocating more memory than the requirement leads to wastage of memory space and less allocation of memory also leads to a problem.
1) Array stores data elements of the same data type. 2) Maintains multiple variable names using a single name. Arrays help to maintain large data under a single variable name. This avoid the confusion of using multiple variables. 3) Arrays can be used for sorting data elements. Different sorting techniques like Bubble sort, Insertion sort, Selection sort etc use arrays to store and sort elements easily. 4) Arrays can be used for performing matrix operations. Many databases, small and large, consist of one-dimensional and two-dimensional arrays whose elements are records. 5) Arrays can be used for CPU scheduling. 6) Lastly, arrays are also used to implement other data structures like Stacks, Queues, Heaps, Hash tables etc.


--- layout: demo title: CSS Color Grid description: I wanted to see if I could build an 8x6 color grid using only CSS colors. ---
| black | dimgrey | grey | slategrey | darkgrey | lightgrey | gainsboro | white |
| indianred | wheat | lightyellow | palegreen | lightcyan | lightsteelblue | thistle | pink |
| crimson | sandybrown | khaki | yellowgreen | lightskyblue | cornflowerblue | darkorchid | plum |
| red | orange | yellow | green | dodgerblue | blue | purple | hotpink |
| firebrick | coral | gold | forestgreen | mediumturquoise | mediumblue | rebeccapurple | magenta |
| maroon | chocolate | goldenrod | olivedrab | teal | midnightblue | indigo | mediumvioletred |


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This is my website for the Summer Work at Blue Coat for Computer Science. I have used Javascript to:
- Animate the title's colour using JQuery, by using the
function, and make it continuous by using a recursive function.$.animate
- Animate the JQuery overview page with examples of the JQuery functions I listed.
- Make a dinosaur run across the page when a viewer enters the konami code, which is:
Up Up Down Down Left Right Left Right B A
with the following Javascript features:
- Variables, such as
, these let you sustain values all through a function scope that you can change.var x = 12; // global scope
const x = 12; // global scope constant
let x = 12 // block scope - Conditionals, such as
, these let you run code only if a value evaluates to a true value. I used this for the Konami code functionality to check that the array values are equal.if(x < 12) console.log(x)
- Functions, such as
and (new arrow syntax)function(x) return x + 2
, these let you run bits of code with values called arguments. These arguments can have default values in newer Javascript. I used these in the callbacks I passed to JQuery.(x) => x + 2
- Objects, such as
, these let you associate multiple named values woth a single value. I used these to configure the JQuery animations.{ x: 20, y: 30 }
- Arrays, such as
, these let you associate multiple values with a single value.[ 20, 12 ]
- TypedArrays, such as
, these let you store multiple values of a single type in a single array value. These are way faster than regular arrays because of their typed access as they take less room in memory than normal arrays, but they are slightly more compilicated to work with. I used these to store the keyboard buttons pressed and the desired buttons for the Konami code functionality.new Int32Array([1, 3, 5, 7])


Test coverage user interface for C and C++
Sure you do. Lots and lots of code. And tests...not so much? Not enough?
So you know you need more tests, because everyone needs more tests... but how are you supposed to know which parts of your code to test next?
Easy: ggcov tells you which parts of your software are well tested, and which parts...need a little lovin'. ggcov is a set of tools for exploring test coverage data produced by C and C++ programs compiled with gcc --coverage. So it's basically a replacement for the gcov program that comes with gcc. ggcov has a tool for your workflow.
ggcov has a Gnome GUI for exploring test coverage.
See annotated source, reports, and visualisations.
ggcov generates static HTML reports with much of the functionality of the Gnome GUI.
Explore your code in any web browser, no web server needed.


$subtl$
Posted on $date$ $if(author)$ by $author$ $endif$
Have an issue? Please join the conversation.


mlpack benchmarks
This page contains benchmarks for the various algorithms implemented in mlpack 1.0.10. When applicable, timing results are also given for other libraries. Currently, benchmarks are provided for scikit-learn, the SHOGUN machine learning toolbox, Weka 3, mlpy, and standard MATLAB implementations. If you don't see benchmarks for your favorite library or algorithm, feel free to file a bug report or consult the documentation for the automatic benchmarking system and write a script.
The automatic benchmarking system was developed as a Google Summer of Code 2013 project by Marcus Edel and improved by Anand Soni during GSoC 2014, and is maintained separately on Github.
Below, you may select one of many interactive JavaScript visualizations for inspecting the benchmarking results. At this time, we are still adding results (especially historical results). If you are interested in the previous non-interactive visualizations, which included memory usage graphs for mlpack methods, click here.


We are the Blade Hackers.
Our names are Holly, Kevin, Anas, and Hajar.
I am learning how to make a website for my hacking team.
website is to help people learn about hacking and more coding projects.


The course content is divided into sections which teaches specific parts of the course syllabus. Each section may contain reading instructions, lectures, labs and other learning activities.
course content
Section 1: Web application development.
Section 2: HTML, CSS and JavaScript.
Section 3: Client side JavaScript with AJAX.
Section 4: Server side JavaScript with Node and Express.
Section 5: PHP and databases with MySQL/MariaDB.
Section 6: JavaScript and PHP frameworks.
Section 7: ASP.NET and Model View Controller (MVC).
Section 8: Web application performance.
Section 9: Web security and OWASP.
Section 10: Project.
GitHub repository for this course can be accessed form here.


Install SnipeitPS from the PowerShell Gallery Install-Module
requires PowerShellGet (included in PS v5, or download for v3/v4 via the gallery link)
# One time only install: (requires an admin PowerShell window)
Install-Module SnipeitPS
# Check for updates occasionally:
Update-Module SnipeitPS
# To use each session:
Import-Module SnipeitPS
Set-Info -URL 'https://asset.example.com' -apiKey 'tokenKey'
# Review the help at any time!
Get-Help about_SnipeitPS
Get-Command -Module SnipeitPS
Get-Help Get-Asset -Full # or any other command


LogLevel
public enum LogLevel: Int, CustomStringConvertible
See https://logging.apache.org/log4j/2.0/manual/architecture.html for more info
- ALL: All levels including custom levels.
- DEBUG: Designates fine-grained informational events that are most useful to debug an application.
- ERROR: Designates error events that might still allow the application to continue running.
- FATAL: Designates very severe error events that will presumably lead the application to abort.
- INFO: Designates informational messages that highlight the progress of the application at coarse-grained level.
- OFF: The highest possible rank and is intended to turn off logging.
- TRACE: Designates finer-grained informational events than the DEBUG.
- WARN: Designates potentially harmful situations.

A log request of level p in a logger with level q is enabled if p >= q
-
Undocumented
Declaration
Swift
public enum LogLevel: Int, CustomStringConvertible
-
Undocumented
Declaration
Swift
public enum LogLevel: Int, CustomStringConvertible
-
Undocumented
Declaration
Swift
public enum LogLevel: Int, CustomStringConvertible
-
Undocumented
Declaration
Swift
public enum LogLevel: Int, CustomStringConvertible
-
Undocumented
Declaration
Swift
public enum LogLevel: Int, CustomStringConvertible
-
Undocumented
Declaration
Swift
public enum LogLevel: Int, CustomStringConvertible
-
Undocumented
Declaration
Swift
public enum LogLevel: Int, CustomStringConvertible
-
Undocumented
Declaration
Swift
public enum LogLevel: Int, CustomStringConvertible
-
Converts the LogLevel into a string - Returns: The name of the log level as a string
Declaration
Swift
public var description: String
Return Value
The name of the log level as a string


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{% endif %}


Just... play?
Added highscore save system
Fixed update log organization
Added toggleable 'hard-mode'
Added fast arrow collectable
Added slow arrow collectable
- Added the ability to press [ENTER] on menu and game over screen to continue
- Added feather collectable
- Added ball and chain collectable
- Added life token collectable
- Added ability bar
- Reworked collectable spawing system
- Added pause feature
- Added bouncing wall obstacle
- Reduced image render lag
- Changed player rotation rate for hard mode
- Added new texture for player when invincibility is enabled
- Reworked randomization system
- Added new obstacle spawn layouts
- Changed texture and collision box for filter wall obstacle
- Added invincibility flower collectable
- Changed all collectable textures
- Changed layer rendering order
- Reworked collision system
- Added toggleable 'easy-mode'
- Added toggleable 'developer-mode'
- Added new 'slow moving object' system
- Added water bucket collectable
- Added slime bucket collectable
- Added filter wall obstacle
- Fixed physics
- Added game-over screen
- Added score system
- Added coin collectable
- Added wall obstacle
- Made, ya know, the game


--- title: "Exploratory Data Analysis" summary: "Basics for data preparation" subtitle: "An introduction to data manipulation and analysis in R" disable_comments: false # Optional, enable Table of Contents for specific post authors: - admin date: '2019-08-04' featured: true image: caption: 'Image credit: [**Photo by Isaac Smith on Unsplash**](https://unsplash.com/photos/AT77Q0Njnt0)' focal_point: "" placement: 3 preview_only: true output: md_document lastmod: "2019-08-04" projects: [] categories: [R, Data Visualization] tags: [Twitter, R, Data Visualization] ---
“The goal is to turn data into information and information into insight.” – Carly Fiorina, former chief executive officer, Hewlett Packard.
If you are familiar with data analysis then I’m certain that you fully relate to the above statement. After all, it would be pointless to play around with lots of data just for the love of it, sometimes not but you get the point.
Data is gold, and the more you have the better off you are. However, raw unprocessed data is of no use unless you manipulate and gain insights from it. Before embarking on say statistical modelling and visualization of your data, it is very important to first have an understanding of the data itself. Exploratory Data Analysis (EDA) aids in visualization, transformation, and generally cleaning or remodeling data before diving deep into information extraction.
There are no set rules to be followed when performing EDA. As a data preparation phase, one is allowed to decide what suits them best in order to gain an understanding of their data. However, there are two most important questions one should seek to answer while studying their data:
That being said, EDA involves the following checks among others:
In this post, we will perform EDA on a sample data set containing responses to a mobile banking survey in Kenya. If you would like to follow along with the same data, you can download it here.
The code chunk below imports our data set into R.
#Loading Data into R toc_depth: 2
mobileBanking.Df <- read.csv("J://Personalprojects//Blogsite//data//MobileBankinginKenya.csv", header = TRUE, stringsAsFactors = FALSE )
mobileBanking.Df <- mobileBanking.Df[,-1] #Remove the number column which is Irrelevant
Once our sample data set is loaded, we check for features present. We first need to load all the libraries needed for data analysis and manipulation.
#Load required packages or install if not present.----
load.libraries <- c('data.table','tidyverse','gridExtra', 'corrplot', 'GGally', 'ggplot2', 'e1071', 'dplyr')
install.lib <- load.libraries[!load.libraries %in% installed.packages()]
for(libs in install.lib) install.packages(libs, dependences = TRUE)
#Load libraries and flag TRUE
sapply(load.libraries, require, character = TRUE)
The function above takes in a list of required libraries, checks if they are already installed and installs them if not. It then loads all the packages one at a go.
dim(mobileBanking.Df)
## [1] 43 11
The data set has 43 rows with 11 Variables. We therefore explore the data types of each variable/column.
#Check Categorical VS Numeric Characters----
cat_vars <- names(mobileBanking.Df)[which(sapply(mobileBanking.Df, is.character))]
cat_vars
## [1] "Gender" "Age.Range"
## [3] "Have.Bak.Account" "Bank.account.connected.to.MB"
## [5] "MB.used.for" "Importance"
## [7] "Benefit" "Bank.Visit"
## [9] "MB.Safety" "Influence"
## [11] "Satisfaction"
numeric_vars <- names(mobileBanking.Df)[which(sapply(mobileBanking.Df, is.numeric))]
numeric_vars
## character(0)
To identify the data types, we can check for numeric and categorical variables present in the data. In our case, all the variables in our data set are categorical. We will therefore explore the data from a categorical approach rather than numeric. There exists different visualization methods for different data types. Now that we have established the general structure of the data, we can check for missing values, NAs
.
#Checking data for any missing values
colSums(sapply(mobileBanking.Df, is.na))
## Gender Age.Range
## 0 0
## Have.Bak.Account Bank.account.connected.to.MB
## 0 0
## MB.used.for Importance
## 0 0
## Benefit Bank.Visit
## 0 0
## MB.Safety Influence
## 0 0
## Satisfaction
## 0
We have no columns with missing values in our data. We can therefore proceed to analysis without worrying about missing values. In a case whereby there exists NA values, one can choose whether to replace the nulls with the most appropriate values or remove the rows with nulls from the data. This is important for later stages of analysis that include data modelling, like Machine Learning.
#Data Summary----
summary(mobileBanking.Df)
## Gender Age.Range Have.Bak.Account
## Length:43 Length:43 Length:43
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
## Bank.account.connected.to.MB MB.used.for Importance
## Length:43 Length:43 Length:43
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
## Benefit Bank.Visit MB.Safety
## Length:43 Length:43 Length:43
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
## Influence Satisfaction
## Length:43 Length:43
## Class :character Class :character
## Mode :character Mode :character
The base R Summary()
function comes in handy at summarizing data. In our case, there is no statistical measures since all our variables are categorical. Note that the function also specifies the specific data types. There are more than enough ways to inspect data structures in R.
The main goal of descriptive statistics is to inform data analysts on the main features of either numerical or categorical data, using sample summaries represented as either tables, individual numbers or charts and graphs. Since we only have categorical data, I will illustrate the most used forms of descriptive statistics for the same. However, like I mentioned earlier, there are more than enough ways to analyze data in R.
Frequencies illustrate the number of occurrences or observations of a particular category in data. We use contigency tables to present this information. In R this can be achieved using the table() function.
From out data, the total distribution of respondents based on gender looks like this;
#Gender frequencies
#library(kableExtra)
table(mobileBanking.Df$Gender)
##
## Female Male
## 20 23
We can illustrate multiple attributes using cross classification tables such as;
#library(kableExtra)
# Cross classification counts for gender by Mobile banking safety opinion
table(mobileBanking.Df$Gender, mobileBanking.Df$MB.Safety)
##
## NotAtAll Somewhat Very
## Female 3 11 6
## Male 0 19 4
Multidimensional tables with three or more categories can also be achieved using the ftable() . As an example, let’s check out the number of respondents based on gender, mobile banking safety opinion and how often they visit the bank.
#Counts by gender, opinion and bank visits
table_ <- table(mobileBanking.Df$Gender, mobileBanking.Df$MB.Safety, mobileBanking.Df$Bank.Visit)
ftable(table_)
## FewTimesAyear OnceMonth
##
## Female NotAtAll 3 0
## Somewhat 11 0
## Very 5 1
## Male NotAtAll 0 0
## Somewhat 15 4
## Very 4 0
Proportions are basically contingency tables represented as percentages. From our previous tables, we can do proportions for the same by applying prop.table() to output produced by the *table() function. Proportions for the above will then be;
#library(kableExtra)
#Gender frequencies proportions
prop.table(table(mobileBanking.Df$Gender))
##
## Female Male
## 0.4651163 0.5348837
#Percentage idistribution for Gender by mobile banking safety
prop.table(table(mobileBanking.Df$Gender, mobileBanking.Df$MB.Safety))
##
## NotAtAll Somewhat Very
## Female 0.06976744 0.25581395 0.13953488
## Male 0.00000000 0.44186047 0.09302326
#Percentage by gender, opinion and bank visits, rounding off to 2 decimal places
table_ <- table(mobileBanking.Df$Gender, mobileBanking.Df$MB.Safety, mobileBanking.Df$Bank.Visit)
ftable(round(prop.table(table_),2))
## FewTimesAyear OnceMonth
##
## Female NotAtAll 0.07 0.00
## Somewhat 0.26 0.00
## Very 0.12 0.02
## Male NotAtAll 0.00 0.00
## Somewhat 0.35 0.09
## Very 0.09 0.00
Marginals measure counts across columns or rows in a contingency table. Margin.table() gives us the frequencies while prop.table() gives us the percentages. Using our previous examples on frequencies;
# FREQUENCY MARGINALS
# row marginals - totals for each gender across mobile banking opinion
margin.table(table(mobileBanking.Df$Gender, mobileBanking.Df$MB.Safety), 1)
##
## Female Male
## 20 23
# colum marginals - totals for each gender across mobile banking opinion
margin.table(table(mobileBanking.Df$Gender, mobileBanking.Df$MB.Safety), 2)
##
## NotAtAll Somewhat Very
## 3 30 10
# PERCENTAGE MARGINALS
# row marginals - row percentages across gender
prop.table(table(mobileBanking.Df$Gender, mobileBanking.Df$MB.Safety), margin = 1)
##
## NotAtAll Somewhat Very
## Female 0.150000 0.550000 0.300000
## Male 0.000000 0.826087 0.173913
# colum marginals - column percentages acrossmobile banking opinion
prop.table(table(mobileBanking.Df$Gender, mobileBanking.Df$MB.Safety), margin = 2)
##
## NotAtAll Somewhat Very
## Female 1.0000000 0.3666667 0.6000000
## Male 0.0000000 0.6333333 0.4000000
The code chunk bellow is a function that takes in our data set and plots all the present variables in it. Since we have categorical variable only, we will use bar plots for visualization. They are the most appropriate for categorical data.
#Loading Data into R toc_depth: 2
mobileBanking.Df <- read.csv("J://Personalprojects//Blogsite//data//MobileBankinginKenya.csv", header = TRUE, stringsAsFactors = FALSE )
mobileBanking.Df <- mobileBanking.Df[,-1] #Remove the number column which is Irrelevant
#Check Categorical VS Numeric Characters----
cat_vars <- names(mobileBanking.Df)[which(sapply(mobileBanking.Df, is.character))]
numeric_vars <- names(mobileBanking.Df)[which(sapply(mobileBanking.Df, is.numeric))]
####Convert character to factors----
library(data.table)
setDT(mobileBanking.Df)[,(cat_vars) := lapply(.SD, as.factor), .SDcols = cat_vars]
mobileBanking.Df_cat <- mobileBanking.Df[,.SD, .SDcols = cat_vars]
##mobileBanking.Df_cont <- mobileBanking.Df[,.SD,.SDcols = numeric_vars]
#Functions for Plots---
library(ggplot2)
library(gridExtra)
plotHist <- function(data_in, i) {
data <- data.frame(x=data_in[[i]])
p <- ggplot(data=data, aes(x=factor(x))) + stat_count() + xlab(colnames(data_in)[i]) + theme_light() +
theme(axis.text.x = element_text(angle = 90, hjust =1))
return (p)
}
doPlots <- function(data_in, fun, ii, ncol=3) {
pp <- list()
for (i in ii) {
p <- fun(data_in=data_in, i=i)
pp <- c(pp, list(p))
}
do.call("grid.arrange", c(pp, ncol=ncol))
}
plotDen <- function(data_in, i){
data <- data.frame(x=data_in[[i]], SalePrice = data_in$SalePrice)
p <- ggplot(data= data) + geom_line(aes(x = x), stat = 'density', size = 1,alpha = 1.0) +
xlab(paste0((colnames(data_in)[i]), '\n', 'Skewness: ',round(skewness(data_in[[i]], na.rm = TRUE), 2))) + theme_light()
return(p)
}
#Plotting categorical values----
#Bar plots
doPlots(mobileBanking.Df_cat, fun = plotHist, ii = 1:4, ncol = 2)
It can be seen that a larger number of respondents were male, this is however by a small margin. If we had a larger data set we could have more female respondents.
A majority of respondents were younger guys between age 21-30, followed by the 31-40 age bracket. The least respondents were those above age 41. This could be probably because the older people chose not to participate in the survey as opposed to the younger ones, or that they somehow never got to opportunity to do so. A good example is the medium by which the survey was conducted, which the older people didn’t have.
All the respondents had bank accounts. A very small number had their business bank accounts linked to mobile banking. Majority had linked their current accounts probably due to the convenience that comes with mobile banking like frequent or timeless withdrawals.
Most respondents use mobile banking services for making payments. This is followed by cash withdrawals. Airtime purchase and money transfer happen to be the least uses for the service. This could be because they are easily accessible needs unlike cash withdrawal and making payments in terms of mobility convenience.
Most respondents found mobile banking services very important, probably owing to the affordable cost charges and good service which could mean less usability issues when using the services.
We had most users who visit their banks a few times a year while the least do it once a month. This means that generally, fewer people visit the bank physically. This could be a major impact of mobile banking services.
Despite being majorly satisfied by the services, most respondents did not find mobile banking services very safe. It is also seen as time saving which is probably why we had very few bank visits in general.
It can be concluded that mobile banking is mainly preferred by younger people, a majority being of the male gender. However, the only benefit most users find from mobile banking seems to be the convenience it brings. Safety is still a major concern.
That’s basically it for exploratory data analysis. I made sure to cover the basics, meaning there’s still much to be added on to this; more visualizations, packages that simplify the whole process etc…This is to be continued. For a detailed documentation on the same, here’s Hadley Wickham’s R for Data Science book you can use as a reference point.


Keyboard shortcuts for to execute code blocks, code chunks, and equations in display form using CTRL-enter (CMD-enter on macOS)
Added options to set tab size (tabSize), replace tabs by spaces (useSoftTabs), and show invisible characters (showInvisibles). See
Upgrade to Ace 1.3.0 (https://github.com/ajaxorg/ace-builds/releases)
Allow toggling of search-replace using CMD-f (CTRL-f on Windows). See https://github.com/ajaxorg/ace/issues/3552)
Clear editor using "" (@dmenne #30)
Fix when ace is initialized with \r or \f (@The-Dub #46)
Fix for auto complete in shiny modules (@GregorDeCillia #47 and PR54)
Note: This fix required a breaking change (i.e., the aceAutocomplete
function now uses inputid_shinAce_hint
rather than the the old shinyAce_inputid_hint
)
Fix for auto complete lists (@Ping2016 #48 and @saurfang (PR52)
Improved configuration options for auto completers by @saurfang ([PR53]https://github.com/trestletech/shinyAce/pull/53))
Upgrade to Ace 1.1.8
Add code autocompletion (@saurfang, #21)
Added input debouncing
Add shortcut and cursor listeners (@skranz, #16)
Added word wrapping (@ncarchedi, #12)
Added vim key bindings (@Vincent, #9)


Mirrored is a wrapper for the mirrored del.icio.us and ma.gnolia apis.
Installation
$ sudo gem install mirrored
Usage
Establish A Connection
# to magnolia
Mirrored::Base.establish_connection(:magnolia, 'jnunemaker', 'password')
# or to delicious
Mirrored::Base.establish_connection(:delicious, 'jnunemaker', 'password')
# then use any of the examples below
Last Update
Mirrored::Update.last # => ruby time object equal to last update
Posts
# => posts
Mirrored::Post.find(:get)
# => posts tagged ruby
Mirrored::Post.find(:get, :tag => 'ruby')
# => posts tagged ruby on oct. 5, 2007
Mirrored::Post.find(:get, :tag => 'ruby', :dt => '2007-10-05')
# => posts with url http://addictedtonew
Mirrored::Post.find(:get, :url => 'http://addictedtonew')
# => all posts (use sparingly according to delicious and magnolia)
Mirrored::Post.find(:all)
# => all posts for tag ruby (use sparingly according to delicious and magnolia)
Mirrored::Post.find(:all, :tag => 'ruby')
# most recent posts
Mirrored::Post.find(:recent)
# => most recent posts for tag ruby
Mirrored::Post.find(:recent, :tag => 'ruby')
# => 5 most recent posts for tag ruby
Mirrored::Post.find(:recent, :tag => 'ruby', :count => '5')
Tags
# gets list of all tags and the number of times you've used them
Mirrored::Tag.find(:get)
# Rename a tag
Mirrored::Tag.rename('microsoft', 'suckfest')
Dates
# => finds all dates you have posted with counts for each day
Mirrored::Date.find(:all)
# => finds all dates you have posted something tagged ruby with counts for each day
Mirrored::Date.find(:all, :tag => 'ruby')


Instructions
Below we have a blank component. Inside of the
render
method we want to return a <div>
with the text Hello World!
.


Generates the primary RestfulX project directory structure and sets up Flex Builder and TextMate specific descriptor files You can generate Flex Builder configuration for either *pure* Flex project or an AIR project. To generate AIR configuration pass the -a (--air) option to the generator.
Examples:
`rx-gen pomodo` # generates project structure and a # default Flex app configuration. `rx-gen -a pomodo` # as above but generates an AIR app # and configuration
Next Steps:
In your new RestfulX project folder run `ruby script/generate` for a list of available generators.
Required Files
- rubygems
- rubigen
- rubigen/scripts/generate


"Alright ladies and gents! Let's roll!"
"Alright ladies and gents! Let's roll!"
Front Line DPS: Rayman can leap around the enemy party dealing Damage, as well as helping his teammates avoid enemy Control Abilities
| Health | 78 | Health | 160 | |
| Physical Attack | 7.3 | Physical Attack | 15 | |
| Magic Attack | 0 | Magic Attack | 0 | |
| Physical Armor | 2.8 | Physical Armor | 5.8 | |
| Magic Armor | 2.7 | Magic Armor | 5.4 |
None
Rayman gets a pair of blue boxing gloves which immediately hit the enemies in front of Rayman, dealing Physical Damage. After getting these boxing gloves, his Basic Attacks and Ultimate will deal Additional Damage for the rest of the wave. If he uses his Ultimate again during the wave, the gloves will turn red, becoming more powerful and adding a Damage-over-Time effect which can stack
Rayman winds up, then reaches further and punches harder than usual, dealing Damage and Knocking an enemy back (while winding up, he is immune to control abilities)
Rayman steps on his enemies' heads several times, dealing Physical Damage and momentarily Stunning them. While using this ability he is immune to Control Abilities and has an increased Dodge Rating. The amount of times he can leap between enemies is equal to the amount of Stars he has. On his final leap, he will smash the ground, dealing Damage over a small area and Lifting nearby enemies. The Damage dealt by this final leap depends on the number of leaps he made previously
If Rayman steps on 7 enemies while using "Leap and Smash" over the course of a wave, Rayman will earn one heart. Each heart will protect Rayman from taking a fatal amount of Damage one time. Instead of dying he will gain some Health and be immortal for a short period. The hearts may protect Rayman a maximum of twice per wave
Rayman reduces the amount of time nearby allied Heroes are affected by enemy Control Abilities
*Key items required to fuse up to Orange+2 and fully equip. Not all items required for fusions listed. Signature Item not included.


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P1 There are lots of different kinds of fruit - there are over 500 varieties of banana alone. By the time we add the countless type of apples, oranges and other well-known fruit, we are faced with thousands of choices. p2 There are lots of different kinds of fruit - there are over 500 varieties of banana alone. By the time we add the countless type of apples, oranges and other well-known fruit, we are faced with thousands of choices. P3 There are lots of different kinds of fruit - there are over 500 varieties of banana alone. By the time we add the countless type of apples, oranges and other well-known fruit, we are faced with thousands of choices.


KING COIN
-
What?
This is a Decentralized Application (Dapp). You can rule your own countries and write your own message on them. The leaderboard shows the wealthiest countries.
-
What's in it for me?
Once you own a country you're now it's king. You message will be displayed on that countries page. Each time a country is bought, it's price increases by 20%.

-
So now what?
Continue to the site. Explore it on the BSC main net or the BSC test net.
-
Goal?
Have an all-out blockchain-enabled World War with everyone fighting for the wealthiest kingdoms.
Disclaimer: for the best experience, use a desktop!


记忆话搜索，要注意不能出现重复情况。
| Coin Change |
Suppose there are 5 types of coins: 50-cent, 25-cent, 10-cent,
5-cent, and 1-cent. We want to make changes with these coins for a
given amount of money.
For example, if we have 11 cents, then we can make changes with one
10-cent coin and one 1-cent coin, two 5-cent coins and one 1-cent
coin, one 5-cent coin and six 1-cent coins, or eleven 1-cent coins.
So there are four ways of making changes for 11 cents with the
above coins. Note that we count that there is one way of making
change for zero cent.
Write a program to find the total number of different ways of
making changes for any amount of money in cents. Your program
should be able to handle up to 7489 cents.
Input
The input file contains any number of lines, each one consisting of
a number for the amount of money in cents.
Output
For each input line, output a line containing the number of
different ways of making changes with the above 5 types of coins.
Sample
Input
11
26
Sample
Output
4
13
代码：
#include<iostream>
#include<algorithm>
#include<cstring>
#include<fstream>
#define maxn 7500
using namespace std;
int coin[6]={0,1,5,10,25,50};
int num;
int d[maxn][6];
int dp(int s,int k){
if(d[s][k]!=-1){
return d[s][k];
}
d[s][k]=0;
for(long i=k;i<=5&&s>=coin[i];i++)
d[s][k]+=dp(s-coin[i],i);
return d[s][k];
}
int main()
{
// freopen("test.txt","r",stdin);
memset(d,-1,sizeof(d));
for(int i=0;i<=5;i++)d[0][i]=1;
while(cin>>num){
cout<<dp(num,1)<<endl;
}
return 0;
}


1
0
Features
2021-04-24 09:30:37 PM
Tags
Feature
Title
Passed
Failed
Scenarios
Time (ms)
tester/api/api_delete.feature
sample karate test script
1
0
1
532


|
cds
1.2.0
|
Michael's ordered list (key-value pair) More...
#include <cds/container/michael_kvlist_impl.h>
Public Types | |
| typedef Key | key_type |
| Key type. | |
| typedef Value | value_type |
| Type of value stored in the list. | |
|
typedef std::pair< key_type const, value_type > | pair_type |
| key/value pair stored in the list | |
| typedef base_class::gc | gc |
| Garbage collector used. | |
| typedef base_class::back_off | back_off |
| Back-off strategy used. | |
| typedef options::allocator_type | allocator_type |
| Allocator type used for allocate/deallocate the nodes. | |
| typedef base_class::item_counter | item_counter |
| Item counting policy used. | |
| typedef options::key_comparator | key_comparator |
| key comparision functor | |
| typedef base_class::memory_model | memory_model |
| Memory ordering. See cds::opt::memory_model option. | |
| typedef iterator_type< false > | iterator |
| Forward iterator. | |
| typedef iterator_type< true > | const_iterator |
| Const forward iterator. |
Public Member Functions | |
| iterator | begin () |
| Returns a forward iterator addressing the first element in a list. | |
| iterator | end () |
| Returns an iterator that addresses the location succeeding the last element in a list. | |
| const_iterator | begin () const |
| Returns a forward const iterator addressing the first element in a list. | |
| const_iterator | end () const |
| Returns an const iterator that addresses the location succeeding the last element in a list. | |
| MichaelKVList () | |
| Default constructor. | |
| ~MichaelKVList () | |
| List desctructor. | |
| template<typename K > | |
| bool | insert (const K &key) |
| Inserts new node with key and default value. | |
| template<typename K , typename V > | |
| bool | insert (const K &key, const V &val) |
| Inserts new node with a key and a value. | |
| template<typename K , typename Func > | |
| bool | insert_key (const K &key, Func func) |
| Inserts new node and initialize it by a functor. | |
| template<typename K > | |
| bool | erase (const K &key) |
Delete key from the list. | |
| template<typename K , typename Func > | |
| bool | erase (const K &key, Func f) |
Get value of item with key by a functor and delete it. | |
| template<typename K , typename Func > | |
| std::pair< bool, bool > | ensure (const K &key, Func f) |
Ensures that the key exists in the list. | |
| template<typename Q > | |
| bool | find (const Q &key) |
Find the key key . | |
| template<typename Q , typename Func > | |
| bool | find (const Q &key, Func f) |
Find the key key and perform an action with it. | |
| bool | empty () const |
| Check if the list is empty. | |
| size_t | size () const |
| Returns list's item count. | |
| void | clear () |
| Clears the list. |
Additional Inherited Members | |
| Protected Types inherited from cds::intrusive::MichaelList< GC, implementation_defined, Traits > | |
| typedef implementation_defined | value_type |
| type of value stored in the list | |
| typedef Traits | options |
| Traits template parameter. | |
| typedef options::hook | hook |
| hook type | |
| typedef hook::node_type | node_type |
| node type | |
| typedef implementation_defined | key_comparator |
| key comparision functor based on opt::compare and opt::less option setter. | |
| typedef options::disposer | disposer |
| disposer used | |
|
typedef get_node_traits < value_type, node_type, hook > ::type | node_traits |
| node traits | |
|
typedef michael_list::get_link_checker < node_type, options::link_checker >::type | link_checker |
| link checker | |
| typedef GC | gc |
| Garbage collector. | |
| typedef options::back_off | back_off |
| back-off strategy | |
| typedef options::item_counter | item_counter |
| Item counting policy used. | |
| typedef options::memory_model | memory_model |
| Memory ordering. See cds::opt::memory_model option. | |
| typedef iterator_type< false > | iterator |
| Forward iterator. | |
| typedef iterator_type< true > | const_iterator |
| Const forward iterator. | |
|
typedef node_type::atomic_marked_ptr | atomic_node_ptr |
| Atomic node pointer. | |
| typedef node_type::marked_ptr | marked_node_ptr |
| Node marked pointer. | |
| typedef atomic_node_ptr | auxiliary_head |
| Auxiliary head type (for split-list support) | |
| Protected Member Functions inherited from cds::intrusive::MichaelList< GC, implementation_defined, Traits > | |
| MichaelList () | |
| Default constructor initializes empty list. | |
| ~MichaelList () | |
| Destroy list. | |
| bool | insert (value_type &val) |
| Inserts new node. | |
| bool | insert (value_type &val, Func f) |
| Inserts new node. | |
| std::pair< bool, bool > | ensure (value_type &val, Func func) |
Ensures that the item exists in the list. | |
| bool | unlink (value_type &val) |
Unlink the item val from the list. | |
| bool | erase (const Q &val) |
| Delete the item from the list. | |
| bool | erase (const Q &val, Func func) |
| Delete the item from the list. | |
| bool | find (Q &val, Func f) |
Find the key val . |
Michael's ordered list (key-value pair)
This is key-value variation of non-intrusive MichaelList. Like standard container, this implementation split a value stored into two part - constant key and alterable value.
Template arguments:
GC
- garbage collector usedKey
- key type of an item stored in the list. It should be copy-constructibleValue
- value type stored in a listTraits
- type traits, default is michael_list::type_traitsIt is possible to declare option-based list with cds::container::michael_list::make_traits metafunction istead of Traits
template argument. For example, the following traits-based declaration of gc::HP Michael's list
is equivalent for the following option-based list
Template argument list Options
of cds::container::michael_list::make_traits metafunction are:
std::less<T>
.| typedef iterator_type<true> cds::container::MichaelKVList< GC, Key, Value, Traits >::const_iterator |
Const forward iterator.
For iterator's features and requirements see iterator
| typedef iterator_type<false> cds::container::MichaelKVList< GC, Key, Value, Traits >::iterator |
Forward iterator.
The forward iterator for Michael's list has some features:
Therefore, the use of iterators in concurrent environment is not good idea. Use the iterator on the concurrent container for debug purpose only.
The iterator interface to access item data:
operator ->
- returns a pointer to pair_type for iterator operator *
- returns a reference (a const reference for const_iterator
) to pair_type for iterator const key_type& key()
- returns a key reference for iterator value_type& val()
- retuns a value reference for iterator (const reference for const_iterator
)For both functions the iterator should not be equal to end()
|
inline |
Default constructor.
Initialize empty list
|
inline |
List desctructor.
Clears the list
|
inline |
Returns a forward iterator addressing the first element in a list.
For empty list
Reimplemented from cds::intrusive::MichaelList< GC, implementation_defined, Traits >.
|
inline |
Clears the list.
Post-condition: the list is empty
Reimplemented from cds::intrusive::MichaelList< GC, implementation_defined, Traits >.
|
inline |
Returns an iterator that addresses the location succeeding the last element in a list.
Do not use the value returned by end
function to access any item. Internally, end
returning value equals to NULL
.
The returned value can be used only to control reaching the end of the list. For empty list
Reimplemented from cds::intrusive::MichaelList< GC, implementation_defined, Traits >.
|
inline |
Ensures that the key
exists in the list.
The operation performs inserting or changing data with lock-free manner.
If the key
not found in the list, then the new item created from key
is inserted into the list (note that in this case the key_type should be copy-constructible from type K
). Otherwise, the functor func
is called with item found. The functor Func
may be a function with signature:
or a functor:
with arguments:
bNew
- true
if the item has been inserted, false
otherwiseitem
- item of the listThe functor may change any fields of the item.second
that is value_type; however, func
must guarantee that during changing no any other modifications could be made on this item by concurrent threads.
You may pass func
argument by reference using boost::ref
.
Returns std::pair<bool, bool>
where first
is true if operation is successfull, second
is true if new item has been added or false
if the item with key
already is in the list.
|
inline |
Delete key
from the list.
Return true
if key
is found and has been deleted, false
otherwise
|
inline |
Get value of item with key
by a functor and delete it.
The function searches an item with key key
, calls f
functor and deletes the item. If key
is not found, the functor is not called.
The functor Func
interface:
The functor may be passed by reference with boost:ref
Return true
if key is found and deleted, false
otherwise
See also: erase
|
inline |
Find the key key
.
The function searches the item with key equal to key
and returns true
if it is found, and false
otherwise
Reimplemented from cds::intrusive::MichaelList< GC, implementation_defined, Traits >.
|
inline |
Find the key key
and perform an action with it.
The function searches an item with key equal to key
and calls the functor f
for the item found. The interface of Func
functor is:
where item
is the item found.
You may pass f
argument by reference using boost::ref
or cds::ref.
The functor may change item.second
that is reference to value of node. Note that the function is only guarantee that item
cannot be deleted during functor is executing. The function does not serialize simultaneous access to the list item
. If such access is possible you must provide your own synchronization schema to exclude unsafe item modifications.
The function returns true
if key
is found, false
otherwise.
|
inline |
Inserts new node with key and default value.
The function creates a node with key
and default value, and then inserts the node created into the list.
Preconditions:
K
. In trivial case, K
is equal to key_type.Returns true
if inserting successful, false
otherwise.
|
inline |
Inserts new node with a key and a value.
The function creates a node with key
and value val
, and then inserts the node created into the list.
Preconditions:
key
of type K
.val
of type V
.Returns true
if inserting successful, false
otherwise.
|
inline |
Inserts new node and initialize it by a functor.
This function inserts new node with key key
and if inserting is successful then it calls func
functor with signature
The argument item
of user-defined functor func
is the reference to the list's item inserted. item.second
is a reference to item's value that may be changed. User-defined functor func
should guarantee that during changing item's value no any other changes could be made on this list's item by concurrent threads. The user-defined functor can be passed by reference using boost::ref
and it is called only if inserting is successful.
The key_type should be constructible from value of type K
.
The function allows to split creating of new item into two part:
key
;func
functorThis can be useful if complete initialization of object of value_type
is heavyweight and it is preferable that the initialization should be completed only if inserting is successful.
|
inline |
Returns list's item count.
The value returned depends on opt::item_counter option. For atomicity::empty_item_counter, this function always returns 0.
Warning: even if you use real item counter and it returns 0, this fact is not mean that the list is empty. To check list emptyness use empty() method.
Reimplemented from cds::intrusive::MichaelList< GC, implementation_defined, Traits >.


{% extends "_post.html" %} {%hyde title: "Slashdot looking for open proxies?" created: 2008-08-25 16:24:04 %} {% block article %} {%article%}
I saw the following somewhat-strange line in my web server logs today:
<IP_ADDRESS> - - [25/Aug/2008:10:23:51 -0500] "GET http://tech.slashdot.org/ok.txt HTTP/1.0" 401 523 "-" "libwww-perl/5.812"
That web server is running on the IP of my home router. The requesting IP appears to be a Slashdot machine. My guess is that they are trying to find out who accesses their site through an open proxy. But why? Is there another reason they might send a request like that? Do they ban proxies if they find one?
UPDATE: Apparently, they do in fact ban open proxies (according to this). Supposedly a lot of comment spam comes from them. I wonder if it would help blogs at all to do something similar?
{%endarticle%} {% endblock %}


{% extends 'layout.html' %} {% block title %}User settings{% endblock %} {% block content %}
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