Harry’s bar is one of the most popular bar chains in Singapore. It has an iOS app “Appy Hour” that lets users spin the Harry’s “wheel of fortune” to win free drinks. The way it works is that a user would visit one of their strategically located bars and check in using the app. He would then spin the wheel, and if he is lucky, he would win a free drink. A time limit is imposed so that a user can spin the wheel only once in 24 hours while signed in a particular bar.
Now there may not be any such thing as a free lunch, but there are free drinks! Let’s see how.
The ‘luck factor’
The app communicates with www.exhost.se
over HTTP. When started, the first thing the app does is to define the “luck factor” of the user, by downloading an XML file containing probabilities of various prizes. The probabilities are set in way such that 52% of the time a spin would yield ‘Better Luck Next Time’.
GET /harrys_1_1_beta/venues.xml HTTP/1.1
Host: www.exhost.se
User-Agent: Appy Hour 1.1.0 (iPhone; iPhone OS 6.0.1; en_SG)
Connection: keep-alive
Accept-Encoding: gzip
HTTP/1.1 200 OK
Age: 1659
Connection: Keep-Alive
Content-Length: 3071
Content-Type: application/xml
Date: Fri, 01 Nov 2013 06:27:45 GMT
ETag: "3c8066-bff-4d7ddfaa98300"
Last-Modified: Thu, 14 Mar 2013 08:05:00 GMT
Server: Apache/2.2.22 (Unix) mod_ssl/2.2.22 OpenSSL/0.9.8e-fips-rhel5 DAV/2 mod_bwlimited/1.4 mod_fcgid/2.3.6
Via: 1.1 qt-mfc4:80
<?xml version="1.0" encoding="UTF-8"?>
<Prizes>
<Prize>
<Description>Better Luck*Next Time</Description>
<Units>1</Units>
<ID>1</ID>
<Active>1</Active>
<Possibility>13</Possibility>
<IsPrize>0</IsPrize>
<PrizeFile>img/1.png</PrizeFile>
</Prize>
<Prize>
<Description>1-for-1 Bacardi*Sup Gls</Description>
<Units>1</Units>
<ID>2</ID>
<Active>1</Active>
<Possibility>5</Possibility>
<IsPrize>1</IsPrize>
<PrizeFile>img/2.png</PrizeFile>
</Prize>
--snipped--
Time Restriction
Once the user has checked in the bar, the app checks if the user has already tried his luck in the past 24 hours in the same bar. It does so by sending a request with the iPhone’s UDID, a timestamp and the bar’s id. The response simply consists of true
if the user is allowed to spin the wheel, or false
otherwise.
GET /harrys_1_1_beta/fetchdata.php?udid=aba5372762118af8f6f0594f836cd0eb32d10986&time=2013-01-11%02:56:15&venue=30 HTTP/1.1
Host: www.exhost.se
User-Agent: Appy Hour 1.1.0 (iPhone; iPhone OS 6.0.1; en_SG)
Connection: keep-alive
Accept-Encoding: gzip
HTTP/1.1 200 OK
Date: Fri, 01 Nov 2013 06:56:16 GMT
Server: Apache/2.2.22 (Unix) mod_ssl/2.2.22 OpenSSL/0.9.8e-fips-rhel5 DAV/2 mod_bwlimited/1.4 mod_fcgid/2.3.6
X-Powered-By: PHP/5.3.10
Keep-Alive: timeout=5, max=100
Connection: Keep-Alive
Transfer-Encoding: chunked
Content-Type: text/html
true
Getting past everything
Well, the simplest way to get past everything would be to make the app communicate with another server instead of www.exhost.se
. First we will crawl www.exhost.se
to get all the required files. The link http://www.exhost.se/harrys_1_1_beta/
does not contain a default index.html
or similar file, which makes crawling possible.
$ wget -nv -r --no-parent --reject "index.html*" http://www.exhost.se/harrys_1_1_beta/
2013-11-03 23:37:09 URL:http://www.exhost.se/harrys_1_1_beta/ [639/639] -> /"www.exhost.se/harrys_1_1_beta/index.html" [1]
http://www.exhost.se/robots.txt:
2013-11-03 23:37:09 ERROR 404: Not Found.
2013-11-03 23:37:10 URL:http://www.exhost.se/harrys_1_1_beta/cms.php [169] -> "www.exhost.se/harrys_1_1_beta/cms.php" [1]
2013-11-03 23:37:10 URL:http://www.exhost.se/harrys_1_1_beta/connect.php [0/0] -> "www.exhost.se/harrys_1_1_beta/connect.php" [1]
2013-11-03 23:37:10 URL:http://www.exhost.se/harrys_1_1_beta/fetchdata.php [5] -> "www.exhost.se/harrys_1_1_beta/fetchdata.php" [1]
2013-11-03 23:37:11 URL:http://www.exhost.se/harrys_1_1_beta/img/ [1037/1037] -> "www.exhost.se/harrys_1_1_beta/img/index.html" [1]
2013-11-03 23:37:11 URL:http://www.exhost.se/harrys_1_1_beta/js/ [461/461] -> "www.exhost.se/harrys_1_1_beta/js/index.html" [1]
2013-11-03 23:37:12 URL:http://www.exhost.se/harrys_1_1_beta/venues.xml [3071/3071] -> "www.exhost.se/harrys_1_1_beta/venues.xml" [1]
2013-11-03 23:37:19 URL:http://www.exhost.se/harrys_1_1_beta/img/1.png [50769/50769] -> "www.exhost.se/harrys_1_1_beta/img/1.png" [1]
2013-11-03 23:37:23 URL:http://www.exhost.se/harrys_1_1_beta/img/10.png [62543/62543] -> "www.exhost.se/harrys_1_1_beta/img/10.png" [1]
2013-11-03 23:37:24 URL:http://www.exhost.se/harrys_1_1_beta/img/11.png [23376/23376] -> "www.exhost.se/harrys_1_1_beta/img/11.png" [1]
2013-11-03 23:37:26 URL:http://www.exhost.se/harrys_1_1_beta/img/12.png [33471/33471] -> "www.exhost.se/harrys_1_1_beta/img/12.png" [1]
2013-11-03 23:37:29 URL:http://www.exhost.se/harrys_1_1_beta/img/13.png [58419/58419] -> "www.exhost.se/harrys_1_1_beta/img/13.png" [1]
2013-11-03 23:37:31 URL:http://www.exhost.se/harrys_1_1_beta/img/14.png [50769/50769] -> "www.exhost.se/harrys_1_1_beta/img/14.png" [1]
2013-11-03 23:37:32 URL:http://www.exhost.se/harrys_1_1_beta/img/15.png [50119/50119] -> "www.exhost.se/harrys_1_1_beta/img/15.png" [1]
2013-11-03 23:37:33 URL:http://www.exhost.se/harrys_1_1_beta/img/16.png [23376/23376] -> "www.exhost.se/harrys_1_1_beta/img/16.png" [1]
2013-11-03 23:37:34 URL:http://www.exhost.se/harrys_1_1_beta/img/2.png [44208/44208] -> "www.exhost.se/harrys_1_1_beta/img/2.png" [1]
2013-11-03 23:37:36 URL:http://www.exhost.se/harrys_1_1_beta/img/3.png [62543/62543] -> "www.exhost.se/harrys_1_1_beta/img/3.png" [1]
2013-11-03 23:37:38 URL:http://www.exhost.se/harrys_1_1_beta/img/4.png [50769/50769] -> "www.exhost.se/harrys_1_1_beta/img/4.png" [1]
2013-11-03 23:37:40 URL:http://www.exhost.se/harrys_1_1_beta/img/5.png [60030/60030] -> "www.exhost.se/harrys_1_1_beta/img/5.png" [1]
2013-11-03 23:37:44 URL:http://www.exhost.se/harrys_1_1_beta/img/6.jpg [124823/124823] -> "www.exhost.se/harrys_1_1_beta/img/6.jpg" [1]
2013-11-03 23:37:46 URL:http://www.exhost.se/harrys_1_1_beta/img/6.png [50119/50119] -> "www.exhost.se/harrys_1_1_beta/img/6.png" [1]
2013-11-03 23:37:47 URL:http://www.exhost.se/harrys_1_1_beta/img/7.png [45129/45129] -> "www.exhost.se/harrys_1_1_beta/img/7.png" [1]
2013-11-03 23:37:49 URL:http://www.exhost.se/harrys_1_1_beta/img/8.png [50769/50769] -> "www.exhost.se/harrys_1_1_beta/img/8.png" [1]
2013-11-03 23:37:50 URL:http://www.exhost.se/harrys_1_1_beta/img/9.png [40394/40394] -> "www.exhost.se/harrys_1_1_beta/img/9.png" [1]
2013-11-03 23:37:52 URL:http://www.exhost.se/harrys_1_1_beta/js/jquery.min.js [85925/85925] -> "www.exhost.se/harrys_1_1_beta/js/jquery.min.js" [1]
FINISHED --2013-11-03 23:37:52--
Total wall clock time: 54s
Downloaded: 25 files, 950K in 34s (28.1 KB/s)
iPhone:~ root# strings -o /var/mobile/Applications/0B57A351-CE6D-4B05-A5D0-8B12BB150791/Harrys.app/Harrys | grep "http://www.exhost.se"
839501 http://www.exhost.se/harrys_1_1_beta/
842849 http://www.exhost.se/harrys_1_1_beta/venues.xml
843075 http://www.exhost.se/harrys_1_1_beta/fetchdata.php
Once we have the crawled files, we can edit the venues.xml
file to change the probabilities. We can even change the drinks! ;-) Also, the file fetchdata.php
should contain true
for us to spin any number of times. Now these files can be hosted on a different server and these URLs can be changed in the app mach-o binary. Changing only the above two URLs is sufficient to make it work without any restrictions. The strings utility comes handy when trying to find out the location of these strings in the binary. These strings can now be edited using a hex editor.
Once edited, we can run the app any number of times while signed in the same bar, and win a drink on every spin!
Cheers!


Development of the Low Energy (N,Z) (LENZ) experimental program at WNR/LANSCE.
Developing digital data acquisition systems, along with unpacking and analysis codes, for the LENZ experimental program
Investigation of the H production reaction 55Mn(n,p) for core structural materials to be used in future nuclear reactor designs.
Performed cross-section measurements on the 55Mn(n,p) reaction using LENZ to investigate the influence of this reaction as a source of neutron irradiation damage in structural materials in future fission and fusion devices
Investigations of neutron irradiation damage in F-M steels through precision measurements of the He gas production reactions
Performed 56Fe(n,a) reaction cross-section measurements using LENZ to better understand He production rates in various F-M steels materials to be used in future reactor core designs
Investigation of uncertainties in the 35Cl(n,p) reaction as a neutron energy probe in CLYC detectors.
Performed 35Cl(n,p) reaction measurements with LENZ to better constrain resonance region cross-sections to improve uncertainties in this reaction as a neutron energy probe in CLYC detectors
Investigation of (α,p) reaction rates along the αp-process path in Type 1 X-ray Bursts
Measurements of α-capture resonance states in 18Ne, 30S, and 38Ca through the (p,t) reaction with the K600 spectrometer to indirectly calculate 14O(α,p)17F, 26Si(α,p)30S, and 34Ar(α,p)38Ca reaction rates, respectively
Investigation of 44Ti synthesis in core collapse super novae through the indirect measurement of the 44Ti(α,p)47V reaction rate.
Coincidence measurements of α-capture resonance states in 48Cr using the 50Cr(p,t)48Cr reaction with the K600 spectrometer and CAKE Si array system to indirectly measure the 44Ti(α,p)47V reaction rate at relevant stellar temperatures.
Study of 44Ti synthesis in core collapse super novae through the indirect measurement of the 45V(p,γ)46Cr reaction rate
Performed 50Cr(α,8He)46Cr reaction measurements using the Grand Raiden spectrograph in order to probe (p,γ) resonances in 46Cr. By studying resonance properties in 46Cr, the 45V(p,γ)46Cr reaction rate can be indirectly determined
Performed indirect measurements of the 38Ca(α,p)41Sc reaction rate at explosive burning temperatures in XRB’s
Performed measurements of α-unbound states in 42Ti through the 46Ti(α,8He) reactions using the Grand Raiden magnetic spectrometer to calculate the 38Ca(α,p)41Sc reaction rate at explosive burning temperatures in XRB’s
Investigation of the 22Ne(α,n)25Mg reaction as an effective neutron source for the s-process during core helium burning in Red Giant stars and helium shell burning in AGB stars.
Performed experiments probing sub and near neutron-threshold levels in 26Mg through the 22Ne(α,α’), 22Ne(6Li,d), and 25Mg(d,p) reactions using the Grand Raiden magnetic spectrometer to indirectly measure 22Ne(α,γ) and 22Ne(α,n) reaction rates at relevant stellar temperatures.
Investigation of neutron background at potential sites for the DIANA project (now called CASPER).
Participated in neutron background measurements at two potential sites for the underground accelerator project DIANA, Sanford Underground Research Facility (SURF) and the Waste Isolation Pilot Plant (WIPP). Neutron Background measurements were made using 3He proportional counters
Reconstruction of the HIgh Pressure POint like gas target (HIPPO) with implementation of gas recirculation capabilities
Worked in collaboration on the reconstruction of the supersonic helium jet gas target system, HIPPO, at the NSL with newly upgraded pumping lines and roots blower pumps, along with the implementation of a recirculation gas system.
Auxiliary research assistant at the Nuclear Science Laboratory for outside users
Operation of the 10.6 MV FN Tandem and 5 MV Van der Graaf accelerators.
Operation of MC-SNICS Sputter Ion Source, Helium ion source (HIS), and Electron Cyclotron Resonance ion source.
Participated in an experiment measuring the 19F(α,n) reaction cross section for safeguard purposes using the neutron detector array, VANDLE.
Participated in three commissioning experiments for a the 4π summing NaI(Tl) detector, SuN.


The following table is built with JSON data from this URL:
https://api.github.com/users/nathansmith
Text listed in red refer to JSON keys. Adjacent text is each respective value.
red
View the source files here:
./assets/js/index.js
./assets/styles/index.css
Loading…


The Iron Triangle of Project Management
A simple demonstration of the
iron triangle of project management
using the
Cassowary constraint solving toolkit
.
+
+
{{cutlineIndex}}


16 to 19 providers (non-academy)
Contact form https://form.education...
For local authorities, schools, colleges and other (non-academy) providers contacting the Education Funding Agency.
Guidance
A user guide and technical annex to support the December 2016 release of 16 to 18 FE data and management information.
Local authorities (LAs) can now access the December 2016 release of 16 to 18 FE data and management information (MI) pivot tables on the Education Funding Agency’s (EFA) Information Exchange, at the following folder location: Revenue Funding > AY 2015-16. The purpose of the release is to update LAs’ overview of provision. It should be noted that the data provided is not real time/live data as we do not collect this.
This release includes full year (R14) FE data which has been collected about delivery in the 2015 to 2016 academic year for EFA funded provision. We have incorporated changes which have taken place since the June 2016 release. These include:
As part of the June 2016 release, we added data on the English and maths condition of funding which was applicable from the academic year 2014 to 2015. This is also included for the December 2016 release. Each LA will receive:
To accompany this release (in addition to the User Guide) there is a demonstration to help LAs make best use of the data provided in the pivot tables.
Contact form https://form.education...
For local authorities, schools, colleges and other (non-academy) providers contacting the Education Funding Agency.
Published: 30 June 2014
Updated: 22 December 2016
From: Education Funding Agency
Part of: Further education and training


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(Mill«)
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Great
Inagua:
on
coppice-covered
rocky
hill
north
of
Matthew
Town,
Shrub
forming
a
ball,
about
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tall.
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2,
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BOTANICAL
GARDEN
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Herbarium
FAIRCHILD
TROPICAL
GARDEN
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Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


First of all, you should build and run the sample program shown below. This is a typical usage of TJpgDec module and it helps to narrow down the problem on debugging.
The decompression session is divided in two stages. The first stage is to analyze the JPEG image and the second stage is to decompress it.
/*------------------------------------------------*/ /* TJpgDec Quick Evaluation Program for PCs */ /*------------------------------------------------*/ #include <stdio.h> #include <string.h> #include "tjpgd.h" /* User defined device identifier */ typedef struct { FILE *fp; /* File pointer for input function */ uint8_t *fbuf; /* Pointer to the frame buffer for output function */ unsigned int wfbuf; /* Width of the frame buffer [pix] */ } IODEV; /*------------------------------*/ /* User defined input funciton */ /*------------------------------*/ unsigned int in_func ( /* Returns number of bytes read (zero on error) */ JDEC* jd, /* Decompression object */ uint8_t* buff, /* Pointer to the read buffer (null to remove data) */ unsigned int nbyte /* Number of bytes to read/remove */ ) { IODEV *dev = (IODEV*)jd->device; /* Device identifier for the session (5th argument of jd_prepare function) */ if (buff) { /* Raad data from imput stream */ return (unsigned int)fread(buff, 1, nbyte, dev->fp); } else { /* Remove data from input stream */ return fseek(dev->fp, nbyte, SEEK_CUR) ? 0 : nbyte; } } /*------------------------------*/ /* User defined output funciton */ /*------------------------------*/ int out_func ( /* 1:Ok, 0:Aborted */ JDEC* jd, /* Decompression object */ void* bitmap, /* Bitmap data to be output */ JRECT* rect /* Rectangular region of output image */ ) { IODEV *dev = (IODEV*)jd->device; uint8_t *src, *dst; uint16_t y, bws, bwd; /* Put progress indicator */ if (rect->left == 0) { printf("\r%lu%%", (rect->top << jd->scale) * 100UL / jd->height); } /* Copy the decompressed RGB rectanglar to the frame buffer (assuming RGB888 cfg) */ src = (uint8_t*)bitmap; dst = dev->fbuf + 3 * (rect->top * dev->wfbuf + rect->left); /* Left-top of destination rectangular */ bws = 3 * (rect->right - rect->left + 1); /* Width of source rectangular [byte] */ bwd = 3 * dev->wfbuf; /* Width of frame buffer [byte] */ for (y = rect->top; y <= rect->bottom; y++) { memcpy(dst, src, bws); /* Copy a line */ src += bws; dst += bwd; /* Next line */ } return 1; /* Continue to decompress */ } /*------------------------------*/ /* Program Main */ /*------------------------------*/ int main (int argc, char* argv[]) { JRESULT res; /* Result code of TJpgDec API */ JDEC jdec; /* Decompression object */ void *work = (void*)malloc(3100); /* Pointer to the work area */ IODEV devid; /* User defined device identifier */ /* Initialize input stream */ if (argc < 2) return -1; devid.fp = fopen(argv[1], "rb"); if (!devid.fp) return -1; /* Prepare to decompress */ res = jd_prepare(&jdec, in_func, work, 3100, &devid); if (res == JDR_OK) { /* It is ready to dcompress and image info is available here */ printf("Image size is %u x %u.\n%u bytes of work ares is used.\n", jdec.width, jdec.height, 3100 - jdec.sz_pool); /* Initialize output device */ devid.fbuf = (uint8_t*)malloc(3 * jdec.width * jdec.height); /* Create frame buffer for output image (assuming RGB888 cfg) */ devid.wfbuf = jdec.width; res = jd_decomp(&jdec, out_func, 0); /* Start to decompress with 1/1 scaling */ if (res == JDR_OK) { /* Decompression succeeded. You have the decompressed image in the frame buffer here. */ printf("\rDecompression succeeded.\n"); } else { printf("Failed to decompress. (rc=%d)\n", res); } free(devid.fbuf); /* Discard frame buffer */ } else { printf("Failed to prepare. (rc=%d)\n", res); } free(work); /* Discard work area */ fclose(devid.fp); /* Close the JPEG file */ return res; }
These are the memory usage of some platforms at default configuration. Each compilations are optimized in code size.
| AVR | PIC24 | CM0 | IA-32 | |
|---|---|---|---|---|
| Compiler | GCC | C30 | GCC | VC6 |
| text+const | 9422 | 6544 | 4536 | 6144 |
TJpgDec requires a work area upto 3100 bytes for most JPEG images. It exactly depends on what parameter has been used to create the JPEG image. The 3100 bytes is the maximum memory requirement at default input buffer configuration (JD_SZBUF == 512) and it varies with JD_SZBUF. The JD_SZBUF defines how many bytes read from input stream at a time. TJpgDec alignes each read request to the buffer size, so that 512, 1024, 2048... byte is ideal to read data from the storage device.
This is a copy of the TJpgDec license document that included in the source codes.
/*----------------------------------------------------------------------------/ / TJpgDec - Tiny JPEG Decompressor R0.xx (C)ChaN, 20xx /-----------------------------------------------------------------------------/ / The TJpgDec is a generic JPEG decompressor module for tiny embedded systems. / This is a free software that opened for education, research and commercial / developments under license policy of following terms. / / Copyright (C) 20xx, ChaN, all right reserved. / / * The TJpgDec module is a free software and there is NO WARRANTY. / * No restriction on use. You can use, modify and redistribute it for / personal, non-profit or commercial products UNDER YOUR RESPONSIBILITY. / * Redistributions of source code must retain the above copyright notice. / /----------------------------------------------------------------------------*/
Therefore TJpgDec license is one of the BSD-style license but there is a significant difference. Because TJpgDec is for embedded projects, the conditions for redistributions in binary form, such as embedded code, hex file and binary library, are not specified to increase its usability. The documentation of the distributions need not include about TJpgDec and its license document, and it may also. Of course TJpgDec is compatible with the projects under GNU GPL. When redistribute it with any modification, the license can also be changed to GNU GPL or BSD-style license.


--- title: Mirobot UI author: Ben Pirt contact<EMAIL_ADDRESS>layout: app stylesheets: - mirobot-ui/main.css description: This is the default app used to program Mirobot manifest: /assets/apps/mirobot-ui/mirobot-ui.manifest ---
{% javascript mirobot-ui/app %}


UK Athletics CEO resigns before starting job
LONDON (AP) - The incoming CEO of Britain’s governing body for track and field has resigned before starting work amid questions over her husband’s conduct.
UK Athletics chairman Chris Cook says in a statement that he met with new CEO Zara Hyde Peters on Sunday and “we have agreed together that she will now not be taking up her position.”
Hyde Peters had been due to start Dec. 1.
The Times newspaper reported that Hyde Peters’ husband had been banned from working as a school teacher but later coached athletes at a club where his wife was an official.
A British teaching regulatory panel ruled in 2012 that Mike Peters had exchanged “inappropriate photographs” with a 15-year-old girl, amounting to “unacceptable professional conduct.” He was cleared of sexual misconduct.
More AP sports: https://apnews.com/apf-sports and https://twitter.com/AP_Sports
Sign up for Daily Newsletters
Copyright © 2019 The Washington Times, LLC.
Please read our comment policy before commenting.


PUL GitHub Issues
2023-06-13
#80 Evaluate Options for Replacing All/Bento Search
- Creator:
- Kevin Reiss
- Created:
- 2023-05-01 14:57:00
- Status:
- Open
#761 DataSpace collections for academic departments and senior theses are sometimes ambiguous
- Creator:
- James R. Griffin III
- Created:
- 2023-06-13 16:24:02
- Status:
- Open
- Events:
-
-
assigned
by James R. Griffin III at 2023-06-13 16:24:02.
-
labeled
by James R. Griffin III at 2023-06-13 16:24:18.
#762 DataSpace downloads consistently set the filename to "download" for unpublished Items
- Creator:
- James R. Griffin III
- Created:
- 2023-06-13 18:04:08
- Status:
- Open
- Events:
-
-
assigned
by James R. Griffin III at 2023-06-13 18:04:08.
#11 Add search box for sale field
- Creator:
- rladdusaw
- Created:
- 2023-06-13 13:43:02
- Status:
- Open
#12 Remove notes field from results table
- Creator:
- rladdusaw
- Created:
- 2023-06-13 13:44:03
- Status:
- Open
#13 Make search results deep-linkable
- Creator:
- rladdusaw
- Created:
- 2023-06-13 13:49:06
- Status:
- Open
#14 Accessibility audit
- Creator:
- rladdusaw
- Created:
- 2023-06-13 14:37:30
- Status:
- Open
#1263 Curator questions/corrections in pdc-staging
- Creator:
- Tyler Wade
- Created:
- 2023-06-09 21:45:50
- Status:
- Closed
(pull request)
- Events:
-
-
referenced
by Bess Sadler at 2023-06-13 18:28:16.
-
merged
by Bess Sadler at 2023-06-13 18:28:17.
-
closed
by Bess Sadler at 2023-06-13 18:28:17.
-
head_ref_deleted
by Bess Sadler at 2023-06-13 18:28:18.
#1242 Bump vite from 3.2.6 to 3.2.7
- Creator:
- dependabot[bot]
- Created:
- 2023-06-06 03:32:48
- Status:
- Open
(pull request)
#3978 Library-staging should be connected to mailcatcher, and not lib-ponyexpress
- Creator:
- Jane Sandberg
- Created:
- 2023-06-13 19:28:06
- Status:
- Open
#2011 Bump socket.io-parser from 4.2.2 to 4.2.4 in /sites/all/themes/pul_base
- Creator:
- dependabot[bot]
- Created:
- 2023-06-13 14:13:46
- Status:
- Open
(pull request)
- Events:
-
-
labeled
by None at 2023-06-13 14:13:47.
-
labeled
by None at 2023-06-13 14:13:47.
#2008 Bump socket.io-parser from 4.2.2 to 4.2.3 in /sites/all/themes/pul_base
- Creator:
- dependabot[bot]
- Created:
- 2023-05-24 01:58:43
- Status:
- Closed
(pull request)
- Comments:
- Events:
-
-
closed
by None at 2023-06-13 14:13:50.
-
head_ref_deleted
by None at 2023-06-13 14:13:52.


|
ArkGameFrame
v0.1.0
ArkGameFraime is a lightweight, fast, scalable, distributed module and plugin framework to create a game server easily. Greatly inspired by OGRE and Bigworld.
|
Go to the source code of this file.
Classes | |
| class | NFCDataList |
| List of nfc data. More... | |


Evelus
on 2012-07-30 01:28:29
Fantastic, thanks! Been trying to figure out the best way to slice clientside.
????? ????? ???
on 2012-04-18 10:18:01
I agree it is a very informative article and I actually enjoy reading good stuff unlike all the crap out there on the internet


NGC weekend attendance capped to ensure ultimate fan experience
by Lynn Butler - Sport24Sun City - The Nedbank Golf Challenge at the Gary Player Country Club is not about the amount of people that flock to Sun City, it's about creating the best fan experience, according to tournament director Ken Payet.
The fan experience at this year's tournament is exceptional with various activities, a wide arrange of entertainment and dining options over and above the top-class golf on offer.
Last year, "Africa's Major" broke all previous attendance records with 72 000 fans attending thanks to the major drawcard of Rory McIlroy and Sergio Garcia.
Payet, who has a been the tournament director for the past two years, revealed that they have decided to cap the weekend to allow only 20 000 people in per day to ensure an incredible fan experience.
"For us it's not about the amount of people, it's about the experience," Payet told Sport24 in an exclusive interview on Wednesday.
"So we've actually capped on a Saturday and Sunday to 20 000 because if we go over that mark then that detracts from the whole fan experience that we're trying to create.
"We making sure than year-on-year, we improve. Next year it's our 40th anniversary and we need to make sure we're better than this year," he said.
The winner of this year's Nedbank Golf Challenge will take home $2.5 million - an increase on the $1.25 million won by Lee Westwood last year.
Englishman Tommy Fleetwood is the highest ranked golfer in the 63-man field with a ranking of 18th.
Payet admitted that although they were hoping for a more star-studded line-up, he was quite content with the field.
"We always try and get the superstars, your marquee players like your Rory's and Dustin Johnson. However, in reality some Americans are reluctant to travel so far to South Africa and it's their off season," said Payet.
"We were hoping the $2.5 million first prize cheque would entice those players but we're not disappointed in our field. I know this is a world class field."
There are nine South Africans in the field, with the action scheduled to get underway on Thursday from 09:00.


THE KING IS ALIVE A film review by David N. Butterworth Copyright 2001 David N. Butterworth
*** (out of ****)
Stranded in Africa's equivalent of the Australian outback, a busload of tourists decides to stage an impromptu performance of Shakespeare's "King Lear."
Now perhaps group therapy through artistic expression wouldn't be the first order of business for you or I under these circumstances, and indeed there are some passengers who question the wisdom of all this, but then again we're not appearing in a movie by Danish director Kristian Levring, and don't have three hand-held cameras constantly thrust in our faces, Dogme 95-style.
"The King is Alive" is the latest offering from the Danish movement pioneered by the likes of "Dancer in the Dark"'s Lars Von Trier, a movement which strips "modern day" filmmaking of what it considers to be trippy conveniences--tripods, lighting, non-source music, and directorial credits, resulting in a pure and "natural" film experience.
If anything, the Dogme 95 style works especially well in "The King is Alive," since the drama is played out amid the rough-lit dunes and abandoned mining shacks of an arid North African landscape, where grainy, gritty camerawork heightens the experiences of our marooned protagonists. And indeed the play's the thing, with Levering and his international cast, among them Jennifer Jason Leigh, Bruce Davison, Janet McTeer, and Romane Bohringer, making the production entirely believable given the available options (how quickly would *you* feel left out if someone else got to play Cordelia?).
Where the film breaks down, however, is in its characterizations. Not one of these people is anyone you would want to spend time with, let alone perform alongside. They're whiney and unpleasant, mean and hostile, and this makes their ultimate fate--and that of the film--meaningless, since we care very little about what happens to them.
The cast gives it their all, and it's fascinating seeing how quickly the sexual power struggles come to a head (and, especially, how quickly Levring manages to avoid pretentiousness), but in the end "The King is Alive" more closely approximates another of Shakepeare's works, at least in name: "Much Ado About Nothing."
-- David N. Butterworth<EMAIL_ADDRESS>Got beef? Visit "La Movie Boeuf" online at http://members.dca.net/dnb
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Kylie Jenner sells a majority stake in her cosmetics company for $600 million
- Advertisement -
Reality star, model and entrepreneur Kylie Jenner has just sold a majority stake in her cosmetics company to CoverGirl owner Coty for $600 million.
Her sisters Kim, Kourtney, Khloe and Kendall have posted on social multiple times in the 24 hours since then.
None of them mentioned about Kylie’s business deal.
Khloe Kardashian took it to Instagram to celebrate the ‘OG trio’ which is herself, Kourtney and Kim in a frangrance promo.
- Advertisement -
The Internet was abuzz after 22-year-old Kylie Jenner sold a majority stake in her cosmetics company.
Her own family did not seem to be interested in the world’s youngest ever self-made billionaire.
Checking through the Kardashian-Jenner’s social media accounts in the past 24 hours, you may think that her sisters Kim, Khloe, Kourtney and Kendall are seething about her achievement.
As Kylie’s mum and manager, Kris Jenner may have something to say on the subject but not one of her siblings had any comment.
35-year-old Khloe Kardashian celebrated the ‘OG trio’ which is the original Keeping Up With The Kardashians stars, herself and sisters Kourtney and Kim.
She uploaded a post that promotes the trio’s new KKW fragrance.
Khloe also uploaded a photo of her beautiful home with no mention about Kylie’s achievement.
It was surprising because for fans of Keeping Up With The Kardashians, she is the closest family member to Kylie.
Kris noted that it was a moment for our family to be proud but other than that, the rest of the Kardashian-Jenner clan did not acknowledge the huge payday.
As for Kim, she was plugging her Skims range, her Rodney Reed interview with Jenna Bush as well as her KKW Beauty line and fragrances.
The 39-year-old reality star congratulated Khloe’s bestie Malika Haqq and her sister on their new show as well as celebrating her own makeup artist and collaborator Mario’s influencer award.
Kim also professed her love for husband Kanye West and daughter Chicago.
Four years ago, before Kylie launched her $29 lipkits, Kim was the most successful reality star in history making millions in endorsement deals.
Kim’s estimated $370 million personal net worth is now beaten by her younger sister’s recent achievement.
Kylie cited Kim as her biggest inspiration and while Kim is proud of what her sister has done, Kylie’s achievement may be grating on the mother-of-four.
Kim worked for more than two decades to reach her level of success while Kylie launched her lipskits with just an Instagram post four years ago.
Kourtney Kardashian plugged her KKW beauty fragrance and Poosh website via Instagram stories in the past 24 hours while Kendall Jenner posted an ad for her Proativ range.
The sisters didn’t find time to thank their baby sister and instead promoted their own products.
64-year-old Kris Jenner said that it was a big day for daughter Kylie and that it was a moment for the family to be proud.
It was a ‘crystallization of all our work’, she added.
51-percent of Kylie’s makeup and skincare businesses were sold to beauty company Coty which owns around 77 brands including CoverGirl, Hugo Boss, Burberry, Rimmel and Max Factor – in exchange for the lump sum.
Kylie said that she is excited to partner with Coty to reach to more fans of Kylie Cosmetics and Kylie Skin around the world.
She is also looking forward to continue the creativity and ingenuity for each collection.
The deal isn’t expected to close until the third quarter of the fiscal year 2020 but shares in Coty have shot up by 5 per cent.
- Advertisement -


Career Objective
Self-motivated person believes in growth and very open to new ideas. I am looking for the place where my skills and expertise is being fully utilized and proved to be an asset to the company. I am always fascinated towards continuous learning process
and capable of working in a team,
Educational Qualifications
| Qualification |
Board |
Percentage / CGPA |
Year |
| B.Tech(Computer Science & Engineering |
Vivekananda Global University |
9.23 CGPA |
2020* |
| H.S.C (Science Stream) |
CBSE |
75.40% |
2016 |
| S.S.C. |
CBSE |
7.4 CGPA |
2014 |
Independent Courses
-
Machine Learning – Adhoc Networks, Jaipur
-
Core Java - CSDIT Solutions, Patna
-
Web Development - CSDIT Solutions
Volunteer Experience:
- President of CSI Student Branch VGU.
- Coordinator in Panache10, College cultural Fest.
- Coordinator in Panache9, College cultural Fest
Achievements and Awards:
- Secured first rank in Branch in 1st Semester
Strengths:
- A high tolerance of stress and enjoys responsibilities
- Quick learner with good grasping ability
- Action-oriented and result-focused
- Lead & work as a team in an organized way
Personal Information:
-
A young, determined hard and smart working person. I believe in task based roles and complete ownership of work.
-
Languages Known:English, Hindi
-
Father's Name:Mohd. Abdul Ayyub
Declaration
I hereby declare that the details furnished above are true and correct to the best of my knowledge and belief.
Nisar Ahmed


Load profiles¶
CLOVER has the functionality to build load profiles from the bottom-up, summarised in the following steps:
- Input the devices or appliances available in the community
- Input the usage profile of each device throughout the day and year
- Calculate the number of devices in use throughout the lifetime of the system
- Calculate the daily utilisation profile of each device
- Calculate the number of devices in use in every hour
- Calculate the load profile of each device
- Calculate the total load profile of the community.
This process is performed by the Load module, described in this section. The terms device and appliance are used interchangeably, meaning any piece of equipment that uses electricity, and specific meanings of other similar terms (for example usage and utilisation) will be made explicit where relevant.
Preparation¶
Input the devices in the community¶
CLOVER allows the user to include as many devices as desired in their
load profile. These are input using the Devices
input CSV in the
Load folder for the given location, which can be edited directly.
Let’s look at the devices included for Bahraich:
import pandas as pd
devices = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Devices.csv")
devices.head(len(devices))
| Device | Available | Power | Initial | Final | Innovation | Imitation | Type | |
|---|---|---|---|---|---|---|---|---|
| 0 | light | Y | 3 | 2.00 | 4.00 | 0.04 | 0.50 | Domestic |
| 1 | phone | Y | 5 | 2.20 | 3.00 | 0.02 | 0.20 | Domestic |
| 2 | radio | Y | 10 | 0.28 | 0.35 | 0.01 | 0.20 | Domestic |
| 3 | tv | Y | 20 | 0.08 | 0.90 | 0.03 | 0.25 | Domestic |
| 4 | laptop | Y | 40 | 0.01 | 0.50 | 0.02 | 0.10 | Domestic |
| 5 | fridge | Y | 50 | 0.00 | 0.50 | 0.02 | 0.20 | Domestic |
| 6 | fan | Y | 10 | 0.10 | 2.00 | 0.04 | 0.30 | Domestic |
| 7 | kerosene | Y | 1 | 3.40 | 2.00 | 0.02 | 0.10 | Domestic |
| 8 | mill | Y | 750 | 0.01 | 0.10 | 0.02 | 0.20 | Commercial |
| 9 | workshop | Y | 350 | 0.05 | 0.05 | 0.02 | 0.20 | Commercial |
| 10 | SME | Y | 200 | 0.05 | 0.03 | 0.25 | 0.25 | Commercial |
| 11 | streetlight | Y | 25 | 0.20 | 0.20 | 0.00 | 0.00 | Public |
This CSV contains many variables, some of which are more obvious than others, summarised in the table below:
| Variable | Explanation |
|---|---|
Device |
Unique name of the device |
Available |
Device is included (Y ) or not
(N ) in the community load |
Power |
Device power consumption (W) |
Initial |
Average ownership of the device per household at the start of the time period |
Final |
Average ownership of the device per household at the end of the time period |
Innovation |
Parameter governing new households acquiring device |
Imitation |
Parameter governing households copying others |
Type |
Classification of the device as a
Domestic , Commercial or
Public device |
Take the example of the device light
, which represents an LED bulb.
It is available in the load profile (Available = Y
), has a power
rating of 3 W, and classified as a Domestic
load. At the start of
the simulation period there is an average two LED bulbs per household
(Initial = 2.00
) which, over time, increases to four bulbs per
household (Final = 4.00
) by the end of the considered time period -
which we defined to be to 20 years in the General Setup section.
The two remaining variables describe how quickly the average ownership
per household increases: to generalise, Innovation
describes how
likely a household is to get a new appliance based on how much they like
new things and Imitation
describes how much a household is
influenced by others already having the device. These are inputs into a
model of how quickly devices diffuse throughout the community (described
in more detail later) but, simply put, the larger these numbers the
quicker households will acquire them. These should be treated almost as
qualitative measures: the values for a more desirable appliance like a
television should be higher than (for example) a radio. You can use
later outputs from the Load module to check that your appliance
diffusion seems viable.
If you do not want to include any demand growth over time by keeping the
number of appliances the same throughout the simulation, it is possible
to turn off this feature simply by setting the values for Initial
and Final
to be the same, which will negate the Innovation
and
Imitation
parameters (for example streetlight
does this). Bear
in mind that an increase in the number of households, defined when
establishing the location, will result in an increase in the number of
devices as the latter is calculated on the basis of the number of
devices per household.
One of the devices, kerosene
, is different from the others and is
the only device which must remain present in the Devices file.
CLOVER has the functionality to account for the usage of backup
non-electric lighting devices, such as kerosene lamps, which are used
during periods when electricity is unavailable. This is useful when
investigating electricity systems with less than 100% reliability, for
example. This device is therefore necessary as an input for later
functions and must be present here, and have corresponding utilisation
profiles, described later. If backup sources of non-electric lighting
are not relevant to your investigation, set Initial = 0
and
Final = 0
in the Devices file to not consider it whilst still
allowing the other functions to operate as expected. If a different
non-electric lighting source is relevant, such as candles, complete the
input data for that source but the name must remain as kerosene
in
the Devices file.
With this in mind, complete the Devices
input CSV for your
investigation.
Input the device utilisation profiles¶
CLOVER first considers the service that appliances provide as a necessary step in understanding the electricity demand of the community, rather than jumping directly to the latter. This is because two devices may provide very similar services, and the times of using those devices may be very similar, but the electricity requirements could be very different: LED and incandescent light bulbs, for example. By considering the demand for the service as a first step it is possible to more easily consider issues such as the usage of efficient, low-power devices which are becoming more common.
The utilisation of a device is defined to be the probability that a device is being used, given that it is present in the community. Utilisation values can vary hourly (throughout the day) and monthly (throughout the year) and must be between 0 (the device is never used in a specific hour) to 1 (it is always used). Utilisation profiles for each device are found in the Device utilisation folder in the Load folder.
Every device listed in the Devices
input CSV must have a
utilisation profile associated with it for CLOVER to calculate the
load demand correctly and be named [device]_times
. Even if a device
has Available = N
in the Devices input CSV, CLOVER will still use
the utilisation profile but not eventually include the load in the final
total community demand. If you do not want to include a device at all it
is much easier to delete its entry from the Devices input CSV.
Each utilisation profile is a 24 x 12 matrix of utilisation values,
corresponding to the hour of the day for each month of the year. Let’s
take a look at the example of light
:
light_utilisation = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Device utilisation/light_times.csv",header=None)
print(light_utilisation)
0 1 2 3 4 5 6 7 8 9 10 11
0 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39
1 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39
2 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39
3 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39
4 0.39 0.39 0.39 0.39 0.48 0.56 0.46 0.39 0.39 0.39 0.39 0.39
5 0.39 0.39 0.47 0.48 0.23 0.12 0.28 0.45 0.53 0.57 0.40 0.39
6 0.58 0.48 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.05 0.37 0.53
7 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
8 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
9 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
16 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
17 0.47 0.08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.39 0.74 0.76
18 0.93 0.93 0.54 0.51 0.23 0.03 0.00 0.26 0.79 0.93 0.93 0.93
19 0.93 0.93 0.93 0.93 0.93 0.93 0.90 0.93 0.93 0.93 0.93 0.93
20 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93
21 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93 0.93
22 0.88 0.88 0.88 0.88 0.88 0.88 0.88 0.88 0.88 0.88 0.88 0.88
23 0.83 0.83 0.83 0.83 0.83 0.83 0.83 0.83 0.83 0.83 0.83 0.83
This device, representing an LED bulb from before, has a changing utilisation profile throughout the day: it is never used during the middle of the day (utilisation is 0.00), is very likely to be used in the evenings (up to 0.93), and some lights in the community are likely to be left on overnight (0.39). The utilisation of this device also changes throughout the year: in January (month 0) the utilisation at 18:00 is 0.93, but is 0.00 in July (month 6), owing to the changing times of sunset.
Making a representative utilisation profile will depend significantly on the specifics of your own investigation. These could come from primary data collection (indeed, the utilisation profile shown above did) or from your best estimate of what the demand for service is likely to be. Bear in mind that the probability that a device being used is an average over the entire community, so this should represent the utilisation of an “average” household without considering inter-household variations. To model device utilisation as the same throughout the year, use the same 24-value column for each of the 12 months.
For every device you have listed in the Devices
input CSV,
complete a corresponding utilisation profile matrix and ensure that is
is called [device]_times
.
Building load profiles¶
Calculating the number of devices in the community¶
The next step is to know how many devices there are in the community at
any given time which, when combined with the utilisation profiles, will
then allow us to calculate how many are in use. This step is relatively
straightforward in that it takes information we have already input (into
the Devices
CSV file) and calculates everything for us. It also
accounts for the growing number of devices in the community, if we chose
to use that.
To calculate this automatically for all of the devices listed, run the function
Load().number_of_devices_daily()
in the console. This will take every device listed and calculate the
number in the community on every day of our 20 year investigation
period, and save them as a CSV file in the Device ownership folder in
the Load folder with title format of [device]_daily_ownership.csv
.
Let’s take a look at the light
device again and look at the first
and final number of devices in the community:
light_ownership = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Device ownership/light_daily_ownership.csv")
initial_light_ownership = int(light_ownership.iloc[0][1])
final_light_ownership = int(light_ownership.iloc[-1][1])
print('Initial light ownership = '+ str(initial_light_ownership))
print('Final light ownership = ' + str(final_light_ownership))
Initial light ownership = 200
Final light ownership = 487
The final light
ownership perhaps looks higher than expected, but
when we take into account how much the community has grown it makes
sense:
The slight discrepancy in the two values likely comes from the diffusion model tending towards (but never quite reaching) the final value of average ownership and/or rounding errors.
Calculating the daily utilisation profiles¶
The utilisation profiles input for each device was defined by month but, if we assigned that utilisation profile for the whole month-long period, there would be a sharp transition between each month which would be unrealistic. To overcome this CLOVER interpolates between the monthly values to give a smooth transition between every day, meaning that there are no harsh boundaries where demand suddenly changes. This process is also performed automatically by CLOVER. Run the following function in the console to calculate this:
Load().get_device_daily_profile()
This function takes the (monthly) utilisation inputs and converts them
to a daily utilisation input of size 365 x 24 and saves it in the
Device utilisation folder in the Load folder using the title format
[device]_daily_times.csv
. CLOVER assumes that the values stated in
the monthly utilisation profile apply to the middle day of each month
when interpolating to the daily scale.
As an example, let’s compare the monthly input values for January and
February against the first week of daily values for the light
device:
jan_feb_inputs = light_utilisation[light_utilisation.columns[0:2]]
jan_feb_inputs.columns = ['Jan','Feb']
print('Input values for January and February:\n')
print(jan_feb_inputs)
light_daily_utilisation = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Device utilisation/light_daily_times.csv",index_col=0)
light_daily_utilisation = round(light_daily_utilisation.iloc[0:7],3)
print('\nDaily varying values: \n')
print(light_daily_utilisation.T)
Input values for January and February:
Jan Feb
0 0.39 0.39
1 0.39 0.39
2 0.39 0.39
3 0.39 0.39
4 0.39 0.39
5 0.39 0.39
6 0.58 0.48
7 0.00 0.00
8 0.00 0.00
9 0.00 0.00
10 0.00 0.00
11 0.00 0.00
12 0.00 0.00
13 0.00 0.00
14 0.00 0.00
15 0.00 0.00
16 0.00 0.00
17 0.47 0.08
18 0.93 0.93
19 0.93 0.93
20 0.93 0.93
21 0.93 0.93
22 0.88 0.88
23 0.83 0.83
Daily varying values:
0 1 2 3 4 5 6
0 0.390 0.390 0.390 0.390 0.390 0.390 0.390
1 0.390 0.390 0.390 0.390 0.390 0.390 0.390
2 0.390 0.390 0.390 0.390 0.390 0.390 0.390
3 0.390 0.390 0.390 0.390 0.390 0.390 0.390
4 0.390 0.390 0.390 0.390 0.390 0.390 0.390
5 0.390 0.390 0.390 0.390 0.390 0.390 0.390
6 0.555 0.557 0.559 0.560 0.562 0.564 0.566
7 0.000 0.000 0.000 0.000 0.000 0.000 0.000
8 0.000 0.000 0.000 0.000 0.000 0.000 0.000
9 0.000 0.000 0.000 0.000 0.000 0.000 0.000
10 0.000 0.000 0.000 0.000 0.000 0.000 0.000
11 0.000 0.000 0.000 0.000 0.000 0.000 0.000
12 0.000 0.000 0.000 0.000 0.000 0.000 0.000
13 0.000 0.000 0.000 0.000 0.000 0.000 0.000
14 0.000 0.000 0.000 0.000 0.000 0.000 0.000
15 0.000 0.000 0.000 0.000 0.000 0.000 0.000
16 0.000 0.000 0.000 0.000 0.000 0.000 0.000
17 0.615 0.605 0.594 0.584 0.574 0.563 0.553
18 0.930 0.930 0.930 0.930 0.930 0.930 0.930
19 0.930 0.930 0.930 0.930 0.930 0.930 0.930
20 0.930 0.930 0.930 0.930 0.930 0.930 0.930
21 0.930 0.930 0.930 0.930 0.930 0.930 0.930
22 0.880 0.880 0.880 0.880 0.880 0.880 0.880
23 0.830 0.830 0.830 0.830 0.830 0.830 0.830
Note that the daily utilisation CSV file has a slightly different structure (days are presented as rows) but we have transposed it here and rounded to three decimal places for comparability and readability. The hours where there is a difference between utilisation in January and February (hours 6 and 17) also vary in the daily profile, whilst the others remain the same as expected. As mentioned above, note that the utilisation input for January is not the same as the daily utilisation on day 0: the former is assumed to be for the middle day of the month in January, whereas the latter is halfway between the inputs for December and January. We can check this:
december_utilisation_example = light_utilisation[light_utilisation.columns[11]][6]
january_utilisation_example = light_utilisation[light_utilisation.columns[0]][6]
midpoint = round((december_utilisation_example + january_utilisation_example) / 2.0,3)
print('December utilisation at 6:00: ' + str(december_utilisation_example))
print('January utilisation at 6:00: ' + str(january_utilisation_example))
print('Midpoint utilisation between December and January: ' + str(midpoint))
print('Day 0 utilisation at 6:00: ' + str(light_daily_utilisation.iloc[0][6]))
December utilisation at 6:00: 0.53
January utilisation at 6:00: 0.58
Midpoint utilisation between December and January: 0.555
Day 0 utilisation at 6:00: 0.555
As expected, the two values match.
Calculating the number of devices in use¶
Now that we have both the number of devices in the community on a given day, and the daily utilisation profile of each device, we can calculate the number of devices that are in use at any given time. CLOVER does this automatically for each type of device by using a binomial random number generator: the number of trials is the number of devices, and the probability is the utilisation value for that hour. To do this, run the following function in the console:
Load().devices_in_use_hourly()
This function will take a while to complete as it runs through each type
of device and randomly assigns the number in use over the full 20 year
period, and needs to be performed once only. The outputs are saved as
CSV files in the Devices in use folder in the Load folder, using the
title format [device]_in_use.csv
, so that they can be used as
consistent inputs when used by CLOVER. Note that rerunning this function
will create a new profile which will differ every time because of the
random statistics used to generate it: if you need to rerun this
function but want to keep your previous files, save a copy of them
elsewhere otherwise they will be overwritten.
Let’s consider the light
device over the first three days of its
usage:
import matplotlib.pyplot as plt
import matplotlib as mpl
light_in_use = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Devices in use/light_in_use.csv",index_col=0)
light_in_use = light_in_use[0:72]
plt.plot(range(72),light_in_use,label='Light')
plt.legend(loc='upper left')
plt.xticks(range(0,73,4))
plt.yticks(range(0,251,50))
plt.xlabel('Hour of simulation period')
plt.ylabel('Devices in use')
plt.title('Number of devices in use')
plt.show()
The number of light
devices in use in a given hour changes
throughout the day: as expected from the utilisation profile, some are
in use overnight, none are in use during the day, and most are in use in
the evenings. Comparing between days, the number of devices in use in a
certain hour also varies.
Calculating the load profile of each device¶
Now that we know the number of each device in use at any given time, and the power rating of each from the Device input CSV, it is straightforward to get the load profile of each device. Run the following function in the terminal:
Load().device_load_hourly()
This function uses the [device]_in_use.csv
file and the power rating
to save a new CSV file in the Device Load folder in the Load folder
using the title format [device]_load.csv
.
Let’s now compare two devices, light
and tv
, to see how the
number in use and load demand vary over the first three days:
tv_in_use = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Devices in use/tv_in_use.csv",index_col=0)
tv_in_use = tv_in_use[0:72]
fig, ax = plt.subplots(1,2,figsize=(8,4))
ax[0].plot(range(72),light_in_use,label='Light')
ax[0].plot(range(72),tv_in_use,label='TV')
ax[0].legend(loc='upper left')
ax[0].set(xticks = (range(0,73,6)),yticks = range(0,251,50),
xlabel = 'Hour of simulation period',
ylabel = 'Devices in use',
title = 'Number of devices in use')
light_load = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Device load/light_load.csv",index_col=0)
light_load = light_load[0:72]
tv_load = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Device load/tv_load.csv",index_col=0)
tv_load = tv_load[0:72]
ax[1].plot(range(72),light_load,label='Light')
ax[1].plot(range(72),tv_load,label='TV')
ax[1].legend(loc='upper left')
ax[1].set(xticks = (range(0,73,6)),yticks = range(0,701,100),
xlabel = 'Hour of simulation period',
ylabel = 'Load (W)',
title = 'Load demand from each device')
plt.tight_layout()
plt.show()
Comparing the two devices, the usage of tv
devices is limited to the
evening periods only and very few are ever in use, owing to the low
average ownership. When we compare the load demanded by each device,
tv
has a more significant effect, albeit still relatively small, as
the relative power rating is higher than that of light
.
 Once again, CLOVER calculates this automatically when you run the following function in the console:
Load().total_load_hourly()
This function adds together all of the devices listed in the Device
input file that have Available = Y
and creates a new CSV in the
Device load folder in the Load folder called total_load.csv
.
This also uses another of the input parameters from before, Type
, to
split the load into three categories: Domestic
for households,
Commercial
for businesses and enterprises, and Public
for
community-level electricity uses.
With this, we now have the necessary load data to input into our simulations.
Troubleshooting¶
Most of the processes for generating load profile are automated but there are ample opportunities for simple mistakes when inputting the data which will cause errors. Solving the issues is normally simple but finding where they appear can be much harder, so if they come up:
- Check that you have used consistent spelling and capitalisation for your devices throughout as these are case sensitive, e.g.
radio
andRadio
will be treated as two completely different devices - Check that your file names correspond to the correct devices and are in the correct formats, e.g.
radio
has a utilisation profile namedradio_times
- Ensure that your input variables are in the correct format, for example
Type
is eitherDomestic
,Commercial
orPublic
- Ensure that your utilisation profiles are the correct size and format, and have the correct naming convention including the
.csv
suffix - Ensure that your device power is input in Watts (W), not kilowatts (kW)
- Ensure that you have completed each of the steps in the correct order
Extension and visualisation¶
Using your own load profile¶
CLOVER gives users the functionality to construct their own load profiles from the bottom up, but sometimes you already have a load profile which you want to use directly without trying to recreate it using the Load module. This is straightforward to do, but your own load profile must be in the same format as the one generated by the Load module. To do this:
- Ensure that your load profile is in the correct format: at an hourly
resolution for the duration of your simulation period, measured in
Watts (not kilowatts), and with the
Domestic
,Commercial
andPublic
headings - Name your profile
total_load.csv
and copy it into the Device load folder in the Load folder of your location - Run the function
Load().get_yearly_load_statistics('total_load.csv')
to get the yearly load statistics - Copy
kerosene_load.csv
into the same folder (the values can be changed to zero, or the outputs ignored later, as necessary)
If you do not have Domestic
, Commercial
and Public
loads, or
they are combined into one category, it is most straightforward to
include them all together in a single headed column (e.g. Domestic
).
The kerosene_load.csv
needs to be included for compatibility with
the later functionality, but the outputs relating to this can be ignored
or the values in that profile can be set to zero for completeness. The
Load().get_yearly_load_statistics('total_load.csv')
is used later in
the simulation process for sizing equipment (such as the inverters) so
must be updated from the default case study values provided.
Comparing domestic, commercial and public electricity demand¶
Let’s take a look at how the three demand types compare over the first three days of the simulation period:
import numpy as np
total_demand = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Device load/total_load.csv",index_col=0)
total_demand = total_demand[0:72]
plt.plot(range(72),total_demand['Domestic'],label='Domestic')
plt.plot(range(72),total_demand['Commercial'],label='Commercial')
plt.plot(range(72),total_demand['Public'],label='Public')
plt.plot(range(72),np.sum(total_demand,axis=1),label='Total')
plt.legend(loc='upper right')
plt.xticks(range(0,73,4))
plt.yticks(range(0,4501,500))
plt.xlabel('Hour of simulation period')
plt.ylabel('Power demand (W)')
plt.title('Load profile of the community')
plt.show()
This allows us to compare the different types of demands in the community and how they vary throughout the day:
- The
Domestic
demand is highest in the evening due to lighting and entertainment (such as TV) loads - The
Commercial
demand peaks in the day and has high variability caused by a smaller number of higher-power devices - The
Public
demand, composed here asstreetlight
only, has a consistent load profile as it is modelled to operate on a timed basis
Varying demand throughout the year¶
We can also see how these demands vary over the year by reformatting the data into daily demands. For visibility let’s look at a five-day rolling average, with the raw data plotted behind it:
total_demand = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Device load/total_load.csv",index_col=0)
total_demand = total_demand[0:8760]
domestic_demand = 0.001 * np.sum(np.reshape(total_demand['Domestic'].values,(365,24)),axis=1)
commercial_demand = 0.001 * np.sum(np.reshape(total_demand['Commercial'].values,(365,24)),axis=1)
public_demand = 0.001 * np.sum(np.reshape(total_demand['Public'].values,(365,24)),axis=1)
total_demand = 0.001 * np.sum(np.reshape(np.sum(total_demand,axis=1).values,(365,24)),axis=1)
fig, ax = plt.subplots(1,2,figsize=(8,4))
ax[0].plot(range(365),pd.DataFrame(domestic_demand).rolling(5).mean(),label='Domestic',color='blue')
ax[0].plot(range(365),pd.DataFrame(commercial_demand).rolling(5).mean(),label='Commercial',color='orange')
ax[0].plot(range(365),pd.DataFrame(public_demand).rolling(5).mean(),label='Public',color='green')
ax[0].plot(range(365),domestic_demand,alpha=0.5,color='blue')
ax[0].plot(range(365),commercial_demand,alpha=0.5,color='orange')
ax[0].plot(range(365),public_demand,alpha=0.5,color='green')
ax[0].legend(loc='best')
ax[0].set(xticks = (range(0,366,60)),yticks = range(0,26,5),
xlabel = 'Day of simulation period',
ylabel = 'Load (kWh per day)',
title = 'Energy demand of each load type')
ax[1].plot(range(365),pd.DataFrame(total_demand).rolling(5).mean(),label='Total',color='red')
ax[1].plot(range(365),total_demand,alpha=0.5,color='red')
ax[1].legend(loc='best')
ax[1].set(xticks = (range(0,366,60)),yticks = range(15,41,5),
xlabel = 'Day of simulation period',
ylabel = 'Load (kWh per day)',
title = 'Total community energy demand')
plt.tight_layout()
plt.show()
Note that the axes of the two subplots use the same scale but the axis
of the right plot, showing the total community demand, is shifted
upwards. Commercial
demand, as before, displays the largest amount
of variation both between days and over the course of the year, in this
case because of varying agricultural demand. The Domestic
demand has
relatively little day-to-day variation but there is a noticeable
decrease in the summer as lighting demand decreases. The growth in
Domestic
device ownership also results in the growth of the daily
load demand (comparing January and December), almost exceeding the
Commercial
demand. Finally the Public
demand remains the same
throughout the year, as expected.
The total community demand is shown on the left. Its structure is mostly
governed by the variation in the Commercial
demand, but the effect
of the Domestic
demand can be seen when comparing the upwards shift
in load comparing the start and end of this year-long profile.
Growing demand over the investigation period¶
We can see how load grows in the community across the investigation period, for example to replicate how appliance ownership might grow over time as a community develops economically. Let’s reformat the load data into yearly totals and compare them across the 20-year period:
total_demand = pd.read_csv("/Users/prs09/Documents/CLOVER/Locations/Bahraich/Load/Device load/total_load.csv",index_col=0)
domestic_demand = 0.000001 * np.sum(np.reshape(total_demand['Domestic'].values,(20,8760)),axis=1)
commercial_demand = 0.000001 * np.sum(np.reshape(total_demand['Commercial'].values,(20,8760)),axis=1)
public_demand = 0.000001 * np.sum(np.reshape(total_demand['Public'].values,(20,8760)),axis=1)
total_demand = 0.000001 * np.sum(np.reshape(np.sum(total_demand,axis=1).values,(20,8760)),axis=1)
plt.plot(range(20),domestic_demand,label='Domestic',color='blue')
plt.plot(range(20),commercial_demand,label='Commercial',color='orange')
plt.plot(range(20),public_demand,label='Public',color='green')
plt.plot(range(20),total_demand,label='Total',color='red')
plt.legend(loc='upper left')
plt.xticks(range(0,21,2))
plt.yticks(range(0,71,10))
plt.xlabel('Year of investigation period')
plt.ylabel('Energy demand (MWh per year)')
plt.title('Load growth of the community')
plt.show()
We can see here that the Domestic
and Commercial
loads both
increase over time, but the Domestic
increases much faster than
Commercial
and therefore is the greatest contributor to the total
load soon after the first year (as we saw in
earlier). The Public
demand meanwhile remains the same throughout.


Summary
I am a senior Android engineer with a decade of application development experience with a broad range of apps, including e-commerce, photo collage and camera app. I have solid understanding of mobile and software development cycles, and Agile methodologies. In addition, I mentor colleagues in my company. I am looking for new challenges, which I can apply these assets to continue my professional development.


--- title: Development type: dev ---
If you are interested in the evolution of wallaroo, you can have a look at the project roadmap.
Wallaroo is hosted by sourceforge.
If you want to browse the code or checkout the source you can go to the
repository.
If you have a problem to report or you would like new features you can use the
sourceforge ticket system.
On sourceforge you can also find the wiki, the forum and the blog.


Examples of track types include climbing sticks, where Pikmin go from the base to the top, or the vine slides in Pikmin 3
To create a new type of track, please follow the making object types tutorial.
Overview
A track object doesn't do much except for idling and waiting for leaders or Pikmin to draw near. It has information on how objects get transported around, which includes who can ride it, at what speed, how they pose while riding, and if they can stop riding by being whistled out of it.
When an object wants to ride a track, it goes to where the track's first body part is located. Then, it moves linearly to where the second body part is. If there is a third body part, it moves there afterwards, and so on. Objects move from one body part to the next at the specified speed, but this is in ratio per second. This means that if the value is 0.5, it takes two seconds to go from the first body part to the second, another two to go from that to the third, etc. Riders can be in mid-air whilst riding, and will fall to the floor if they cancel out of the ride.
Track objects are hardcoded to not do anything, but there is logic in the engine for when a Pikmin or leader gets close, to go to it and start riding, if applicable.
Properties
Besides the global object type properties, a track type has the following properties.
Mandatory
riders
: A list of what types of riders are allowed. This list is separated by space, and the possible values arepikmin
orleaders
.
Recommended
riding_pose
: What sort of animation the riders switch to when riding. Possible values arestopped
,sliding
,climbing
. Defaults to stopped.ride_speed
: The speed riders go from one body part to the next at. This is in ratio per second, so 0.5 means 50% of the way in one second. Defaults to 0.5.
Optional
cancellable_with_whistle
: Iftrue
, riders can stop riding if they are whistled by a leader. Defaults to false.
Animations
A track type needs to have the following animations:
idling
: Idling; used for everything.
Script
Track types have hardcoded scripts, so the only thing you can do is enhance them.
Some script variables control special behavior, like the track's starting team. To know which ones exist, you can go to the area editor, select a track, and read the tooltip of each variable.


|
{{data.part}}
min diff
max diff
|
True:{{element.y}}
Pred:{{element.y_pred}}
Diff: {{element.metric_diff}}
|
|---|


Is energy consumption a real issue in the software development process? Do developer really care about that?
These questions were the start point of our paper, “Mining Questions About Software Energy Consumption”. In this paper, we investigated several questions about software energy consumption. Since we believe that research needs to be grounded in practice, we analyzed StackOverflow, one of the most famus software development web site.
We filter out all questions that contain at least one energy consumption related word (e.g., energy efficiency). After this process, we found 615 question, but after removing false positives, we ended up with only 325 valid questions. We used a qualitative approach to analyze these questions, named Thematic Analysis.
Analyzing such questions, we observed that practitioners are aware of the energy consumption problems: the questions they ask are not only diverse – we found 5 main themes of questions – but also often more interesting and challenging when compared to the remaining questions on StackOverflow.
We found five main themes regarding energy consumption questions. They are:
- Measurements. Questions about measurement tools or techniques.
- General Knowledge. Questions that do not have a concrete use case.
- Code Design. Questions about programming techniques that can help in saving energy.
- Context-specific. The authors of such questions need to provide more details in order for other users to better understand the problem, and to facilitate replication
- Noise. These questions are not directly associated with an energy consumption issue. Usually, the user first wants to improve one aspect of her application and, as a secondary goal, also improve energy consumption
Since questions in the Code Design theme are usually focused on how programmer decisions may improve energy consumption, we believe that the Code Design category is the most important one for future energy-aware software development. This category is also the most popular among developers. In a in-depth analysis of this theme, we identified 8 solutions that developers use in order to save energy. They are:
- Keep IO to a minimum.
- Bulk operations.
- Avoid Polling.
- Hardware Coordination.
- Concurrent programming.
- Lazy Initialization.
- Race to Idle.
- Efficient Data structure.
We also observed that some reseachers support such solutions proposed by software developers. However, for some of them, like concurrent programming, solutions cannot be seen as one-size-fits-all, since no consensus has emerged from the relationship between concurrent programming, performance and energy consumption.
In conclusion, this study serves as a research agenda for future energy consumption research. The needs of developers and the challenges they face may help energy-efficiency researchers stay focused on the real-world problems. The collective wisdom shared by developers may serve as a practical guide for future energy- aware and energy-efficient software development. The conceptually incorrect views they hold may inspire educators to develop more state-of-the-art curricula.
For more details, please check out our paper.


KRAIG RYAN HAMIT
Republican
Deputy District Attorney with 21st Judicial District District Attorney's Office
I graduated from the University of Northern Colorado with a bachelors in political science and a minor in legal studies. I graduated from Creighton University School of Law with a JD and a masters in Government and Leadership. I am licensed to practice law in Colorado.
81505
I have a lot of experience in advocating for people and some experience in organizing and representing organization. In my time with the District Attorney's Office, I have had considerable experience advocating and speaking with people from all walks of life. While on the board of the Pro Bono Project we made strides in our representation and advocacy for survivors of domestic violence and sexual assault. The Grand Valley Ducks Unlimited chapter also gave me experience in organizing a decent-sized fundraiser and having to deal with the transition to a completely online event due top COVID restrictions that was a big success.
I have voted in almost all available elections. I was an intern in Representative Cory Gardner's (CO-4) DC office in the summer of 2012. I have donated to the following political campaigns: Pete Buttigieg, John Hickenlooper, and Jake Niece.
Mesa County Pro Bono Project - Board member Grand Valley Ducks Unlimited - Board member Heritage Heights Homeowners Association - President Colorado Bar Association - member
I would like to play a part in the redrawing of the congressional and legislative districts. I think it is my civic duty to contribute where I can, and I can here.
My job as a district attorney is to create agreement between people by presenting them with facts. My job also requires a fairness and impartiality for the effective and efficient administration of the justice system. My time on the board of the Pro Bono Project also helped me develop skills in promoting consensus among professional organizations that have diverse and sometimes competing interests in order to attain a common goal. With the Grand Valley Ducks Unlimited chapter I contributed by soliciting donations from various organizations and businesses and also took recommendations from various stakeholders in the community to the board for consideration.
As an attorney I have spent years developing my analytical skills. Applying logic and reason to problems is also a daily task for me. While making a decision for bringing criminal charges, I have look at the facts presented to me and analyze how they fit within the laws of the state. I often have to make determinations based upon logical conclusions that can be drawn from the information presented to me prior to that decision. I also bring the logic and reason to solving any problems I encounter as a parent. Recently there was a safety concern at my child's daycare and my wife and I brought to the attention of the supervisory staff and requested a meeting. In an area where it is easy to get emotional and defensive, there were no raised voices or short tempers; just conversation and understanding that lead to a resolution all parties could support.
male


AkshayKishore
Reach me @ Github / Twitter
MERN STACK
HTML/CSS3 & Javascript
C
Music, Movies, Cricket,Playing Instruments, Travelling, Cooking.


§8. Certain offices abolished. That the offices of President, minister of foreign affairs, minister of the interior, minister of finance, minister of public instruction, auditor-general, deputy auditor-general, surveyor-general, marshal, and deputy marshal of the Republic of Hawaii are hereby abolished.
Referred to in 15 H. 115, 274; 16 H. 245. See §§9, 66, 68, and 71-79.


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
32
33 34 35 36 37 38
39
40 package ti.uia.runtime;
41 import xdc.runtime.Types;
42 import xdc.runtime.Log;
43 import ti.uia.runtime.IUIATraceSyncProvider;
44
45 /*!
46 * ======== LoggerTypes ========
47 * Function pointer type definitions for various types of loggers
48 *
49 * This module defines function prototypes for use in defining
50 * callback functions that support device-specific features (e.g.
51 * synchronization with CPU Trace) and support customization and
52 * extensibility of core UIA features (e.g. logging a range of memory values).
53 */
54 module LoggerTypes {
55
56 /*!
57 * ======== LogMemoryRangeFxn ========
58 * Log an event along with values from a range of memory addresses
59 *
60 * Note that this function can support logging of null terminated strings,
61 * arrays of characters and memory mapped registgers as well as blocks of
62 * memory. The LogSnapshot module uses this callback function.
63 * Modules that implement the ILoggerSnapshot interface provide implementations
64 * of this callback function.
65 *
66 * @param(ptr) module instance object handle
67 * @param(evt) event to be logged
68 * @param(snapshotId) 0 = no other snapshot groups, Use value from
69 * LogSnapshot.getSnapshotId() for all snapshots to be
70 * grouped.
71 * @param(fileName) __FILE__ result
72 * @param(lineNum) __LINE__ result
73 * @param(fmt) a `printf` style format string
74 * @param(startAdrs) value for first format conversion character
75 * @param(lengthInMAUs) value for second format conversion character
76 *
77 * @see Log#Event
78 * @see ILoggerSnapshot#writeMemoryRange
79 */
80 typedef Void (*LogMemoryRangeFxn)(Ptr, xdc.runtime.Log.Event,
81 UInt32, UInt32, IArg, IArg, IArg, IArg, IArg);
82
83 /*!
84 * ====== InjectIntoTraceFxn ======
85 * Callback function that injects syncPoint info into GEM Trace
86 *
87 * This callback function injects correlation info into the trace stream
88 * to enable correlation between software events and hardware trace.
89 *
90 * @param(serialNum) the serial number that is to be injected
91 * @param(ctxType) the context type ID to be injected into the trace
92 *
93 * @see IUIATraceSyncProvider
94 * @see IUIATraceSyncClient
95 */
96 typedef Void (*InjectIntoTraceFxn)(UInt32, IUIATraceSyncProvider.ContextType);
97 }


BJP legislator warns AIMPLB of claim for 40,000 temples
by J B S UmanadhFirebrand BJP legislator Raja Singh Lodh warned the All India Muslim Personal Law Board against filing a review petition on Ayodhya issue in Supreme Court.
The lone BJP legislator in Telangana said Hindus would claim for the 40,000 temples demolished for Masjids during various Muslim regimes.
In a video message, the BJP's MLA without naming anyone directly alleged that the AIMPLB had corrupt members. "And one of them is a traitor from Hyderabad," he said.
Raja Singh said that the historic Supreme Court judgement had helped to build mutual trust among communities. " Prime Minister Narendra Modi and Home Minister Amit Shah are trying to build Ram Mandir involving people from all sections," he said.
"I think it is time for Indian Muslims to wake up. Ayodhya issue has been pending for 500 to 600 years. Indian Muslims are on one side and AIMPLB is on the other side", he said urging Muslims to cooperate.
Raja Singh argued that people such as Taimoor, Mohammed Ghazni, Tipu Sultan, Babar, Allauddun Chisti, Ahmed Shah, Aurangzeb had dismantled temples and built Mosques. He said Hindus can demand the restoration of all such temples.


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p2pchat
- package p2pchat
P2PChat
- Class in
p2pchat
P2PChat()
- Constructor for class p2pchat.
P2PChat
p2pchat.connection
- package p2pchat.connection
p2pchat.connection.parser
- package p2pchat.connection.parser
p2pchat.controller
- package p2pchat.controller
p2pchat.controller.listeners
- package p2pchat.controller.listeners
p2pchat.model
- package p2pchat.model
p2pchat.model.chat
- package p2pchat.model.chat
p2pchat.server
- package p2pchat.server
p2pchat.view
- package p2pchat.view
p2pchat.view.commands
- package p2pchat.view.commands
p2pchat.view.custom
- package p2pchat.view.custom
p2pchat.view.views
- package p2pchat.view.views
P2PChatController
- Class in
p2pchat.controller
P2PChatModel
- Class in
p2pchat.model
P2PChatMVC
- Class in
p2pchat
P2PChatMVC()
- Constructor for class p2pchat.
P2PChatMVC
P2PChatView
- Class in
p2pchat.view
P2PServer
- Class in
p2pchat.server
P2PServer()
- Constructor for class p2pchat.server.
P2PServer
paintComponent(Graphics)
- Method in class p2pchat.view.custom.
JUpdatableIconPanel
paintComponent(Graphics)
- Method in class p2pchat.view.custom.
JUpdatablePanel
parse()
- Method in class p2pchat.connection.parser.
InputParser
PeerToPeerConnection
- Class in
p2pchat.connection
PeerToPeerConnection()
- Constructor for class p2pchat.connection.
PeerToPeerConnection
PeerToServerConnection
- Class in
p2pchat.connection
PeerToServerConnection(ConnectionManager)
- Constructor for class p2pchat.connection.
PeerToServerConnection
PREF_HEIGHT
- Static variable in class p2pchat.view.
P2PChatView
PREF_WIDTH
- Static variable in class p2pchat.view.
P2PChatView
printSizes(Component)
- Static method in class utils.
SpringUtilities
A debugging utility that prints to stdout the component's minimum, preferred, and maximum sizes.
process(String)
- Static method in class p2pchat.connection.parser.
XMLParser
processExternal(String)
- Method in class p2pchat.model.
P2PChatModel
Process user action
processLocal(String)
- Method in class p2pchat.model.
P2PChatModel
Process user action
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Time:
What is the smallest planet in the Solar System?
Earth
Mercury
Uranus
Neptune
What do you call molten rock before it has erupted?
Lava
Volcano
Magma
Something, something... I needed a fourth answer!
What are female elephants called?
Cows
Felephant
Pigs
Brides
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DEMs during Tartary buckwheat seed development. a Venn diagram represented the overlap of DEMs among the comparisons. b Number of DEMs in the comparisons of S1 vs. S2, S1 vs. S3, and S2 vs. S3. Green and yellow bars represented the number of up- or down-regulated genes, respectively. c Expression heat map of DEMs. The different colors represent the expression abundance of the miRNAs


OrcaContext
Initialization and Termination
As a starting point of Project Orca, you need to call init_orca_context
to create or get a SparkContext for your Spark cluster (and launch Ray services
across the cluster if necessary). When your application finishes, you need to call stop_orca_context
to stop the SparkContext (and stop Ray services across the cluster if necessary).
from zoo.orca import init_orca_context, stop_orca_context
# At the very beginning:
sc = init_orca_context(cluster_mode="local", cores=2, memory="2g", num_nodes=1,
init_ray_on_spark=False, **kwargs)
# Your application goes after init_orca_context.
# When your application finishes:
stop_orca_context()
Arguments for init_orca_context
:
cluster_mode
: The mode for the Spark cluster. One of "local", "yarn-client", "k8s-client", "standalone" and "spark-submit". Default to be "local".
For "spark-submit", you are supposed to use spark-submit to submit the application. In this case, please set the Spark configurations through command line options or the properties file. You need to use "spark-submit" for yarn-cluster or k8s-cluster mode. To make things easier, you are recommended to use the launch scripts we provide.
For other cluster modes, you are recommended to install and run analytics-zoo through pip, which is more convenient.
cores
: The number of cores to be used on each node. Default to be 2.memory
: The memory allocated for each node. Default to be '2g'.num_nodes
: The number of nodes to be used in the cluster. Default to be 1. For Spark local, num_nodes should always be 1 and you don't need to change it.init_ray_on_spark
: Whether to launch Ray services across the cluster. Default to be False and in this case the Ray cluster would be launched lazily when Ray is involved in Project Orca.kwargs
: The extra keyword arguments used for creating SparkContext and launching Ray if any.
Extra Configurations
Users can make extra configurations when using the functionalities of Project Orca via OrcaContext
.
Import OrcaContext using from from zoo.orca import OrcaContext
and then you can choose to modify the following options:
- log_output
OrcaContext.log_output = False # Default
OrcaContext.log_output = True
Whether to redirect Spark driver JVM's stdout and stderr to the current python process. This is useful when running Analytics Zoo in jupyter notebook. Default to be False. Needs to be set before initializing SparkContext.
- pandas_read_backend
OrcaContext.pandas_read_backend = "spark" # Default
OrcaContext.pandas_read_backend = "pandas"
The backend for reading csv/json files. Either "spark" or "pandas".
"spark" backend would call spark.read
and "pandas" backend would call pandas.read
.
Default to be "spark".
- serialize_data_creation
OrcaContext.serialize_data_creation = False # Default
OrcaContext.serialize_data_creation = True
Whether add a file lock to the data loading process for PyTorch Horovod training. This would be useful when you run multiple workers on a single node to download data to the same destination. Default to be False.


Question: Can TRIAC's be used to drive the immersion without problems?
Probably have to fire the triac at zero crossing.
Is this the basis for the Crydom solid state relay with proportional output?
Re: Heating immersion heater - can a triac be used? - that old topic!
I have built my solar immersion controller with a triak and it is working great see image
Re: Heating immersion heater - can a triac be used? - that old topic!
Hi everyone, I am looking at using an Arduino Uno with Ct sensors to monitor my solar output and dump the excess into the immersion heater.
The water is normally heated from economy 7 and has a 3kW element.
Having trawled t'internet I was looking at using a triac to control the flow to the element. I am fairly new to the world of triacs and AC generally - apart from the odd belt from mains obviously!
An I right on the following?:
Triacs only let, effectively, 1/2 waves through?
Triacs ramp up their output linearly according to the input (from the Arduino).
Are there issues with triacs and :
a: EM noise
b: problems with the extra 1/2 wave feeding into the mains / household supply
Sorry to be vague, just trying to get my head around all of this and dont have time to read the 240+ page triac theory document kindly made available from MrSharkey
Cheers
Phill
Re: Heating immersion heater - can a triac be used? - that old topic!
More info over here...
http://openenergymonitor.org/emon/node/176


Ocala events
-
cortlandt manor historical sites
Fireball streaks across California skies: three shooting stars in one ...
Feb 16, 2013 .  Tonight, it appears that a third celestial body .
http://www.theverge.com/2013/2/16/3994618/fireball-streaks-across-california-skies-three-shooting-stars-in-oneWhat causes a "falling star"?
A "falling star" or a "shooting star" has nothing at all to do with a star! These amazing streaks of light you can sometimes see in the night sky are caused by tiny .
http://starchild.gsfc.nasa.gov/docs/StarChild/questions/question12.html
pataskala to magic mountain Upcoming events in Ocala
- Sponsored event
criminal defendant punches lawyer cnn video
Apr 6 - Dance It Studio
one moore productions voice over talant need cabinet key no original
outlook web access notification display Hottest Tickets
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Apr 11dr barbara hershey durham nc
Amway Center -
Apr 28new maternity ward at ucl
Amway Center -
Jun 25pr blogger jenny lewis
Bob Carr Performing Arts Center -
Mar 30doggett's new york city directory 1848
Amway Center -
Aug 27industrial revolution factory owners
Amway Center -
Jun 21event edutainment in italy
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Sep 13bob smith mutual funds manager
Francis Field -
Mar 17malt vinegar cole slaw recipe
St Augustine Amphitheatre -
Oct 8fire station 5 las vegas nevada
Amway Center -
May 4coming powered by phpbb
Bob Carr Performing Arts Center
Ocala's best venues
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Geminid meteor shower: Shooting stars light the sky (Photo).
Dec 14, 2012 . As I wrote a couple of days ago, the annual Geminid meteor shower peaked last night, raining down a magnificent display of shooting stars.
http://www.slate.com/blogs/bad_astronomy/2012/12/14/geminid_meteor_shower_shooting_stars_light_the_sky_photo.html -
2013 Meteor Showers | StarDate Online
A meteor shower is a spike in the number of meteors or "shooting stars" that streak through the night sky. Most meteor showers are spawned by comets.
http://stardate.org/nightsky/meteors -
Tonight, the sky belongs to shooting stars - Hindustan Times
Dec 13, 2012 . Skywatchers can get ready for a 'meteor night' from sunset on December 13 till sunrise the next day. If you are lucky, you may spot as many as .
http://www.hindustantimes.com/HTNext/LifeAndUniverse/Tonight-the-sky-belongs-to-shooting-stars/Article1-972073.aspxcarolyn pray bank of america
98 people's favorite
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Sky watchers have good weekend to catch falling stars
Oct 18, 2012 . A big meteor shower this weekend could produce as many as 60 falling stars an hour as the Earth passes through the trail of Halley's comet.
http://www.usatoday.com/story/news/nation/2012/10/18/meteor-shower-this-weekend/1641579/ -
meteor showers 2013 guide dates shooting stars comets leonids
Spread a blanket on the ground and look up in the dark night sky. . click here to read our article, "What are Meteor Showers: Facts About Shooting Stars." .
http://www.almanac.com/content/meteor-showers-guide


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