GPS Raw - The original GPS files from the receiver RINEX - RINEX files converted from the raw files Solutions - Text solutions (e.g., from OPUS). Products - Coordinate files generated, etc
File->New Folderand enter the Folder name.
Once created, from that Folder do:
File->New EntryUnder the Field Project section choose Raw GPS File. Select and upload your file.
To upload multiple files first zip them up. In the upload form open the "More..." section and check on the "Unzip archive" checkbox.
If TEQC is installed then the spatial location, time and station information (if it exists) should be harvested from the file.
You can specify an antenna and antenna height for each file or, you can specify a single value for all of the submissions.
For now, the next step is manual. OPUS will mail you the results. All you need to do is Copy and Paste the body of the email into the OPUS Solution ingest form. This will create an OPUS entry in RAMADDA and add the appropriate links to the source RINEX files. The UTM, ITRF and LAT/LON coordinates will be extracted and these more refined values will be applied to any linked RINEX or raw GPS files.
Add a comment, select the OPUS input files to use and optionally select a RAMADDA Folder to publish the results to.
You then need to specify the path to teqc with the property:
gps.teqc=/path/to/teqcThis can be placed in a .properties (e.g., gps.properties) file in the RAMADDA home dir or can be specified in the Admin->Settings properties field.
If you have raw Trimble GPS files you also need to install runpkr which is used to convert the raw files into a form that TEQC can process. To set this define the property:
gps.runpkr=/path/to/runpkr


It's lovely to see someone from 1998 on our web application! Thanks for visiting.
Unfortunately, automata is a web application that requires Javascript to run properly.
Please Enable Javascript and try again.


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| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object atg.servlet.security.ServletSecurityUtils
UserResolver is a collection of static methods to help Security Servlets and droplets to resolve the User instance from the current HttpSession as well as to see if a an element from a list of Personae is represented within User
| Field Summary | |
static java.lang.String |
CLASS_VERSION
Class version string |
| Constructor Summary | |
ServletSecurityUtils()
|
| Method Summary | |
static User |
currentUser(java.lang.String pPath,
DynamoHttpServletRequest pRequest)
Given a path and the handle to the current request, this static call will resolve the User instance and return it |
static boolean |
stringArrayToPersonaArray(java.lang.String[] pNames,
Persona[] pPersonae,
UserAuthority pUserAuthority)
Takes an array of Personae names which should be contained in a given UserAuthority, and converts them into an array of Personae instances returns true if convertions was successful. |
static boolean |
userHasPersona(User pUser,
UserAuthority pUserAuthority,
Persona[] pGroups)
Checks to see if pUser has a Persona in the given array of Personae It is up to the caller to insure the integrity of the arguments provided to this function call. |
static boolean |
userHasPersona(User pUser,
UserAuthority pUserAuthority,
java.lang.String[] pGroups)
Checks to see if pUser has a Persona in the given array of Personae It is up to the caller to insure the integrity of the arguments provided to this function call. |
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
public static java.lang.String CLASS_VERSION
| Constructor Detail |
public ServletSecurityUtils()
| Method Detail |
public static User currentUser(java.lang.String pPath, DynamoHttpServletRequest pRequest)
pPath
- the path to where the User definition liespRequest
- the current HTTP request (what holds the state)
public static boolean userHasPersona(User pUser, UserAuthority pUserAuthority, Persona[] pGroups)
pGroups
- an array of Personae that represent different user groupspUser
- is an instance of User class which could contain 0 or N PersonaepUserAuthority
- UserAuthority instance with which pUser was authenticated
public static boolean userHasPersona(User pUser, UserAuthority pUserAuthority, java.lang.String[] pGroups)
pGroups
- an array of names of groups that represent different user personaepUser
- is an instance of User class which could contain 0 or N PersonaepUserAuthority
- UserAuthority instance with which pUser was authenticated
public static boolean stringArrayToPersonaArray(java.lang.String[] pNames, Persona[] pPersonae, UserAuthority pUserAuthority)
pNames
- an array of String that represent different user groupspPersonae
- is initially empty array of the same size as pNames, which
should be filled out by the end of the operation.pUserAuthority
- UserAuthority instance which should contain approprite personae
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Explanation
The Peptide per Ratio is a chart of the peptide distribution versus the study variables in the quantitation experiment. It shows the different between all the replicates and sample for every peptide. Also shows the relation between different conditions globally. The following example shows the differences between all the samples in ITRAQ experiments.
The inspector chart can be used independently and plugged in Java desktop applications but also in can be use to generate JSON structures with the distributions and values of the nine charts. It has been used in the PRIDE pipeline during the submission process to generate the quality metrics for each file.


A solid square bar of cross-sectional dimensions CS1 x CS1 is attached rigidly to the wall at point A and has a gap of 1 mm from the rigid wall at point B at T degree C. Knowing the bar is made of aluminum,
L =
L m
\delta=
gap m
T_n=
nT degree C
E=
E Pa
\alpha=
a
\delta = \alpha \Delta T L
round((gap / (a*L) + T)*1000) / 1000 The correct answer expected from the student
round((a * (nT-T) * L)*1000) / 1000 The correct answer expected from the student
round((gap / (L * (nT-T)))*1000) / 1000 The correct answer expected from the student
round((gap / (a * (nT-T)))*1000) / 1000 The correct answer expected from the student


Class
DPBandConfigSimple class to configure banded alignments.
Simple class to configure banded alignments.
| Defined in | <seqan/align.h> |
|---|---|
| Signature |
template <typename TSwitch>
class DPBandConfig<TSwitch>;
|
Template Parameters
TSwitch |
Tag to switch between banded and unbanded alignments. One of DPBandSwitch. Defaults to BandOff. |
|---|
Member Function Overview
Interface Function Overview
-
TSize bandSize(obj);
Returns the size of the band. -
TPosition lowerDiagonal(obj);
Returns the value of the lower diagonal. -
setLowerDiagonal(obj, val);
Sets the value of the lower diagonal. -
setUpperDiagonal(obj, val);
Sets the value of the upper diagonal. -
TPosition upperDiagonal(obj);
Returns the value of the upper diagonal.
Interface Metafunction Overview
-
typename Position<T>::Type;
Metafunction returning the position type. -
typename Size<T>::Type;
Metafunction returning the size type.
Detailed Description
To compute banded alignments use DPBand as a shortcut for the DPBandConfig with band switched on.
Member Functions Detail
DPBandConfig<TSwitch>();
DPBandConfig<BandOn>(lowerDiag, upperDiag);
Constructor.
Template Parameters
TSwitch |
Tag to switch between banded and unbanded alignments. One of DPBandSwitch. The second constructor is only supported when DPBandConfig is specialized with BandOn. |
|---|
Parameters
lowerDiag
|
The value for the lower diagonal of the band. |
|---|---|
upperDiag
|
The value for the upper diagonal of the band. |
A negative value for the diagonals indicates an intersection of the diagonal with the vertical sequence (y-axis) and a positive value indicates an intersection with the horizontal sequence (x-axis). The value of the lower diagonal has to compare less or equal to the value of the upper diagonal.
Data Races
Thread safety unknown!
Interface Functions Detail
TSize bandSize(obj);
Note.
If the band is switched off this function always returns 0.
Returns the size of the band.
Parameters
obj
|
The object of type DPBandConfig to query the band size for. |
|---|
Returns
TSize |
The number of diagonals covered by the band. |
|---|
Data Races
Thread safety unknown!
TPosition lowerDiagonal(obj);
Note.
If the band is switched off this function always returns 0.
Returns the value of the lower diagonal.
Parameters
obj
|
The object of type DPBandConfig to query the lower diagonal for. |
|---|
Returns
TPosition |
The value of the lower diagonal. |
|---|
Data Races
Thread safety unknown!
setLowerDiagonal(obj, val);
Note.
If the band is switched off, this function defaults to no-op.
Sets the value of the lower diagonal.
Parameters
obj
|
The object of type DPBandConfig to set the lower diagonal for. |
|---|---|
val
|
The new value for the lower diagonal. |
Data Races
Thread safety unknown!
setUpperDiagonal(obj, val);
Note.
If the band is switched off, this function defaults to no-op.
Sets the value of the upper diagonal.
Parameters
obj
|
The object of type DPBandConfig to set the upper diagonal for. |
|---|---|
val
|
The new value for the upper diagonal. |
Data Races
Thread safety unknown!
TPosition upperDiagonal(obj);
Note.
If the band is switched off this function always returns 0.
Returns the value of the upper diagonal.
Parameters
obj
|
The object of type DPBandConfig to query the upper diagonal for. |
|---|
Returns
TPosition |
The value of the upper diagonal. |
|---|
Data Races
Thread safety unknown!


We wanted to make an easy way for people to both find and post about found items, and thought that a lost and found page would be quite useful.
Our user group is primarily college students, since people often lose water bottles, ID cards, etc. In terms of future goals, we hope to enable map pinning and more filtering options to ensure a seamless user experience.
For posting, first log into your Gmail account, then on your user page, upload an image and write a description. The search function also works, so search any terms and the page will load any posts that match. If you want to see all the posts again after searching something, you can do an empty search.
Rising Junior at UC Berkeley
Rising Junior at Smith College
Rising Junior at UCLA
Rising Junior at Georgia Tech


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{{'All Domains' | translate}}
{{domain.name}}
{{'Criticity' | translate}}
{{criticity.domain_critic_name}}
add_circle
{{criticity.domain_critic_name | translate}}
{{domain}}remove_circle
{{'Maintenance Time Criticity' | translate}}
{{'Your changes for Maintenance Time Criticity are successfully saved!'}}{{'Your changes for Maintenance Time Criticity could not be saved. Please try again later.'|translate}}
{{"Given M maintenance's end date for a software product, please provide values for start month for the following levels of time criticity:"|translate}}
{{'Your changes for Risk Matrix are successfully saved!'}}
{{'Your changes for Risk Matrix could not be saved. Please try again later.'|translate}}{{tile.text}}-- {{'Select'|translate}} --{{risk.risk_name}}


Hi Sean,
Thank you for the suggestion. After editing the input file I gave a shot at the calculation this time it ended up saying the below error message.
Input file:
title B3LYP/cc-pvdz/zora"
memory total 400 mb
echo
geometry units angstroms
symmetry c1
Ir 0.0429710000000 0.0037150000000 -0.0518300000000
C 2.0837130000000 0.2858480000000 -0.1881780000000
C 2.4110990000000 0.4583120000000 -1.5657240000000
C 3.7831340000000 0.7080860000000 -1.8802690000000
C 4.7652080000000 0.7909470000000 -0.8775270000000
C 4.4188390000000 0.6383280000000 0.4682270000000
C 3.0821370000000 0.3980000000000 0.8086920000000
C 1.3356020000000 0.3528330000000 -2.5939620000000
N 0.0902830000000 0.1007240000000 -2.1018020000000
C -0.9315740000000 -0.0265630000000 -2.9795080000000
C -0.7944140000000 0.0858860000000 -4.3656600000000
C 0.4758120000000 0.3496930000000 -4.8824170000000
C 1.5449290000000 0.4823910000000 -3.9873640000000
F 4.2182270000000 0.8801900000000 -3.1493910000000
F 5.3640050000000 0.7268600000000 1.4331450000000
H 5.7932200000000 0.9774600000000 -1.1474910000000
H 2.8390300000000 0.3019010000000 1.8546090000000
H -1.9117540000000 -0.2336030000000 -2.5860150000000
H -1.6494290000000 -0.0259470000000 -5.0157220000000
H 0.6310880000000 0.4470350000000 -5.9469250000000
H 2.5094620000000 0.6794230000000 -4.4187700000000
C -0.1830850000000 2.0442310000000 0.1045180000000
C -1.5781820000000 2.3288620000000 0.0993620000000
C -1.9585370000000 3.6954000000000 0.2772130000000
C -0.9993590000000 4.7154180000000 0.4130310000000
C 0.3657590000000 4.4129920000000 0.3894330000000
C 0.7691740000000 3.0808140000000 0.2396900000000
C -2.5566280000000 1.2145890000000 -0.0627220000000
N -2.0189890000000 -0.0395580000000 -0.0978640000000
C -2.8690300000000 -1.0866580000000 -0.2205200000000
C -4.2529320000000 -0.9701620000000 -0.3713210000000
C -4.8073170000000 0.3107770000000 -0.3786320000000
C -3.9491100000000 1.4065250000000 -0.2289280000000
F -3.2518690000000 4.0885700000000 0.3340970000000
F 1.2873660000000 5.3963330000000 0.5163360000000
H -1.3180120000000 5.7383570000000 0.5413570000000
H 1.8267330000000 2.8678250000000 0.2396730000000
H -2.4569190000000 -2.0787580000000 -0.2021350000000
H -4.8739190000000 -1.8483140000000 -0.4695330000000
H -5.8716690000000 0.4537060000000 -0.4945890000000
H -4.4049260000000 2.3798190000000 -0.2461500000000
N -0.9813790000000 -0.0040710000000 2.5276970000000
C -1.3246040000000 -1.2770580000000 2.7381330000000
C -0.1902840000000 -2.0557810000000 2.3540030000000
C 0.8059810000000 -1.1904620000000 2.6895770000000
N 0.2519230000000 -0.1617770000000 1.9924980000000
C -0.1441430000000 -3.1927370000000 1.3714000000000
P 0.1323950000000 -2.3547690000000 -0.2818950000000
C 1.9693860000000 -2.6539570000000 -0.5927470000000
C 2.4214350000000 -2.7557740000000 -1.9272970000000
C 3.7788860000000 -2.9869860000000 -2.2198140000000
C 4.7073060000000 -3.1327180000000 -1.1734450000000
C 4.2709370000000 -3.0543430000000 0.1616210000000
C 2.9115260000000 -2.8223340000000 0.4479190000000
C -0.4069850000000 -3.8716860000000 -1.2436460000000
C 0.1571880000000 -5.1490670000000 -1.0244340000000
C -0.2773710000000 -6.2638230000000 -1.7671470000000
C -1.2807100000000 -6.1128480000000 -2.7420770000000
C -1.8417500000000 -4.8440320000000 -2.9769870000000
C -1.4023530000000 -3.7322200000000 -2.2331360000000
C -2.7535400000000 -1.6731700000000 3.0743240000000
F -3.6253030000000 -0.7042600000000 2.7905580000000
F -3.1036280000000 -2.7695610000000 2.4001890000000
F -2.8303670000000 -1.9423480000000 4.3776610000000
H 1.0177680000000 -0.8664360000000 3.7023820000000
H 0.6443870000000 -3.9042810000000 1.6107400000000
H -1.0734030000000 -3.7610140000000 1.3602710000000
H 1.7140160000000 -2.6495550000000 -2.7375240000000
H 4.1052790000000 -3.0524600000000 -3.2475680000000
H 5.7503060000000 -3.3082870000000 -1.3942070000000
H 4.9805190000000 -3.1682590000000 0.9685000000000
H 2.6081800000000 -2.7591280000000 1.4802430000000
H 0.9409870000000 -5.2791660000000 -0.2928640000000
H 0.1648930000000 -7.2338920000000 -1.5926800000000
H -1.6135570000000 -6.9671120000000 -3.3136690000000
H -2.6061670000000 -4.7226800000000 -3.7306450000000
H -1.8314840000000 -2.7614180000000 -2.4283110000000
end
basis
Ir library cc-pVDZ-pp rel
P library 6-31G**
C library 6-31G**
F library 6-31G**
H library 6-31G**
N library 6-31G**
end
DFT
XC B3LYP
END
RELATIVISTIC
ZORA ON
END
task DFT energy
Error Message:
Superposition of Atomic Density Guess
-------------------------------------
charge = 77.0 Ir (Iridium)
symmetry species s p d f
number of basis functions =22 19 11 1
number of cont. functions = 4 4 3 1
number of closed shells = 6 4 2 1
number of open shells = 0 0 1 0
open shell occupation = 0 0 7 0
------------------------------------------------------------------------
atomscf:atomd: error in atom scf 0
------------------------------------------------------------------------
------------------------------------------------------------------------
current input line :
101: task DFT energy
------------------------------------------------------------------------
------------------------------------------------------------------------
This error has not yet been assigned to a category
------------------------------------------------------------------------
For more information see the NWChem manual at http://nwchemgit.github.io/index.php/NWChem_Documentation
For further details see manual section: No section for this category
0:atomscf:atomd: error in atom scf:Received an Error in Communication
MPI_ABORT was invoked on rank 0 in communicator MPI COMMUNICATOR 3 DUP FROM 0
with errorcode -1.

You may or may not see output from other processes, depending on
exactly when Open MPI kills them.
Primary job terminated normally, but 1 process returned
a non-zero exit code.. Per user-direction, the job has been aborted.
mpirun detected that one or more processes exited with non-zero status, thus causing
the job to be terminated. The first process to do so was:
Process name: [[8875,1],0]
Exit code: 255
|


@return [Hash]
The mapping that resulted from the match. Note that this mapping does not include keys or values for variables that appear in the Template, but are not present in the URI.
@return [Addressable::Template]
The Template used for the match.
@return [Addressable::URI]
The URI that the Template was matched against.
Creates a new MatchData object. MatchData objects should never be instantiated directly.
@param [Addressable::URI] uri
The URI that the template was matched against.
# File lib/addressable/template.rb, line 101 def initialize(uri, template, mapping) @uri = uri.dup.freeze @template = template @mapping = mapping.dup.freeze end
Accesses captured values by name or by index.
@param [String, Symbol, Fixnum] key
Capture index or name. Note that when accessing by with index of 0, the full URI will be returned. The intention is to mimic the ::MatchData#[] behavior.
@param [#to_int, nil] len
If provided, an array of values will be returend with the given parameter used as length.
@return [Array, String, nil]
The captured value corresponding to the index or name. If the value was not provided or the key is unknown, nil will be returned. If the second parameter is provided, an array of that length will be returned instead.
# File lib/addressable/template.rb, line 168 def [](key, len = nil) if len to_a[key, len] elsif String === key or Symbol === key mapping[key.to_s] else to_a[key] end end
Returns a String
representation of the MatchData's state.
@return [String] The MatchData's state, as a String
.
# File lib/addressable/template.rb, line 211 def inspect sprintf("#<%s:%#0x RESULT:%s>", self.class.to_s, self.object_id, self.mapping.inspect) end
Dummy method for code expecting a ::MatchData instance
@return [String] An empty string.
# File lib/addressable/template.rb, line 220 def pre_match "" end
@return [Array]
Array with the matched URI as first element followed by the captured values.
# File lib/addressable/template.rb, line 182 def to_a [to_s, *values] end
@return [String]
The matched URI as String.
# File lib/addressable/template.rb, line 189 def to_s uri.to_s end
@return [Array]
The list of values that were captured by the Template. Note that this list will include nils for any variables which were in the Template, but did not appear in the URI.
# File lib/addressable/template.rb, line 141 def values @values ||= self.variables.inject([]) do |accu, key| accu << self.mapping[key] accu end end
Returns multiple captured values at once.
@param [String, Symbol, Fixnum] *indexes
Indices of the captures to be returned
@return [Array]
Values corresponding to given indices.
@see Addressable::Template::MatchData#[]
# File lib/addressable/template.rb, line 203 def values_at(*indexes) indexes.map { |i| self[i] } end
@return [Array]
The list of variables that were present in the Template. Note that this list will include variables which do not appear in the mapping because they were not present in URI.
# File lib/addressable/template.rb, line 130 def variables self.template.variables end


{% extends "_layouts/struct.html" %} {% block main %} Oops! 404. That page can’t be found. {% endblock %}
That page can’t be found.


Search fields: author, short, detail, keywords, and location
Search method: use ':' to separate fields and the word you are searching for. '&&' to search for more than one field ex) author: James && keywords: test
{% for r in found_entries %}
{% if r.private == False %}


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About me
Research Interests
- Music Information Retrieval
- Deep Learning
Career
- 2020 - now. CEO (Co-founder), Neutune, Seoul, South Korea
Education
- 2017 - 2021. PhD (Thesis), Graduate School of Culture Technology, KAIST, Daejeon, South Korea (Advisor: Juhan Nam)
- 2015 - 2017. MS, Graduate School of Culture Technology, KAIST, Daejeon, South Korea
- 2007 - 2015. BS, EE, Hanyang University, Seoul, South Korea
Experience
- 2020. Visiting PhD, Music and Audio Research Laboratory, New York University, New York City, United States
- 2019. Research Intern, Audio Research Group, Adobe, San Francisco, United States
- 2017. Research Intern, Clova Artificial Intelligence Research, Naver, Seongnam, South Korea
Tutorial
Metric Learning for Music Information Retrieval
Brian McFee, Jongpil Lee, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2020
Waveform-based Music Processing with Deep Learning
Jordi Pons, Jongpil Lee, and Sander DielemanInternational Society of Music Information Retrieval Conference (ISMIR), 2019
Journals
Semantic Tagging of Singing Voices in Popular Music Recordings
Keunhyoung Luke Kim, Jongpil Lee, Sangeun Kum, Chae Lin Park, and Juhan NamIEEE/ACM Transactions on Audio, Speech and Language Processing, 2020
Comparison and Analysis of SampleCNN Architectures for Audio Classification
Taejun Kim, Jongpil Lee, and Juhan NamIEEE Journal of Selected Topics in Signal Processing, 2019
Deep Learning for Audio-based Music Classification and Tagging: Teaching Computers to Distinguish Rock from Bach
Juhan Nam, Keunwoo Choi, Jongpil Lee, Szu-Yu Chou, and Yi-Hsuan YangIEEE Signal Processing Magazine, 2019
SampleCNN: End-to-End Deep Convolutional Neural Networks Using Very Small Filters for Music Classification
Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim, and Juhan NamApplied Sciences, 2018
Multi-Level and Multi-Scale Feature Aggregation Using Pre-trained Convolutional Neural Networks for Music Auto-tagging
Jongpil Lee, and Juhan NamIEEE Signal Processing Letters, 2017
Exhibition
NEUROSCAPE: Artificial Soundscape Based on Multimodal Connections of Deep Neural Networks
Seungsoon Park, Jongpil Lee, and Juhan NamInternational Computer Music Conference (ICMC), 2018
Conferences, Workshops, Challenges, Demos
Learning a Cross-domain Embedding Space of Vocal and Mixed Audio with a Structure-preserving Triplet Loss
Keunhyoung Luke Kim, Jongpil Lee, Sangeun Kum, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2021
Mixed Scape: Development of Framework and Artwork for Auditory Correspondence in Mixed Reality
Seungsoon Park, Jongpil Lee, Taewan Kim, Tae Hong Park, Joonhyung Bae, and Juhan NamInternational Computer Music Conference (ICMC), 2021
Metric Learning VS Classification for Disentangled Music Representation Learning
Jongpil Lee, Nicholas J. Bryan, Justin Salamon, Zeyu Jin, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2020
Musical Word Embedding: Bridging the Gap between Listening Contexts and Music
Seungheon Doh, Jongpil Lee, Tae Hong Park, and Juhan NamMachine Learning for Media Discovery Workshop, International Conference on Machine Learning (ICML), 2020
Disentangled Multidimensional Metric Learning for Music Similarity
Jongpil Lee, Nicholas J. Bryan, Justin Salamon, Zeyu Jin, and Juhan NamIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
*** IEEE SPS Student Travel Grant ***
Zero-shot Learning for Audio-based Music Classification and Tagging
Jeong Choi*, Jongpil Lee*, Jiyoung Park, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2019
* Equally contributed
A Cross-Scape Plot Representation for Visualizing Symbolic Melodic Similarity
Saebyul Park, Taegyun Kwon, Jongpil Lee, Jeounghoon Kim, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2019
Representation Learning of Music Using Artist, Album, and Track Information
Jongpil Lee, Jiyoung Park, and Juhan NamMachine Learning for Music Discovery Workshop, International Conference on Machine Learning (ICML), 2019
Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging
Jeong Choi, Jongpil Lee, Jiyoung Park, and Juhan NamMachine Learning for Music Discovery Workshop, International Conference on Machine Learning (ICML), 2019
Deep Content-User Embedding Model for Music Recommendation
Jongpil Lee, Kyungyun Lee, Jiyoung Park, Jangyeon Park, and Juhan Namhttps://arxiv.org/abs/1807.06786, 2018
Representation Learning of Music Using Artist Labels
Jiyoung Park*, Jongpil Lee*, Jangyeon Park, Jung-Woo Ha, and Juhan NamInternational Society of Music Information Retrieval Conference (ISMIR), 2018
* Equally contributed
A Hybrid of Deep Audio Feature and i-vector for Artist Recognition
Jiyoung Park, Donghyun Kim, Jongpil Lee, Sangeun Kum, and Juhan NamJoint Workshop on Machine Learning for Music, International Conference on Machine Learning (ICML), 2018
Sample-level CNN Architectures for Music Auto-tagging Using Raw Waveforms
Taejun Kim, Jongpil Lee, and Juhan NamIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018
Raw Waveform-based Audio Classification Using Sample-level CNN Architectures
Jongpil Lee, Taejun Kim, Jiyoung Park, and Juhan NamMachine Learning for Audio Signal Processing Workshop, Neural Information Processing Systems (NIPS), 2017
Building K-POP Singing Voice Tag Dataset: A Progress Report
KeunHyoung Luke Kim, Sangeun Kum, Chae Lin Park, Jongpil Lee, Jiyoung Park, and Juhan NamLate-Breaking/Demo Session of International Society of Music Information Retrieval Conference (ISMIR), 2017
MUSIC GALAXY HITCHHIKER: 3D Web Music Navigation Through Audio Space Trained with Tag and Artist Labels
Dongwoo Suh, Kyungyun Lee, Jongpil Lee, Jiyoung Park, and Juhan NamLate-Breaking/Demo Session of International Society of Music Information Retrieval Conference (ISMIR), 2017
Cross-cultural Transfer Learning Using Sample-level Deep Convolutional Neural Networks
Jongpil Lee, Jiyoung Park, Chanju Kim, Adrian Kim, Jangyeon Park, Jung-Woo Ha, and Juhan NamMusic Information Retrieval Evaluation eXchange (MIREX), 2017
1st place in the four K-POP tasks across all algorithms submitted so far
Representation Learning Using Artist labels for Audio Classification Tasks
Jiyoung Park, Jongpil Lee, Jangyeon Park, Jung-Woo Ha, and Juhan NamMusic Information Retrieval Evaluation eXchange (MIREX), 2017
1st place in the Music Mood Classification task across all algorithms submitted so far
Combining Multi-Scale Features Using Sample-level Deep Convolutional Neural Networks for Weakly Supervised Sound Event Detection
Jongpil Lee, Jiyoung Park, Sangeun Kum, Youngho Jeong, and Juhan NamProceedings of the 2nd Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), 2017
Multi-Level and Multi-Scale Feature Aggregation Using Sample-level Deep Convolutional Neural Networks for Music Classification
Jongpil Lee, and Juhan NamMachine Learning for Music Discovery Workshop, International Conference on Machine Learning (ICML), 2017
Sample-level Deep Convolutional Neural Networks for Music Auto-tagging Using Raw Waveforms
Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim, and Juhan NamSound and Music Computing Confenrence (SMC), 2017
The Effect of DJs’ Social Network on Music Popularity
Hyeongseok Wi, Kyung hoon Hyun, Jongpil Lee, and Wonjae LeeInternational Computer Music Conference (ICMC), 2016
Contact
- jongpillee.brian (at) gmail.com
- richter (at) kaist.ac.kr


This app will help you keep track of your music lessons and practice
- The timeline section lets you add, edit and delete practice sessions as well as display a list of all practice sessions
- The goals section lets you add, edit and delete a goal, as well as display the current goal
- The resources section is incomplete and was not meant to be part of the final product, but I was unable to remove the button for it
1.0.1Current versionHand-in version
- Fixed bug 5 - Warning icon not displayed on timelines screen
- Added about section
- Added confirmation dialogs
- Some bug fixes
- Added some comments to the code
- 1Cannot navigate from resources page about page
- 2Updating the list of practice sessions displayed from the database requires a page reload
- 3Updating the goal displayed from the database requires a page reload and/or switching tabs
- 4Edit button displayed on goals screen when no goal exists
- 5Wraning icon not displayed on timeline screen
- 6Vertical scrolling for action buttons needs a better solution
Link to new version with the latest updates and features. This version will remain here since it is the one I handed in
assignmentTo develop next


Battle of Ohio: Browns win third straight over Bengals
by John Boyle - Staff WriterThe Cleveland Browns won their third straight game over the Cincinnati Bengals, scoring a 27-19 victory Sunday at FirstEnergy Stadium.
Nick Chubb rushed for 106 yards and Kareem Hunt added touchdown run as the Browns (6-7) kept their faint playoff hopes alive.
Denzel Ward returned an interception 61 yards for a score and the Browns defense limited the Bengals (1-12) to three field goals and a touchdown on five red-zone trips. The Browns stopped Andy Dalton on a fourth-and-goal quarterback draw from the 5 in the fourth quarter.
Cincinnati’s Joe Mixon rushed for 146 yards and a TD.
It was the Bengals’ ninth straight AFC North loss and their 11th straight road loss.
The teams meet again in the final game of the regular season in Cincinnati.


{% extends "base.html" %} {% block content %} {% block index %} {% endblock %} {% load staticfiles %} {% load thumbnail %}
Please limit your input to 40 characters
{% elif has_special_characters != None %}Please include only alphabetical or numerical characters in the search input
{% endif%} {% if forloop.counter|divisibleby:4 %}Sorry, no item related to "{{ search_keyword }}".
{% if suggested_items_search == 1%}Here are a few similar items we found in a different category:
{% else %}Here are a few recommended items:
{% endif %} {% for item in suggested_items %} {% if forloop.first %}Sorry, no item in {{ picked_category }}.
Here are a few recommended items:
{% for item in suggested_items %} {% if forloop.first %}Please limit input to 40 characters.
{%elif has_special_characters != None%}Please don't include special characters.
{% endif %} {% endfor %}


Goal:
Customize the tutorialScritp.xml file to create a unique tutorial title.
Steps to complete:
- Open tutorialScript.xml with a text editor
- Change the title of the tutorial. Make the changes as outlined in the file to the right by following these steps: (Refer to the legend below)
- Change the value of the 'name' attribute of the 'tutorial' tag to 'New Tutorial From Template'
- Save tutorialScript.xml
See the effects of your work
(Click here for an example of the expected results of this step)
- If 'New Tutorial' is already open, then reload it using the reload icon to the left of the tutorial title
- If 'New Tutorial' is not already open then navigate to Learn → Technology Explorer → New Tutorial
You should now see that the tutorial name has been changed in both the main tab title and the tutorial title next to the reload icon.
The changes are indicated with the following:
- Indicated text has been removed
- Indicated text has been edited
- Indicated text has been added
- Indicated text is the source of a copy


{% extends 'global/base.html' %} {% load staticfiles rev %} {% block extra_js %} {% endblock %} {% block content %}
Django Girls is an initiative aimed at introducing women who have never coded before to the world of technology and increasing the diversity within the tech industry. We do that by organizing workshops and inviting women to join us to learn how to build the internet using HTML, CSS, Python and Django in a safe, friendly and inclusive environment.
As a Django Girls Organizer, you make a commitement to foster and advance Django Girls values:


WCS Lean In Circle: Behavioral Interview Edition
Welcome!
Get into groups of 4-6
Introductions
- Name
- Major/Minors
- Year
- Where You're From
- Fields of CS You're Interested In (robotics, data, HCI, etc.)
- One Fun Fact
Pitching Yourself
- Do: Firm handshake, eye contact
- Do: Have your resume in view, but start with a normal conversation
- Do: Ask about certain teams after having done your research
- Don't: Go up to a company and ask what they do, or ask if they have developer positions available
Let's Practice!
- Pair up with the person next to you: take turns pitching yourself to one another, as if you were at a career fair
Example
- Hi, nice to meet you, I’m Emily. I am currently a sophomore studying Computer Science. Last summer, I had an internship at kCura and I primarily worked on a web application that processed XML data for US patents to be used in a web application. This internship sparked an interest in web development. The positions you have would be a good fit for someone with my skills and interests. Could you tell me a little bit more about the positions you have in the Front-end teams at Company Name Here? I’m particularly interested in Specific Company Teams/Divisions Here.
What would you say are your weaknesses?
- Why would you say that is your weakness?
- How are you improving on that weakness?
Tips
- Don't say the cliche - "I'm a perfectionist. I work too hard. I'm lazy." - everyone says this, doesn't reveal anything about yourself.
Example
- My weakness is public speaking. I really want to improve this skill for future project and group presentations. I recently had a presentation due for a Communications class and I practiced my speech in front of the mirror to watch out for “ums” and “likes”.
Why this works
- Shows the recruiter that you have recognized a sufficient weakness and that you are actively trying to improve upon it.
What would you say are your strengths?
- Give examples as to why you consider this your strength.
- Why do you think this strength will convince me to hire you?

- If you need a third opinion, reviewing your resume can help you.
- Back up your strengths with stories - this helps portray confidence rather than arrogance.
Example
- Scenario: Front-end developer position interview
- “I think my greatest strength is attention to detail. Through various projects, I have developed a user interfaces for websites and learning responsive design has really heightened my awareness of maximizing usability on various screen sizes and paying attention to changes in styling. I am meticulous and follow through with my designs.”
Why this works
- Shows the recruiter why they should hire you, in particular, if your strength matches the strengths they look for in the position you’re interviewing for.
- Shows the recruiter why you’re a good fit.
- Try to match your greatest strength to what the company has put as desired skills in the job posting.
How have you handled a difficult working relationship with a teammate for a project or other related event?
- What was the challenge you faced?
- What actions did you take the resolve this?
Tips
- Give context to the project/situation. What was the project? How big was your team? What was the task breakdown?
- Many company cultures value teamwork, so showing that you have this experience will show the recruiter that you can work on their teams.
- Don’t bash the teammate. Instead, explain what the challenge was and then what steps you took to resolve it.
- Emphasize what you learned from that experience.
- STAR - Situation Task Action Result
Example
- “Last semester, for a final class project, 3 other students and I worked on a web app for helping students find distinct restaurants. But one of our teammates often didn’t share what he was coding. We often felt lost and that we couldn’t contribute as much. So at one of our meetings, we sat down and had a feedback session...After this session, we started implementing pair-programming so that everyone felt that their contribution was more equal.”
Why This Works
- Shows that you have teamwork experience
- Show that you can easily integrate with already established teams at the company
- Shows that you will be able to bring something to the table
- Shows that you can resolve conflicts and help put out fires for the team benefit
Describe a project you have worked on in the past, either academic or extracurricular.
- What were some of the challenges you faced while doing the project and how did you overcome them?
- What were some of the lessons you learned during this project period?
Tips
- Describe the process you went through, from planning to implementing to finish.
- Describe any challenges you had along the way (in case of CS, development wise, setup, bugs, etc) and how you overcame them/what you learned from them
- STAR - Situation, Task, Action, Result
Example
- A project that I have worked on in the past is the website for a startup called Miss Possible. I first developed their landing page using Bootstrap, HTML/CSS and some Javascript. Then I implemented some backend features, allowing the startup to collect emails for their newsletter. One of the biggest challenges for me was collaborating with graphic designers on assets for the site...
Why This Works
- Shows that you have motivation to learn skills outside of classroom.
- Shows that you are willing to work on expanding your technical skills


FLATLINERS A film review by Andrew Hicks Copyright 1996 Andrew Hicks / Fatboy Productions
(1990) **1/2 (out of four)
In medical slang, a "flatline" is when a person suffers clinical and mental death. Ironically, the film FLATLINERS does the same thing about halfway through. It starts out a fascinating drama about a group of medical students who have found a way to induce death and bring themselves back to life, experiencing the mystery of the afterlife and living to tell abotu it. It ends up becoming a supernatural thriller reminiscent of the most mediocre Stephen King TV-movie adaptations.
At the outset, Keifer Sutherland convinces a few of of his fellow students to help him with his death-cheatin' experiment, which calls for them to lower his body temperature and inject various chemicals into his blood stream until he flatlines. Kiefer flies over a giant field of flowers and trees for awhile. Then, thirty seconds later, they begin to raise his temperature and electroshock him back to life. Here, as with every other part of the movie where one of the flatliners is being brought back to life, director Joel Schumacher milks every drop of suspense he can get by making us think the students won't be able to bring their colleague back from the great beyond.
Sutherland comes back blathering about the tunnel, the shining light and all that crap, and suddenly the other students want to experience it as well. Next comes Billy Baldwin, the stud of the bunch, whose personal afterlife involves quick cuts of beautiful women in various stages of undress, once again reinforcing my belief that heaven is an Aerosmith video. Finally, Kevin Bacon and Julia Roberts experience a few fleeting moments of death.
But the movie's only halfway over, so we now some kind of complications will come along with these four manipulating the forces of nature. I just didn't think it would be a cross between BILL AND TED'S BOGUS JOURNEY and the ending of GHOSTBUSTERS. Suddenly everyone's worst memory of regret comes back to haunt them, Keifer's being an eight-year-old boy he inadertently killed when he was a child, Joe's in the form of all the women he's lied to for cheap sex (which he also secretly videotaped and sent to Bob Saget), Kevin's nightmare a ten-year-old girl he used to torment at school and Julia's her dead father.
It's at this point the movie crashes and burns, becoming a second-rate horror/thriller. The topic of death is one that either interests or frightens everyone, and FLATLINERS could have taken more time to explore the theme instead of making it a plot device that brings the characters' worst feelings of guilt to life. In reality, the only guilt these people should feel is standing by and letting this movie die instead of doing something to save it.
--
Visit the Movie Critic at LARGE homepage at http://www.missouri.edu/~c667778/movies.html
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


NOTE: Filters have in effect been replaced by Replacer add-on and scripts which are more powerful and flexible.
Filters will be removed in a future version of ZAP.
Filters add extra features that can be applied to every request and response.
By default no filters are initially enabled. Enabling all of the filters may
slow down the proxy.
Filters are configured via the Filters dialog.
| UI Overview | for an overview of the user interface | |
| Features | provided by ZAP |


Ariana Grande, sick, might cancel a show
She says she's struggling with 'so much pain'
by Theresa Waldrop, CNN(CNN) - Ariana Grande told her fans that she's "very sick" and may have to cancel an upcoming concert.
In an Instagram post Saturday, the pop star said her throat and head "are still in so much pain," and it's difficult to breathe during a show. She said she'd been struggling with the illness since her concert in London last month.
"I just really don't know what's happening with my body right now and need to figure it out," Grande said.
Although canceling the show is "the last thing i would ever want to do," Grande wrote, fans should take the post as a "gentle heads up" in case she can't "make the show happen" on Sunday.
Grande is scheduled to perform in Lexington, Kentucky, Sunday, the next stop on her world tour that ends in December.
Grande said she's taking medication and is on IV drips, "doing everything i possibly can to pull through."
Her fans wished her well and encouraged her to take care of her health first.
"We wouldn't want anything happening to our beloved Ari," Ayoade Fridaos tweeted.


Success! You are Register.
Thank you for Register, it means a lot to us, just like you do! We really appreciate you giving us a moment of your time.
Thank you for Register, it means a lot to us, just like you do! We really appreciate you giving us a moment of your time.


对一组值进行计算，并返回计算后的值，一般用来统计数据
累加所有行的值
计算ID=1的学生的的总分
select SUM(grade) as '总分' from score where student_id = 1;
计算所有行的平均值
计算ID=1的学生的的平均分
select AVG(grade) as '平均分' from score where student_id = 1;
select MAX(grade) 最高分,MIN(grade) 最低分 from score where student_id = 1;
select AVG(grade) as '平均分' 最低分 from score where student_id = 1;
select COUNT(*) from student;
select COUNT(1) from student;
select COUNT(name) from student;
select COUNT(NULL) from student;
分组查询就是按某列的值进行分组，相同的值分成一组，然后可以对此组内进行求平均、求和等计算
SELECT 列名,查询表达式
FROM <表名>
WHERE <条件>
GROUP BY <分组字段>
HAVING 分组后的过滤条件
ORDER BY 列名 [ASC,DESC]
LIMIT 偏移量,条数
SELECT列表中只能包含：
select student_id,avg(grade) from score group by student_id;
select course_id,max(grade) 平均分 from score group by course_id order by max(grade) desc
select province,gender,COUNT(*) from student group by province,gender
SELECT FROM <表名>
WHERE
GROUP BY {col_name|expr|position}
HAVING {col_name|expr|position}
ORDER BY {col_name|expr|position} [ASC|DESC]
LIMIT offset,row_count
统计学生人数超过1人的省份
select province,COUNT(*) from student group by province having COUNT(*)>1
不及格次数大于1次的学生
select student_id,COUNT(*) 不及格次数 from score where grade <60 group by student_id having COUNT(*)>1
>
大于>
= 大于等于SELECT ROUND(AVG(age),2) FROM student;
SELECT * from student WHERE age > (SELECT ROUND(AVG(age),2) FROM student)
= < <= = <> !=
年龄大于陕西省任何一位同学
SELECT * from student WHERE age > ANY (SELECT age FROM student WHERE province = '陕西省');
年龄大于陕西省某些同学
SELECT * from student WHERE age > SOME (SELECT age FROM student WHERE province = '陕西省');
年龄大于陕西省所有同学
SELECT * from student WHERE age > ALL (SELECT age FROM student WHERE province = '陕西省');
SELECT * FROM student where id in (SELECT distinct student_id from score);
SELECT * FROM student where EXISTS (SELECT distinct student_id from score where student.id = score.student_id )
使用ON关键字来设定连接条件，也可以使用WHERE来代替
显示左表和右表中符合条件的
SELECT * FROM student INNER JOIN score ON student.id = score.student_id;
显示左表的全部和右表符合条件的
SELECT * FROM student LEFT JOIN score ON student.id = score.student_id;
显示右表的全部和左表符合条件的
SELECT * FROM student RIGHT JOIN score ON student.id = score.student_id;
SELECT student.name,course.name,score.grade FROM score
INNER JOIN student ON student.id = score.student_id
INNER JOIN course ON course.id = score.course_id;
CREATE table category(
id int(11) PRIMARY KEY AUTO_INCREMENT NOT NULL,
name varchar(50),
parent_id int(11)
)
INSERT INTO category(id,name,parent_id)
VALUES (1,'数码产品',0),(2,'服装',0),(3,'食品',0),
(4,'iPad',1),(5,'李宁',2),(6,'康师傅',3);
SELECT c1.id,c1.name,COUNT(1)
FROM category c1 INNER JOIN category c2 ON c1.id = c2.parent_id
WHERE c1.parent_id = 0
GROUP BY c1.id;
SELECT c1.id,c1.name,p.name
FROM category c1 LEFT JOIN category p ON c1.parent_id = p.id
INSERT INTO category(id,name,parent_id)
VALUES
(7,'iPad',1),
(8,'李宁',2),
(9,'康师傅',3);
SELECT * FROM category c1 LEFT JOIN
(SELECT id,name from category GROUP BY name HAVING COUNT(1)>1) c2
ON c1.name = c2.name WHERE c1.id != c2.id
SELECT * FROM category c1
WHERE c1.name IN
(SELECT name from category GROUP BY name HAVING COUNT(1)>1)
AND c1.id NOT IN
(SELECT MIN(id) from category GROUP BY name HAVING COUNT(1)>1)
DELETE FROM category
WHERE name IN
(SELECT NAME FROM ( SELECT name from category GROUP BY name HAVING COUNT(1)>1) AS T1 )
AND id NOT IN
(SELECT id FROM (SELECT MIN(id) id from category GROUP BY name HAVING COUNT(1)>1) AS T2)
CREATE TABLE province(id int PRIMARY KEY AUTO_INCREMENT,name varchar(50))
INSERT INTO province(name) SELECT DISTINCT province FROM student;
UPDATE student INNER JOIN province ON student.province=province.name
SET student.province=province.id
ALTER TABLE student
CHANGE COLUMN `province` `province_id` int(11);


FilterReturns from textToFilter only those characters specified in filterText, in the order they were originally entered in textToFilter.filterText - the characters to preserve in the specified textIf filterText doesn’t have any characters, an empty string is returned. The Filter function is case-sensitive.Filter(“(408)555-1212”;“0123456789”) returns<PHONE_NUMBER>.Filter(“AaBb”;“AB”) returns AB.


[all packages]
[package ]
[class hierarchy]
[index]
public abstract class Drawable
(source file: Drawable.java)
java.lang.Object
|
+----Drawable
The pure class interface.
public abstract class Drawable
-
A drawable object is one which knows how to draw itself
using a Drawer object.
- Author:
- Alan Jeffrey
- Version: v1.0 1998/06/09
- See also:
- Drawer
- Drawable()
-
- draw(Drawer)
-
Draw it.
Drawable
public Drawable();
draw
public abstract void draw(Drawer d);
-
Draw it.
- Parameters:
- d - where to draw to.
[all packages]
[package ]
[class hierarchy]
[index]
Drawable.html


| 004:015 Khan | : |
And those of your women who commit illegal sexual intercourse, take the evidence of four witnesses from amongst you against them; and if they testify, confine them (i.e. women) to houses until death comes to them or Allah ordains for them some (other) way. |
| 004:015 Maulana | : |
And as for those of your women who are guilty of an indecency, call to witness against them four (witnesses) from among you; so if they bear witness, confine them to the houses until death takes them away or Allah opens a way for them. |
| 004:015 Pickthal | : |
As for those of your women who are guilty of lewdness, call to witness four of you against them. And if they testify (to the truth of the allegation) then confine them to the houses until death take them or (until) Allah appoint for them a way (through new legislation). |
| 004:015 Rashad | : |
Those who commit adultery among your women, you must have four witnesses against them, from among you. If they do bear witness, then you shall keep such women in their homes until they die, or until GOD creates an exit for them. |
| 004:015 Sarwar | : |
Those of your women who commit fornication, let four (Muslim) witness testify to their act. If there is sufficient testimony, confine them to their homes until they die, or until God provides a way for their freedom. |
| 004:015 Shakir | : |
And as for those who are guilty of an indecency from among your women, call to witnesses against them four (witnesses) from among you; then if they bear witness confine them to the houses until death takes them away or Allah opens some way for them. |
| 004:015 Sherali | : |
And such of your women who are guilty of any flagrant impropriety - call to witness four of you against them; and if they bear witness, then confine them to the houses until death overtakes them or ALLAH opens for them some other way. |
| 004:015 Yusufali | : |
If any of your women are guilty of lewdness, Take the evidence of four (Reliable) witnesses from amongst you against them; and if they testify, confine them to houses until death do claim them, or Allah ordain for them some (other) way. |
Concepts/Themes Covered: العمل > العمل الطالح > الفاحشة والزنى > الفحشاء Action(Work)> Bad Deeds> Adultry and Atrocity>Atrocity الإنسان والعلاقات الأخلاقية > الأخلاق الذميمة > الفجور Man and The Moral Relations>The Dispraised Morals>Immorality
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


 Leave it to the British to be snobby enough to reject the letter "s" in all its forms. It doesn't make sense, but neither do any of the movies in the James Bond series.  Even the most suave amongst us would have sex with an atomic bomb and defuse three beautiful women by mistake every once in awhile.
This was Timothy Dalton's second and final appearance as 007 and good riddance to him, I say. Sure, he's not a bad Bond, but he's got a certain sliminess about him I just don't like. Dalton outstayed his welcome after only two movies, whereas I didn't start to get sick of Roger Moore until the OCTOPUSSY period. Let's face it, though. Any rugged-looking white guy with dark hair could do a decent James Bond. Hell, people would even pay to see Regis Philbin in the role. And Kathie Lee could play Octocody. Just a thought...
Even with Dalton at the helm, LICENCE TO KILL is still a good Bond outing, for the fact that it so drastically departs from the tried-and-true 007 formula used in the seventeen movies before it. Here, Bond is on a personal mission to avenge the murder of a CIA friend and his wife. Bond is all alone this time, his "licence" to kill having been revoked by the British secret service, and must track down the Mexican drug lord who ordered the double execution.
Locating the villain in a Bond movie is never hard. Just look for the biggest exotic mansion around. Bond finds the place and, as usual, is held captive for a considerable percentage of the movie (something like 22.7%, but don't quote me on that). He also invites the drug lord's girlfriend to a fiesta in his pantalones. That's one of Dalton's two conquests in LICENCE TO KILL... See, that right there is how you know he wasn't meant to play James Bond. The other Bonds get at least a trio of ladies per movie, even George Lazenby in ON HER MAJESTY'S SECRET SERVICE.
LICENCE TO KILL clocks in as one of the better entries in the series, with a visually-stimulating-yet-down-to-earth climax, a more gritty feel to it and an entirely new direction for the Bond series. Bond is self-motivated and independent, with a little help from his friend Q. (who actually joins Bond in the mission toward the end) and his unusually competent girlfriend Pam (who also functions as a low- calorie cooking spray). It also reminds us what the 80's were all about by throwing in cocaine and Wayne Newton. You have to have the cocaine to tolerate Newton.
Visit the Movie Critic at LARGE website at http://www.missouri.edu/~c667778/movies.html
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


Civil Law
Contractual Law
Negotiation
Management
Germany
Univerbackity of Erlangen-Nurnberg, Nurnberg, Germany, backecond backtate Exam (JD) Jan 2012
German
Englibackh
French
Turkibackh (converbackational)
Lex International law Firm, Miami, Florida, UbackA, 8/2016 – prebackent, Juribackt + German Attorney (Contractback and Corporate Law, Immigration, real ebacktate).
backixt Rent a Car, LLC, Fort Lauderdale, UbackA, 07/2013-11/2015, Contract and Concebackbackion Manager (bubackinebackback, compliance, contractback, corporate).
Drager & Kollegen Law Firm, Bamberg, Germany, 11/2012-06/2013, Attorney at Law (family, employment, inheritance, corporate law and litigation.
Cenanovic Law Firm, Bamberg, Germany, 09/2012-10/2012, Attorney at Law (employment, civil law and litigation).
backparkabackbacke, Nurnberg, Germany, 01/2011-03/2011, Referendar (foreclobackure law).
Lex International Law Firm, P.A. Miami, Florida, UbackA, 01/2011 – 03/2011, Referendar (immigration, corporate law, ebacktate and trubackt, real ebacktate).
Kreuzer & Coll, Law Firm, Nurnberg, Germany, 03/2010-12/2010, Referendar (real ebacktate).
Thiback iback a great place to introduce your company or project and debackcribe what you do. Thiback about page featureback general company information, employee bioback, and other helpful elementback.
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The functions described in this section do PCA analysis and compression for a set of 8-bit images that may not fit into memory all together. If your data fits into memory and the vectors are not 8-bit (or you want a simpler interface), use cvCalcCovarMatrix, cvSVD and cvGEMM to do PCA
Calculates covariance matrix for group of input objects
void cvCalcCovarMatrixEx( int nObjects, void* input, int ioFlags, int ioBufSize, uchar* buffer, void* userData, IplImage* avg, float* covarMatrix );
The function cvCalcCovarMatrixEx calculates a covariance matrix of the input objects group using previously calculated averaged object. Depending on ioFlags parameter it may be used either in direct access or callback mode. If ioFlags is not CV_EIGOBJ_NO_CALLBACK, buffer must be allocated before calling the function.
Calculates orthonormal eigen basis and averaged object for group of input objects
void cvCalcEigenObjects( int nObjects, void* input, void* output, int ioFlags, int ioBufSize, void* userData, CvTermCriteria* calcLimit, IplImage* avg, float* eigVals );
The function cvCalcEigenObjects calculates orthonormal eigen basis and the averaged object for a group of the input objects. Depending on ioFlags parameter it may be used either in direct access or callback mode. Depending on the parameter calcLimit, calculations are finished either after first calcLimit.maxIters dominating eigen objects are retrieved or if the ratio of the current eigenvalue to the largest eigenvalue comes down to calcLimit.epsilon threshold. The value calcLimit -> type must be CV_TERMCRIT_NUMB, CV_TERMCRIT_EPS, or CV_TERMCRIT_NUMB | CV_TERMCRIT_EPS . The function returns the real values calcLimit -> maxIter and calcLimit -> epsilon .
The function also calculates the averaged object, which must be created previously. Calculated eigen objects are arranged according to the corresponding eigenvalues in the descending order.
The parameter eigVals may be equal to NULL, if eigenvalues are not needed.The function cvCalcEigenObjects uses the function cvCalcCovarMatrixEx.
Calculates decomposition coefficient of input object
double cvCalcDecompCoeff( IplImage* obj, IplImage* eigObj, IplImage* avg );
The function cvCalcDecompCoeff calculates one decomposition coefficient of the input object using the previously calculated eigen object and the averaged object.
Calculates all decomposition coefficients for input object
void cvEigenDecomposite( IplImage* obj, int nEigObjs, void* eigInput, int ioFlags, void* userData, IplImage* avg, float* coeffs );
The function cvEigenDecomposite calculates all decomposition coefficients for the input object using the previously calculated eigen objects basis and the averaged object. Depending on ioFlags parameter it may be used either in direct access or callback mode.
Calculates object projection to the eigen sub-space
void cvEigenProjection( int nEigObjs, void* eigInput, int ioFlags, void* userData, float* coeffs, IplImage* avg, IplImage* proj );
The function cvEigenProjection calculates an object projection to the eigen sub-space or, in other words, restores an object using previously calculated eigen objects basis, averaged object, and decomposition coefficients of the restored object. Depending on ioFlags parameter it may be used either in direct access or callback mode.
The functions of the eigen objects group have been developed to be used for any number of objects, even if their total size exceeds free RAM size. So the functions may be used in two main modes.
Direct access mode is the best choice if the size of free RAM is sufficient for all input and eigen objects allocation. This mode is set if the parameter ioFlags is equal to CV_EIGOBJ_NO_CALLBACK . In this case input and output parameters are pointers to arrays of input/output objects of IplImage* type. The parameters ioBufSize and userData are not used.In order to support embedded models the user must define structures to represent 1D HMM and 2D embedded HMM model.
Embedded HMM Structure
typedef struct _CvEHMM { int level; int num_states; float* transP; float** obsProb; union { CvEHMMState* state; struct _CvEHMM* ehmm; } u; } CvEHMM;
For representation of observations the following structure is defined:
Image Observation Structure
typedef struct CvImgObsInfo { int obs_x; int obs_y; int obs_size; float** obs; int* state; int* mix; } CvImgObsInfo;
Creates 2D embedded HMM
CvEHMM* cvCreate2DHMM( int* stateNumber, int* numMix, int obsSize );
The function cvCreate2DHMM returns the created structure of the type CvEHMM with specified parameters.
Releases 2D embedded HMM
void cvRelease2DHMM(CvEHMM** hmm );
The function cvRelease2DHMM frees all the memory used by HMM and clears the pointer to HMM.
Creates structure to store image observation vectors
CvImgObsInfo* cvCreateObsInfo( CvSize numObs, int obsSize );
The function cvCreateObsInfo creates new structures to store image observation vectors. For definitions of the parameters roi, dctSize, and delta see the specification of the function cvImgToObs_DCT.
Releases observation vectors structure
void cvReleaseObsInfo( CvImgObsInfo** obsInfo );
The function cvReleaseObsInfo frees all memory used by observations and clears pointer to the structure CvImgObsInfo .
Extracts observation vectors from image
void cvImgToObs_DCT( IplImage* image, float* obs, CvSize dctSize, CvSize obsSize, CvSize delta );
The function cvImgToObs_DCT extracts observation vectors, that is, DCT coefficients, from the image. The user must pass obsInfo.obs as the parameter obs to use this function with other HMM functions and use the structure obsInfo of the CvImgObsInfo type.
Calculating Observations for HMM
CvImgObsInfo* obs_info; ... cvImgToObs_DCT( image,obs_info->obs, //!!! dctSize, obsSize, delta );
Performs uniform segmentation of image observations by HMM states
void cvUniformImgSegm( CvImgObsInfo* obsInfo, CvEHMM* hmm );
The function cvUniformImgSegm segments image observations by HMM states uniformly (see Initial Segmentation for 2D Embedded HMM for 2D embedded HMM with 5 superstates and 3, 6, 6, 6, 3 internal states of every corresponding superstate).
Initial Segmentation for 2D Embedded HMM
Segments all observations within every internal state of HMM by state mixture components
void cvInitMixSegm( CvImgObsInfo** obsInfoArray, int numImg, CvEHMM* hmm );
The function cvInitMixSegm takes a group of observations from several training images already segmented by states and splits a set of observation vectors within every internal HMM state into as many clusters as the number of mixture components in the state.
Estimates all parameters of every HMM state
void cvEstimateHMMStateParams( CvImgObsInfo** obsInfoArray, int numImg, CvEHMM* hmm );
The function cvEstimateHMMStateParams computes all inner parameters of every HMM state, including Gaussian means, variances, etc.
Computes transition probability matrices for embedded HMM
void cvEstimateTransProb( CvImgObsInfo** obsInfoArray, int numImg, CvEHMM* hmm );
The function cvEstimateTransProb uses current segmentation of image observations to compute transition probability matrices for all embedded and external HMMs.
Computes probability of every observation of several images
void cvEstimateObsProb( CvImgObsInfo* obsInfo, CvEHMM* hmm );
The function cvEstimateObsProb computes Gaussian probabilities of each observation to occur in each of the internal HMM states.
Executes Viterbi algorithm for embedded HMM
float cvEViterbi( CvImgObsInfo* obsInfo, CvEHMM* hmm );
The function cvEViterbi executes Viterbi algorithm for embedded HMM. Viterbi algorithm evaluates the likelihood of the best match between the given image observations and the given HMM and performs segmentation of image observations by HMM states. The segmentation is done on the basis of the match found.
Segments observations from all training images by mixture components of newly assigned states
void cvMixSegmL2( CvImgObsInfo** obsInfoArray, int numImg, CvEHMM* hmm );
The function cvMixSegmL2 segments observations from all training images by mixture components of newly Viterbi algorithm-assigned states. The function uses Euclidean distance to group vectors around the existing mixtures centers.


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Ex-Barcelona star hints at return to the Camp Nou next summer
by HarigovindAfter having left Barcelona for Zenit Saint Petersburg earlier this summer, Brazilian winger Malcom has hinted that he may return to the La Liga defending champions next summer.
In a recent interview with RMC Sport, Malcom revealed that he has been getting messages from Barcelona fans, asking him to return to the Camp Nou.
“I can say that I receive messages about returning to Barcelona,” he said, before adding:
“Every time the coach gave me an opportunity to play, I did my job and I think I did it well. That’s why Barcelona fans love me.”
The former Bordeaux star created quite a lot of controversy ahead of the 2018-19 season, as he initially agreed to join AS Roma – and just before the deal was agreed to by both Bordeaux and the Serie A side, Barcelona hijacked him and took him to Spain.
He then made the move to Zenit St. Petersburg ahead of the ongoing 2019-20 season, after making 24 appearances and scoring four goals for the Catalans across various competitions.
Malcom also made it clear that he does not regret the fact that he had to leave the Blaugrana.
“No, I don’t regret it,” he said, before adding:
“I’m young and I want to play anywhere, because I like football. Zenit are the team who gave me the opportunity to play football, so I don’t regret it.”
Quotes via Marca.


Our Sundance also accepts support in the form of money donations. Each year, we rely on the generosity and accountibility of our sundancers, helpers, community members, and our extended families to provide enough support to keep the Sundance going. You can donate to the Eagle Sundance fund securely through PayPal via the "Donate" button below. 100% of these collected donations will be used for Sundance related costs and supplies. This PayPal donation button is intended solely for use by our Eagle Sundance family and its supporters as a way to simplify the process of donating to our Sundance. Miigwech (Thank you) for your support!
Lodging:
Bad River Lodge & Casino:
Address: 73370 US-2, Ashland, WI 54806
Phone:<PHONE_NUMBER>
Open 24 hours
AmericInn Hotel:
Address: 3009 Lake Shore Dr E, Ashland, WI 54806
Phone:<PHONE_NUMBER>
Crest Motel:
Address: 115 Sanborn Ave, Ashland, WI 54806
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Trust the Sharrow: It's the answer to everything from high-speed rail ...
Aug 4, 2010 . (1) Just upgrade the CSX A-line to 90mph and send trains through Selma .  Pizza, Sun Drop, B105.7 Soft Rock, Dole, Magic Morning Bakery, Yahoo! . Amanda Page Cornett :: Photos - ReverbNation, Purina Dog Chow, CSX, 104.3 KHiTS .  Answers, Mozila Firefox, Material Girl Collection, Priceline.com, Gaylord .
http://www.facebook.com/hoosier1956
Ohio Poacher Notches Record Fine for Taking Trophy Buck | Field ...
Jun 3, 2011 . Hate to see what kind of fine a kid would pay for putting a penny on a CSX railroad track nowdays with the Department of Homeland Security .
http://www.fieldandstream.com/blogs/whitetail-365/2011/06/ohio-poacher-notches-record-fine-taking-trophy-buck
EYE ON MIAMI: 2012-12-30
Jan 5, 2013 . Walgreens Drugstore Sucks. .  And, worse when . How is this for an answer<EMAIL_ADDRESS>.
http://eyeonmiami.blogspot.com/2012_12_30_archive.html
View Guestbook - Fallen Flag Railroads of New Jersey - Railfan.net
Favorite RR's: BNSF, CP, CN, CSX, KCS Woodland . Carl Timberman < cdtimberman -=AT=- yahoo.com> Favorite RR's: . Henry <spamfighter -=AT=- nospam.spammers.suck.org> Favorite . Great site! Do you answer e-mail questions?
http://raildata.railfan.net/guest/visitors.html
PCH, Affordable Shelby Edition: 1986 GLHS or 1989 CSX-VNT?
Aug 14, 2008 . Today we've got the life sentence answer for those who want to drive some lunatic . But if that yahoo with the CSX ($6,500 for that? . Since they both sucked...the square expendible easily smashable to a return of function .
http://jalopnik.com/400415/pch-affordable-shelby-edition-1986-glhs-or-1989-csx+vnt


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Welcome, I’m Tasha Marsh and I offer Mentoring and a Listening Service in South Somerset.
Keep updated by joining us on Facebook, click on the link above or search ‘Tasha Marsh Mentoring and Listening Service’ on Facebook and like the page.
Welcome, I’m Tasha Marsh and I offer Mentoring and a Listening Service in South Somerset.
Keep updated by joining us on Facebook, click on the link above or search ‘Tasha Marsh Mentoring and Listening Service’ on Facebook and like the page.


Optional: Newline separated list of AWS EB Environment url, or CNAMEs for the Application (e.g.: "myapp-prod-env.elasticbeanstalk.com").
When set and Environment Name exists, it will trigger a UpdateEnvironment Call when the Application Version is created.
If not set, then all environments under the Application will be updated together.


It is shown an environment which is an extended version of the "Waterworld" example of the Stanford University CS group – more specific by Andrej Karpathy. You'll find multiple pages, each with different content.
The content of this website is for educational purposes only.
This project shows the simulation environment, the gained pre-trained agents, an explanation of the whole simulation and project construction, hyperparameters and the presentation of the simulation results. It is also shown how the DQN-Method is working in principle. To make yourself an impression the source code of all dependent project modules please see the following section "Dependencies".
The MIT License Copyright (c) 2017 Menno van Rahden
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
 IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


| Module | ActionController::HttpAuthentication::Basic |
| In: |
/usr/lib/ruby/gems/1.8/gems/actionpack-3.0.0.beta4/lib/action_controller/metal/http_authentication.rb
|
Makes it dead easy to do HTTP Basic authentication.
Simple Basic example:
class PostsController < ApplicationController USER_NAME, PASSWORD = "dhh", "secret" before_filter :authenticate, :except => [ :index ] def index render :text => "Everyone can see me!" end def edit render :text => "I'm only accessible if you know the password" end private def authenticate authenticate_or_request_with_http_basic do |user_name, password| user_name == USER_NAME && password == PASSWORD end end end
Here is a more advanced Basic example where only Atom feeds and the XML API is protected by HTTP authentication, the regular HTML interface is protected by a session approach:
class ApplicationController < ActionController::Base before_filter :set_account, :authenticate protected def set_account @account = Account.find_by_url_name(request.subdomains.first) end def authenticate case request.format when Mime::XML, Mime::ATOM if user = authenticate_with_http_basic { |u, p| @account.users.authenticate(u, p) } @current_user = user else request_http_basic_authentication end else if session_authenticated? @current_user = @account.users.find(session[:authenticated][:user_id]) else redirect_to(login_url) and return false end end end end
In your integration tests, you can do something like this:
def test_access_granted_from_xml get( "/notes/1.xml", nil, :authorization => ActionController::HttpAuthentication::Basic.encode_credentials(users(:dhh).name, users(:dhh).password) ) assert_equal 200, status end
Simple Digest example:
require 'digest/md5' class PostsController < ApplicationController REALM = "SuperSecret" USERS = {"dhh" => "secret", #plain text password "dap" => Digest:MD5::hexdigest(["dap",REALM,"secret"].join(":")) #ha1 digest password before_filter :authenticate, :except => [:index] def index render :text => "Everyone can see me!" end def edit render :text => "I'm only accessible if you know the password" end private def authenticate authenticate_or_request_with_http_digest(REALM) do |username| USERS[username] end end end
NOTE: The authenticate_or_request_with_http_digest block must return the user‘s password or the ha1 digest hash so the framework can appropriately
hash to check the user's credentials. Returning +nil+ will cause authentication to fail. Storing the ha1 hash: MD5(username:realm:password), is better than storing a plain password. If the password file or database is compromised, the attacker would be able to use the ha1 hash to authenticate as the user at this +realm+, but would not have the user's password to try using at other sites.
On shared hosts, Apache sometimes doesn‘t pass authentication headers to FCGI instances. If your environment matches this description and you cannot authenticate, try this rule in your Apache setup:
RewriteRule ^(.*)$ dispatch.fcgi [E=X-HTTP_AUTHORIZATION:%{HTTP:Authorization},QSA,L]
# File /usr/lib/ruby/gems/1.8/gems/actionpack-3.0.0.beta4/lib/action_controller/metal/http_authentication.rb, line 127 127: def authenticate(request, &login_procedure) 128: unless request.authorization.blank? 129: login_procedure.call(*user_name_and_password(request)) 130: end 131: end
# File /usr/lib/ruby/gems/1.8/gems/actionpack-3.0.0.beta4/lib/action_controller/metal/http_authentication.rb, line 145 145: def authentication_request(controller, realm) 146: controller.headers["WWW-Authenticate"] = %(Basic realm="#{realm.gsub(/"/, "")}") 147: controller.response_body = "HTTP Basic: Access denied.\n" 148: controller.status = 401 149: end
# File /usr/lib/ruby/gems/1.8/gems/actionpack-3.0.0.beta4/lib/action_controller/metal/http_authentication.rb, line 137 137: def decode_credentials(request) 138: ActiveSupport::Base64.decode64(request.authorization.split(' ', 2).last || '') 139: end
# File /usr/lib/ruby/gems/1.8/gems/actionpack-3.0.0.beta4/lib/action_controller/metal/http_authentication.rb, line 141 141: def encode_credentials(user_name, password) 142: "Basic #{ActiveSupport::Base64.encode64("#{user_name}:#{password}")}" 143: end


data class CommandAndState
Return structure for OwnableState.withNewOwner
<init> |
Return structure for OwnableState.withNewOwner CommandAndState(command: CommandData, ownableState: OwnableState) |
command |
val command: CommandData |
ownableState |
val ownableState: OwnableState |


Event Location:
Microsoft Office
3201 William Nicol Drive
Bryanston, Gauteng, South Africa
Abstract:
SharePoint has become the defacto EIM tool for many large organisations and this comes with a huge responsibility for SQL DBA’s and BI consultants alike. SQL is the heart and soul of any SharePoint Farm and in this session we will be focussing on: • What architectural considerations there are for SQL from SharePoint • Real-world SQL requirements for SharePoint • Simple tips and tricks for SQL before deploying SharePoint • Best practice scenario’s for SQL pertaining to SharePoint Invariably, SharePoint Architects have to co-exist with SQL DBA’s without having to argue and or debate what is required. DBA’s armed with the items listed above will have a better understanding of SharePoint and will also be able to optimize the performance of SharePoint DB’s so as to ensure better overall performance.
Speaker(s): Alistair Pugin,
Abstract:
How often have our SQL Servers been bogged down with a myriad of users issuing lengthy and poorly constructed or poorly performing queries against our tables and views.More often than not,nearly bringing our systems to their knees.Nowhere is this truer than within the financial world where heavy number crunching is par for the course.This beginners to intermediate level hands-on presentation is aimed at the SQL Server developer and business analyst alike and will show the attendee how we had managed to eliminate 90 % of our poorly performing queries by creating a data access layer which provides our end users with a suite of well developed and tuned SQL Server FUNCTIONS and UDT's with which to render their data.
Speaker(s): Steve Simon,
Abstract:
We discuss a list of costly mistakes, and their solutions, made during the design and building of the ETL process. Recommendations to avoid these mistakes are covered as well as a checklist to use to create reliable ETL solutions.
Speaker(s): Luis de Sousa,
Abstract:
This is not for those that are "Gettings Things Done" and already know the "End Game". It is also not for those that are not interested in Professional Development discussions and just want to listen to hard-core technical. It is for those that appreciate being challenged in where they are currently in their professional career and where they are going. It does try to address the decisions "ground rules" required to becoming a "Senior SQL Rockstar" without any regrets and blank spaces in your resume.
Speaker(s): Howard Diesel,
Abstract:
Are you a developer struggling to get maximum performance from your queries? Are you a DBA struggling to get maximum performance from your server? If so then join this session to see Sean Pearce tuning some real life queries and configuring the server accordingly. This session is full of great tips and handy techniques to apply to your code.
Speaker(s): Sean Pearce,
Abstract:
In this session we will cover • Internals of Tabular (and why you should care) • Good and Bad Data Modelling Patterns. • Identifying and fixing bad execution plans.
Speaker(s): Mark White,
Abstract:
In this session we will explore a number of basic data modelling and analytical problems and how to use DAX to solve them. While this session will not make you a DAX Jedi It should provide you with a good understanding of the fundamentals of the language.
Speaker(s): Matt Horn,
Abstract:
This session will explore several of the new SQL Server 2014 features and how they could benefit existing and new BI solutions. This includes features that are typically considered as OLTP feature such as In-memory tables (Hekaton). The session will include a demo that will consider features and the impact they will have on data warehouse load performance, query performance, storage and maintenance. I will be using Windows Azure VMs to do the demo.
Speaker(s): Marius Van Schalkwyk,
Abstract:
We dive into the common knowledge subjects and principles that we already know about but forget to use or just blatantly ignore, Delta management, Project recovery, Best and Worst practice and more. Session is recommended for the intermediate to advanced but the beginner will also gain from this.
Speaker(s): Andreas Bergstedt,
Abstract:
The new SQL 2014 In-Memory Optimized Tables for OLTP is an exiting technology, but with a very specific and focused set of use-cases. This demo will outline their high level functioning and some real word examples.
Speaker(s): Frikkie Venter,
Abstract:
In this session we will cover getting started with SQL Server extended event. Scripting out events.
Speaker(s): Jody Roberts,
Abstract:
TBC
Speaker(s): Gary Hope,
Abstract:
Keynote address
Speaker(s): Franco Rothner,
Abstract:
As a DBA do you control what is utilising the resources within Sql or do the the Applications? Learn how to setup and configure Sql Server Resource Governor, and how it can be used to determine what application or users are hogging the resources and how to limit those that are impacting on the overall system performance.
Speaker(s): Martin Phelps,
Abstract:
TBC
Speaker(s): Bhavesh Lala,
Abstract:
SQL Server 2014: With the vast amounts of data in today’s business warehouses, there has been increased demand on the Business Intelligence solution developer to produce more complex and all inclusive reporting facilities. More complexity, coupled with being all inclusive tends to yield more points of failure.In this hands on presentation we shall be examining new and innovative ways of rendering the required data in some unusual ways.
Speaker(s): Steve Simon,
Abstract:
Columnstore index is an enterprise feature that was introduced in SQL Server 2012 for the purposes of improving the query response on T-SQL queries against OLAP systems. In this session we will look at the initial (SQL Server 2012) implementation of columnstore indexing and how it has been improved in SQL Server 2014.
Speaker(s): Sifiso Ndlovu,
Abstract:
Learn about Microsoft Azure’s relational database service, SQL Database. I will demonstrate key architectural patterns to showcase how customers are achieving mission criticality in the cloud. The focus will be on how and when to apply the new capabilities across business continuity and performance into the design of modern mission-critical applications.
Speaker(s): Brent Samodien,
Abstract:
If there’s one thing that we, as SQL developers, don’t do, it’s use enough transactions. Transactions are critical when multiple changes need to be made entirely or not at all, but even given that it’s rare to see transactions used at all in most production code. In this session, we’ll look at what transactions are and why we should use them. We’ll explore the effects transactions have on locking and the transaction log.
Speaker(s): Gail Shaw,
This is a list of speakers from the XML Guidebook records. The details and URLs were valid at the time of the event.
Matt Horn is a senior consultant with Aphelion software and a regular speaker at SQLSaturdays and other community events. He has been the co lead of the BIDN BI user group in Johannesburg and an active member of SQLCape and the JHB SQL Usergroup.
LinkedIn: https://za.linkedin.com/pub/sean-pearce/2/9b5/914
Contact: http://thesqlguy.blogspot.com/
Sean Pearce is a SQL Server consultant with a background in application development. Initially he was exposed to SQL Server 6.5 as a developer but by the time SQL Server 2000 had been released he had stepped into a SQL Server focused role. His understanding of the architecture of SQL Server allows him to excel at performance tuning and problem solving. Sean is actively involved in the SQL Server community, has spoken at PASS SQLSaturday and presents regularly to the Jhb SQL Server User Group.
Mark is a delivery-focused IT manager, with over 19 years multi-disciplined experience spanning banking, short-term insurance, taxation, healthcare, pharmaceutical, broadcast TV, streaming media, manufacturing and retail. Specialties:Leadership Management, Business Intelligence Solutions, Product Training, Programme Management, Enterprise systems architecture.
Information Technology and Services Consultant and Contractor, Sambe Consulting (Owner
none
Contact: http://www.karabina.co.za
I'm a Business Intelligence Solutions Architect specializing in the Microsoft technology stack. I have been in the Business intelligence space for over 9 years now, most of which I spent as a consultant. I specialize in solving business problems with clean and simple technology solutions. I enjoy mentoring and coaching colleagues and sharing knowledge on different platforms. I love spending time with my family, adventure racing, and studying. I just started with my P.hD in Data Warehousing.
LinkedIn: https://www.linkedin.com/in/alistairpugin/
Contact: http://2guysandsharepoint.co.za
Alistair has worked in various capacities in multiple verticals from retail – manufacturing to government, spanning 50 to 50000 users utilizing all aspects of pure Enterprise Information Management. His current position as an Office Servers and Services MVP in South Africa, provides him with a mechanism to assist companies with architecting their SharePoint environment using "best of breed", proven methodologies to foster innovation and growth through an ECM framework.
LinkedIn: https://www.linkedin.com/in/sifiso-w-ndlovu-89239a14
Contact: http://blogs.selectsifiso.com/
I am a certified Microsoft professional with a Master’s degree in IT Management from the University of Johannesburg. I specializes on a range of enterprise and consumer technologies using open source and proprietary software. I am a member of the Johannesburg SQL User Group wherein I have made several presentations on User Group Meetings and SQLSaturday sessions. I have written for a number of publications including SQLShack.com and SQLServerCentral.com.
LinkedIn: http://za.linkedin.com/pub/jody-roberts/7/b29/193/Edit
Contact: http://JodyWP.wordpress.com
Jody Roberts is a Microsoft Data Platform MVP based in Cape Town, South Africa. He specializes in SQL Server architecture, disaster recovery (DR), and server optimization. Jody serves as a PASS Regional Mentor responsible for the Middle East amp; Africa, Chapter Lead of the SQLCape user group, and Co-Lead of the PASS Cloud Virtual Chapter. Jody is a Principal Consultant at Northern Data.
Cloud Data and AI Solution Architect at Microsoft South Africa
LinkedIn: http://www.linkedin.com/in/stephenrsimon/
Contact: http://www.sqlservercentral.com/blogs/simon_says/
Steve Simon is a Database Solutions Architect with Business Knowledge Services Inc. He has been involved with database design and analysis for over 35 years. Steve has presented papers at numerous PASS Summits and PASS SQL Rallies. He is also regular presenter on the SQLSaturday circuit and he is a contributor on SQLShack.com
Contact: http://www.ensobyte.com
Passionate technologist who enjoys providing leading-edge Information Technology services to medium and enterprise clients in a wide variety of sectors including retail, public, financial, media and communications, energy and the professional services industry. I create value by bridging the gap between business and technology through a focus on strategy; people, processes, information and communication technology.
Contact: http://sqlinthewild.co.za
Gail Shaw is a Database Specialist focusing on database performance tuning and database recovery, with a particular interest in topics such as indexing strategies, execution plans, and writing T-SQL code that performs well and scales gracefully. Gail holds a Microsoft Certified Master certification for SQL Server 2008 and is a Data Platform MVP. She's a frequent poster on the SQLServerCentral forums, a Pluralsight author, writes articles for both SQLServerCentral.com and Simple-Talk.com, and has spoken at SQLSaturdays, SQL Bits and at the PASS Community Summit. Gail has been responsible for extending the lifespan of many an application, by performance-tuning their databases and providing technical guidance on all things SQL Server related.
LinkedIn: http://www.linkedin.com/in/stephenrsimon/
Contact: http://www.sqlservercentral.com/blogs/simon_says/
Steve Simon is a Database Solutions Architect with Business Knowledge Services Inc. He has been involved with database design and analysis for over 35 years. Steve has presented papers at numerous PASS Summits and PASS SQL Rallies. He is also regular presenter on the SQLSaturday circuit and he is a contributor on SQLShack.com
Contact: http://www.modelwaresystems.com
Love working with Data in all it different forms and shapes: from business applications to data warehousing and Data management services. Have spent the last 15 years focussing specifically on business data development. Really enjoy the high-end data analysis and reconciliation. Prior to focussing on data development , technical application development on all platforms from Mainframe to embedded systems.
Technical Manager: Business Intelligence at EOH Microsoft Services
LinkedIn: http://za.linkedin.com/in/luisdza
Contact: http://www.luisdesousa.co.za
Consult to large financial institutions in South Africa providing Business Intelligence and Analysis insight.
LinkedIn: http://za.linkedin.com/pub/andreas-bergstedt/10/119/274/
Contact: https://blog.bi360.ml
24+ Years in the IT Sector, Last 12 years in the BI Space, Passionate about knowing and understanding data and what business actually want from their information.
LinkedIn: http://www.linkedin.com/in/phelpsm
Martin Phelps is database architect at MiX Telematics. Specialising in Solution Architecture across their OLTP and DW databases. With 20 years of in-the-trenches experience with Sql Server he has provided solutions using Sql Server since version 4.2. Has previously done work for Insurance, ICT, Marketing and Mining companies.
The following is a list of sponsors that helped fund the event.