17 02-20 improving the counting method to fill the gender gap (bis). (copie)

DATA MINING AND GENDER GAPDATA MINING AND GENDER GAP
A FUNDAMENTAL ISSUE FOR METRICS. THE DATA MINING
WITH THE MODELS AND PATERNS ARE RESOLVING IT
Source : Business Innovation Research Development

ORDER, CAHOS AND COMPLEXITY
« Selon l’acception héritée de l’art militaire, la stratégie se caractérise par la planification et le calcul. Elle vise à rassurer le décideur en réduisant
l’incertitude quant à l’issue de ses décisions. Elle implique l’évaluation des risques d’erreur et par suite d’échec attachés à toute décision. Le risque étant
au cœur de la question stratégique, la stratégie peut elle-même être comprise comme un moyen de le neutraliser. Face au «règne de l’incertitude et du
désordre, elle correspond à une tentative de conjurer l’incertitude et de soumettre les événements en rapprochant le plus possible l’action d’une pensée
rationalisante et modélisatrice »1. Il en va de même en matière de stratégies d’entreprise. »
(Jean-Paul Petitimbert, Entre l’ordre et le chaos: la précaritécomme stratégie d’entreprise ). Actes
Sémiotique n°116 - Analyses sémiotiques
"According to the understanding inherited from military art, strategy is characterized by planning and calculation. It aims to reassure the decision-maker by
reducing uncertainty about the outcome of his decisions. It involves the evaluation of the risks of error and consequently of failure attached to any decision.
Since risk is at the heart of the strategic question, strategy can itself be understood as a means of neutralizing it. Faced with the "reign of uncertainty and
disorder, it corresponds to an attempt to ward off uncertainty and to subdue events by bringing the action as close as possible to rationalizing and modeling
thought" 1. The same goes for business strategies. "

SUSTAINABLE DEVELOPMENT GOALSUSTAINABLE DEVELOPMENT GOAL
NUMBER 5 (SDG5)NUMBER 5 (SDG5)
●
SDG 5: Achieve gender equality and empower all women and
girls

https://www.unwomen.org/en/news/in-focus/women-and-the-sdgs/sdg-5-gender-equality
UNITED NATIONS WOMEN (UN WOMEN)

Experience de Data Mining (DM)Experience de Data Mining (DM)
models Clusters*
(*) patterns
http://cedric.cnam.fr/~saporta/DM.pdf
DATA INFORMATION KNOWLEDGE
PRE TREAMENT ANALYSIS
DM
Source auhor adapted from
Gilbert SaportaChaire de Statistique Appliquée & CEDRIC, CNAM, 292 rue Saint Martin, F-75003 Paris

VISUAL COUNTINGVISUAL COUNTING
●
IT SHOWS DIFFICULTIES DUE TO THE ARITHMETIC OF COUNTING 1 BY
1, THEN 2 BY 2...IF YOU ARE NOT USED TO COUNT WITH
INCREMENTED NUMBERS WITH IRREGULAR STEPS.

Photo credit : internet
A COMPLEX CROWD MANAGEMENT

D) Counting crowdflow
C) Crowd turbulence is a typical reason for crowd disasters, resultingfrom
pushing, mass-panic, stampede or crowd crushes, and causing anoverall
loss of control (Helbing et al., 2014)
B) In current decades, human population in the world is increas-ing
dramatically. This growth, as a result from movement andurbanization
worldwide, has indirectly made crowd phenomenonincreasing. Large
gatherings of people can be observed at coveredareas such as in building
halls, airports and stadiums as well as inopen areas like at walkways,
parks, sport events and publicdemonstration
A) Intelligent visual surveillance at area under observation is extensively
studied in recent years by computer vision researchers (Shah et al., 2007;
Hu et al., 2004)
APPLICATIONS OF VISUAL COUNTING

HOW DOES THE BRAIN SEES MATH ?
https://www.sciencedirect.com/science/article/pii/S0952197615000081#f0030

If children are encouraged to look at maths more visually, it could actually make them smarter! Whether
we like it or not, the brain processes numbers as images representing the space and quantity.
https://www.indiatoday.in/education-today/featurephilia/story/visual-maths-finger-counting-
975227-2017-05-04 Source : Business Innovation Research Development
THE BRAIN PROCESSES
NUMBERS AS IMAGES

RISK ISSUE
●
TRAINING PROBLEM TO COUNT VISUALLY A HUGE NUMBER (CROWD)
HIGHLY RISKY (DUE TO PRODUCTION PATTERNS) WITH VARIABILITY
AND AMBIGUITY
‘’All experiments on real crowd videos show the effectiveness of the proposed system.
However, the drawback of this approach is that when system initial‫׳‬s setup is changed
a new training procedure is required.’’
https://www.sciencedirect.com/science/article/pii/S0952197615000081#f0030

THE 2 STAGE PROJECTTHE 2 STAGE PROJECT
Project Modeling :
Prototype business
model, and core
model.
Dec. 2019 15.01.20 15.01.20
Project Modeling : Improving
the prototype business model
(counting student in the reading
room (and not with the
prototype model), in order to
improve the calibration of the
model.
17-02-20
DATA MINING

DEALING WITH COMPLEXITY :
Counting numbers (due to the gender gap in a library organisation)
●
Difficulty to count due to step counting, which are requiring higher
need for resources and equipment than just visual counting (if
counting conditions are unchanged). We want to keep the same level
of resources, but organise the counting time and the counting method
differently in order to cater for complexity (gender gap).
●
Make ‘’counting simple, but not simplistic’’
●
Professor Chris Chapman (Risk Project Management)
17-02-20

DENIALS
●
Epistolomogy (a theory of knowledge) is the study of the imperfect conditions
of experience when using sciences : 4 criteria are scrutinized i.e. forecast,
denial, creation, critical thinking.

ALL START WITH YOUR BRAIN…
What are your favorite assumptions ?

0,1, 2, 3,...
:
:
:
1,2,3..
1+2+3=6
..
Easy to countEasy to count
(small or lager
volumes within a
fixed time
interval)
The counting of 6
objects in 1
second
How is it possible
to count visually a
larger number of
different objects
when the numbers
start to be larger,
while the time of
counting is
unchanged ?
1,2,3...6
0, 1, 2, 3,...
0, 1, 2, 3,….
?
?
VISUAL
COUNTING
A SMALL
AND A
LARGE
BATCH OF
OBJECTS
OR
SUBJECTS
UNDER A
SMALL
TIME
CONTROL
17-02-20
REGULAR STEPS
IRREGULAR STEPS
CAN I COUNT
VARIABILITY &
AMBIGUITY ?
Difficult toDifficult to
countcount
VISUAL
COUNTING

Fragmentation method
R: Red
B: Blue
2B 1B 4B 2R 4B
1R 1R 1R1B 1R
Linear visual
counting by
domains
D
1
D
2
D
3
D
4
D
5
Domains
(2B+1R) → (2B+1B) + (1R+1R) →(3B+4B)+(2R+1R) →
Travel, unchanged
Counting Time
T1+T2+T3+T4+T5
T1 T2 T3
3B
2R
Mechanism of counting visually and memorizing the
data when travelling from travel start, and from a
domain to another domain, until travel end.
Total journey
Fragmented travels (T)
T4
(7B+1B ) + (3R+2R) →
T5
(8B+4B)+ (5R+1R)
Total journey
12B+6R
17-02-20
Difficult count is a slow countingDifficult count is a slow counting
Equivalent to linearEquivalent to linear
programmingprogramming

« Linear programming is an optimization technique for a
system of linear constraints and a linear objective
function. An objective function defines the quantity to be
optimized, and the goal of linear programming is to find
the values of the variables that maximize or minimize the
objective function » (Google)
Linear programming is efficient, but it is slow, and you need a program which costs, if
you have to make it on yourself, with a quick visual (eyes) counting : 1’30’’, every
morning (BIRD CEO)
LINEAR PROGRAMMING VERSUS VISUAL (EYES) COUNTINGLINEAR PROGRAMMING VERSUS VISUAL (EYES) COUNTING

CRITICAL THINKING

COUNTING SCENARIO :
I have imagined how the brain counts in different scenarios
Scenarios of several domains, with a unique color (a single object to count), we sum up
unit by unit until we get the total sum of the unit counted. We are very familiar, with this
method of counting that we have learned during our childhood in the primary education.
« The brain may work like a stair counting »
G
F
E
D
C
B
A
2 DOMAINS
Visual
COUNTING (Regular
counting in equal steps
due to counting time
constraint)
Travel though
the domains
A+B+C+D+E+F+G= ABCDEFG
BRAIN
COUNTING
A SINGLE
ORGANIZATION
OBJECT
A COMPLEX
ORG NIZATION
OBJECT
Travel though
the domains2 DOMAINS
Easy steps for the brain,
which habbit is regular step counting
Irregular steps counting create resistance to brain
counting with the same counting conditions (counting
Time, identitical objects)
17-02-20

The goal of the new protocol, while the method of counting is unchanged,
is to transform the experience of counting by genders (particularly large
volumes of students) and within the domains into a basic experience of
counting a small number - without the difficulty of counting large
volumes- accross domains or in single domain (at CT unchanged)
Several
difficult
domains
Barriers to
counting
Irregular counting
Regular counting
Barrier
free
counting
All
domains
are easy
Make
counting
easier
17-02-20
A PROJECT PRE-STAGE :
ORGANIZING FOR ACTION

Too
Difficult
Too difficult
Too easy
Looks
the
same
Regular steps
counting
Counting management
makes easier
The brain can count (slide
2), which is the first
objective of the research
One can manage,
only with one can count :
Counting is not just an
objective measure of object,
there are also subjective and
not numerical data, which can
be neglected and create
numerical uncertainty or which
can facilitate the numerical
date capture and counting
method
One can count
(the brain or the machine
can count)
17-02-20
ORGANIZING
FROM COMPLEX TO SIMPLE

Conclusion
●
Transforming irregular into regular steps counting (without training,
but with a new protocol) GOING GREENGOING GREEN (easy counting) : FROM
RED (difficult counting) TO GREEN (easy counting)
Difficult
Difficult
Too easy
It Looks the same
regular steps
Regular
steps
counting and
management
Reorganising
the counting
In counting
with regular
steps
17-02-20

WITH
THE ORGANIZAL CENTRAL CONTROL POINT
AND THE STRATEGIC COMPLEMENTARITY
17-02-20
Crowd density estimation and counting system

●
Based on the look-out point :
Look out points (CENTRAL ORGANISATION POINT) are special points in the
organizations where you can observe the same phenomenon event, as if the
organization was in a complex environment, but without the need to spend resources
while the observations or counting process is much easier and for the same results
Look out points are concept I have already developed in flood management, to forecast
floods. They are geographical locations in the countryside, where you sit and wait for
the signs of the city floods ? These look out points are prominent points equivalent to
elevated point, where you can anticipate the coming of a predicted flood arrival time.
Like in the Greek story of Marathon. « The event was instituted in commemoration of
the fabled run of the Greek soldier Pheidippides, a messenger from the Battle of
Marathon to Athens, who reported the victory .
APPROACHES & ESTIMATES

‘’SIMPLICITY DOES NOT MEAN SIMPLISTIC’’
(Professor Christ Chapman in Risk Project
Management)
THUS, THE
NEED FOR AN
ORGANISATION
CENTRAL POINT
●
The meaning is the marathon race

Battle (and Race) of Marathon
The soldier ran 26 miles to
announce the victory of
Marathon to GreeceMarathon
victory
People did not know the
victory before the man race
to narrate the story of
Marathon victory.
Flood starts
Far from a
city river
Before the flood
arrived in the city,
people can prepare according
to these information given
by the look out point
Look out point is a magnificient point in the
landscape where the information can travel to the
city to give a warning message
Strategic locations in the
library can
Give the real estimate of the
number of readers in
the Library by
breaking down the difficulty
to a level of manageable
counting
The new setting
(Protocol) can confirm the
number counted would be
exactly the same number, if the
organisation was able to count
in complex environment.
Which gives a meaningful communication
and significance to the solving problem
All above methods (historical Marathon, lookout points, strategic
organisation locations) are of anticipation based on indirect methods,
to celebrate a coming of an event work.
The basis of breakdown complexity into manageable bits is to
anticipate and look for proeminent places, where you have an
overview of the phenomenum that you want to study
17-02-20

●
SHOWING FLOW CONSERVATION BETWEEN
COMPARTMENTS AND APPROACHES WITH FEATURES
DATA MAP

Warehouse People
Speed
Gender
Layout Paterns
FEATURES BASED APPROACHES

+ 59
+6
Registration desk
space
Ground floor
reading room
116116 5151
First floor reading
room
No+N1
0
N2 N3
N4
N5
N6
Basement
reading
room
N5+N6
Inside the Library network on February, 11,02,20
Because THE FLOWS INSIDE THE GROUND FLOOR LIBRARY BETWEEN
10:00-10:20 are the Flows inside the library and within the different
compartment rooms (basement, groundfloor, first floor)
HOW ? MAPPING AND LAYOUT WITH FLOWCHARTINGS
17-02-20
Central
Organisation
point
The domains
are the focus
of the counting
system to find
out how
students are
effective
readers
(organisation
behavior)
Today, N=59

THE GENDER CALCULATOR-
DETECTOR WORK IN PROGRESS
GENDER ANALYSIS AND GAP(S) PRINCIPE BASED
AND EVIDENCE BASED POLICY

GAP concept
(LEAVING NOBODY BEHIND)
GAP concept
(LEAVING NOBODY BEHIND)
Fix
Variable
Change
variable
5
Time (T)
N(T)
GAP (Δ))
0
N1 = N0
N2 = N0+5
Δ) = - 5
(students)
21-02-20
« Early automatic detection of critical and unusual situations in large scale crowd is required ».
INDIRECT APPROACH ONE IS UNABLEINDIRECT APPROACH ONE IS UNABLE
TO COUNT (DUE TO COMPLEXITY)TO COUNT (DUE TO COMPLEXITY)
INDIRECT APPROACH ONE IS ABLE TOINDIRECT APPROACH ONE IS ABLE TO
COUNT (DUE TO SIMPLICITY)*COUNT (DUE TO SIMPLICITY)*
A decision
approach
Based on
the blue (fix)
and red
(change)
variables
T1 T2
INTERMEDIATE
CONCEPT

INDIRECT APPROACH
●
Feature based method : gender, speed,patterns, models, time,
layout, statistics

INDIRECT APPROACH AND FEATURE BASED
METHOD OF COUNTING
●
People counting is carried out normally using the
measurements of some features with learning algorithms or
statistical analysis of the whole crowd to achieve counting
process (Albiol et al., 2009, Ryan et al., 2009, Zhang and Li,
2012). This method is considered to be more robust compared
to direct methods
https://www.sciencedirect.com/science/article/pii/S0952197615000081
Reference : SCIENCE ARTICLE DIRECT,
Fig. 2. The proposed taxonomy for crowd density estimation and counting systems.

THE GENDER CALCULATOR
(BOYS AND GIRLS)
Nbr students
Between 10.00
And 10.21’30
Seating in the self learning
(and proeminent room)
The reseachr room can be
forget, because of the very
small number of searchers
at 10.20
––
Males Females
==
17-02-20
THE
GENDER
CALCULATOR
(PHYSICAL
CONCEPT)

●
In the direct approach, which I cannot appraise easily due to the speed of travel in the organization warehouse, due the design
and layouts of the organisation (library) composed of various compartments, due to crowd patterns, which are clusters in various
domains, which are breaking the direct counting and make it difficult to count, as the brain organization brain (individual, firm,
government) is not able to count in an asynchron manner, but only methodically, with simple models (indirect method)
speedspeed layout
timemodel patternspatterns
gendergender
statisticsstatistics
control
point
people
patternspatterns
COMMON
APPROACH
INDIRECT
APPROACH
DIRECT
APPROACH
GENDER CALCULATOR
Features related to the counting and research performance

AUTHOR WORKSHOP ON DATA COLLECTION
●
To have quality data and reducing errors by being on time in the pre-stage of
collecting the data, bearing in mind that these errors will top up the
uncertainties due to a complex organization.

Morning counts 17.02.20 (from the journal notes)
●
Data collection : Males Females
40 53
2 1
2 x X 2
Observations : more girls than boys
are queuing in at the beginning,
thus they are rushing first into the
library from 10.00 to 10.10
10.00
Counting for missing
students (flow out)
Counting for
readers (flow in)
Males Females
10.20
15 11
6 13
7
2
7 16 16
2 4 4
10.10
(10.20)
+ 1’30
out
in
15 16
3 3
N5
10.25
Project start
(entrance door)
Project end
(computer desk
n° 453)
N4
1’30’’
Male (out) : 1 8 females
(out)
1 4
4
Females are more numerous in
Females are
numerous out
17-02-20

72-172-1 98 - 898 - 8
CALCULATOR FOR BOYS
AND GIRLS
Operation 1 :
Add Nbr students to be collected
Between 10.00 and 10.21’30 (to
add in the calculator)
Operation 2 :
Remove students seating in the
self learning (and proeminent
room). The research room can be
forget, because of the very small
number of searcher at 10.20
15 +315 +3
––
Males Females
16+316+3
5353 7171
==
in
out
N5+N6
Expected number of students by gender, if I was able to count
students who are reading in the domains at gound floor level by
gender are N (boys) = 53 (42.75%) N (girls)= 71 (57.25 %)
Boys Gap Deficit (BDG)/ BDG (or GIRLS SURPLUS) = 15.50 %
Ground floor readers
in the domains N= 124
17-02-2017-02-20
Data are collected
According to the
recipe reported in the
Gender calculator
According the ther
recipe
Data recipe
add
remove
+

Gender GAP TODAY
●
EQUAL READERS
CONCLUSION :
THERE IS A GENDER PARITY IN THE LIBRARY BOYS ARE DISCRIMINATED (AND NOT GIRLS AS IT IS REPRESENTED IN THE
SOCIETY) FOR READING IN THE ORGANISATION
IN ADDITION WOMEN ARE WINNERS. IT IS SHOWS BY THE NUMBER OF INTRIES PER GENDER (N(IN) BOYS < N(IN) GIRLS)
AND ALSO, N(OUT) BOYS < N(OUT) GIRLS.
GIRLS ARE WINNING (TO GO). They are first to come in the library the morning, and this trend continous during the 20 minutes.
10 10.20
53
40
65
72
98
10.10
42.75 %
57.25 %
Equality line
17-02-20
Males Females

REPORTING ON UNIVERSITY PROJECT FINANCE AND
PUBLIC PRIVATE PARTNERSHIP (PPP)
HOW OPINIONS CAN CHANGE AND WHAT ARE THE
COMMON POINTS WITH THE DATA MINING ?
A STATE COUNCIL
ADVISER VISITING
EDUCTION MINISTER
TO HAND THE
REPORT ON
UNIVERSITY
PROJECTS AND PPP

REFERENCE :
●
LA PRÉCARITÉ COMME STRATEGIE D’ENTREPRISE
●
https://www.unilim.fr/actes-semiotiques/1437
●
INGENIERING OF ARTIFICIAL INTELLIGENCE: a Recent survey
on crowd density estimation and counting for visual surveillance
●
https://www.sciencedirect.com/science/article/pii/
S0952197615000081

Business Innovation Research Development
(United Nations Economic Social Consultative Status)
●
Thank you !
●
Any Feed Back at :
●
BIRD CEO
●
gsradjou@outlook.com
TakeAction
Takingactiononclimatechangerepresentsoneofthiscentury’smostsignificantbusiness
opportunities.

17 02-20 improving the counting method to fill the gender gap (bis). (copie)

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17 02-20 improving the counting method to fill the gender gap (bis). (copie)