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Distributed application for calories optimization

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Basic concepts regarding measuring the level of daily calories are presented. Effort level and its influence on the daily needs are measured and classified. Ways to determine the daily level of calories are presented. A database with complex ingredients is build for creating an optimization algorithm of calories needs by minimizing the differences between the level of calories determined, based on the daily effort and the level of calories returned by the application.
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Bodybuilding Journal Vol. 1, no. 1, 2009
83
Distributed Application for Calories Optimization
Mihai DOINEA
Economic Informatics Department
Academy of Economic Studies, Bucharest
mihai.doinea@ie.ase.ro
Abstract: Basic concepts regarding measuring the level of daily calories are presented.
Effort level and its influence on the daily needs are measured and classified. Ways to
determine the daily level of calories are presented. A database with complex ingredients is
build for creating an optimization algorithm of calories needs by minimizing the differences
between the level of calories determined, based on the daily effort and the level of calories
returned by the application.
Keywords: optimization, distributed application, calorie, algorithm.
1. Daily calorie requirements
In this new approach of knowledge based society where technology is at the top of all
human processes and physic activities are part of the past the adjustments in our daily food
table must counterweight the lack of physical effort.
Inactivity given by our new way of life, sitting in an office, in front of a computer and
doing things that only stimulate our intelligence, can be compensated with a strictly diet or
with a regular physical training program. Like astronauts who are making daily exercises to
provided effort for their muscular system, effort which in its absence all the muscles will
atrophy, like this the modern human Homo Sapiens in his unending stroke for surviving and
evolution must keep a healthy diet eating just how much it needs correlated with the effort
factor. The effort correlation with the daily calorie consumption is a complex bound in which
many types of effort should be evaluated like:
physical effort;
neurological effort;
emotional effort.
Physical effort is one of the most researched areas. Scientist, physicians, sportsmen and
other interested parties had developed a whole system of indicators.
Trying to get the best out of the human body they measured calories consumption in
human regular activities and training exercises and classified them by effort intensity. In the
table 1, are presented the daily calorie allowance for male depending on the effort level and
weight expressed in pounds:
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84
Table 1 – Man daily calorie need
Studies had showed that females need for calorie burning is much lower than male. This is
due to the fact that female constitution is different from male and they tend to store fats in the
hip section. In table 2, female daily calorie need is presented from a level of super active
effort to sedentary.
Table 2 – Woman daily calorie need
This means that a woman will consume almost a number of calories equal to a man but
from different sources:
meals;
fat deposits.
The difference between the two sexes is that a man has a much higher metabolism rate
and the daily calorie intake is processed much rapidly comparative to a woman who processes
the fats resource too. But at the end both man and woman has to preserve The First Law of
Thermodynamics, which is: Calories IN = Calories OUT,
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85
no matter where they come.
Cognitive intensive effort has its word in the process of daily calorie consumption. One of
the best practice examples is the student session period when majority students change their
way of life for a couple of weeks. In this time, intensive cognitive effort is made which will
request a high amount of proteins, which are the main resource for the brain to function at full
capacity. Doing so, using more proteins as fuel for the thinking machine, will alter the
established equilibrium, resulting in less food per capita per day. At the end of the students
session period they will fill a change in their weight status in plus or in minus.
Emotional effort is too a direct factor which affects the daily calorie consumption and one
of great importance. Emotional effort can lead peoples in or out of medical problems by
influencing our meals.
It is well known that are persons emotional eaters in which the desire to eat, their hunger
is purely emotional based. This kind of disorder appear suddenly as react to a stressful event
and produces appetite for a particularly type of food.
Stress is one of the most important reasons due to which people get hungry. It is known
that when we are stressed a whole chain of reaction starts in our body. First of all the stress
increases the level of cortisol in our body, a hormone that is triggered by stress and which
tells to our cells to release rapidly an important amount of carbohydrates and fats. That’s why
that energy released must be compensated with another one which enters to preserve the first
law of thermodynamics.
As a response of that chain reactions, our body screams for food, especially sweet and
salty foods from which it can absorb rapidly the amount of energy spent as a reaction to
stress.
2. Calories database
Since 19
th
century people had started to determine correlations between the physical effort
and the amount of calories burned in the process. Lots of statistical data have been gathered to
conclude on this issue, tables which present the amount of calories burn depending on the
type of activity or the amount of calories found in a unit of nourishment have been elaborated
to help people take efficient decisions about their calorie expenditure.
In this sense, IT&C technology can help gather, process and analyze results of large
amounts of data using specialized software and equipments. A database for storing calorie
values for a specific type of food was build for helping on creating the daily menu for a
person based on his weight expressed in pounds and on the level of effort which that person is
exposed for every day. In the figure 1, it is represented the internal structure of a table which
can store this information which can be processed later by other applications.
Fig. 1 – Daily menu table
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This internal structure describes the fields from which the table is composed in the
following order:
idmeniu is the primary field which has number values; must always be present,
meaning that the property Nullable is set to the value No and the most important,
this field is the primary key of the table; the value of this primary key field always
identify uniquely a record in the table;
descriere is the secondary field which has character values; it represents a
description of the entire record identified by the first field; can be absent and it is
not a primary key, only one field or group of fields can compose the primary key;
nrkcal represents the number of calories associated with the corresponded
record; it can be null;
tip – is the type of meal as breakfast, lunch and dinner;
imagine represents a visual description, a picture, of the associated meal,
identified by the first field, the primary key.
This was an example of how people can use IT&C technology to store information about
their calories consumption or about the number of calories found in a particular type of food.
There is lots of useful information that can be stored in a database. A specific type of
aliment contains the following information and more:
food energy represented by the number of calories;
fats specified in grams per unit;
saturated fats per unit;
carbohydrates in grams per unit;
proteins in grams per unit;
cholesterol in milligrams per unit;
fibers;
sodium;
In [01] is presented a food calorie list separated by the type of aliment in which they can
be found like: vegetables, meat, fish, milk, cheese, nuts, alcohol, beans, rice, fruits, cereals,
pizza and more others.
In the following figure, detailed in [02], it is presented the number of calories that a
person of various weights burn per minute during different regular activities.
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Fig. 2 – Calorie burn per activity by weight
Based on this kind of data, complex systems of measuring have been developed,
indicators like BMI – Body Mass Index, FMI – Fat Mass Index, BMR – Basal Metabolic Rate
have been used to measure all the aspects of physical effort to help people understand better
the way how their bodies work.
3. Optimization processes
Optimization is a continuous process of getting significant better results from a
previous state. Optimization has always been in the human nature to perfect things and takes
more and more advantage from the surrounding world. Can even be said that optimization
was the principle of alchemists who tried to transforms a simple metal in gold in antiquity or
middle age. Even the Nature has this principle integrated in its system, because without
optimization, evolution is not possible in the context of a world filled with threats.
Optimization regarding the daily calorie expenditure is related to the following
concepts presented in [03]:
BMI – Body Mass Index, is a statistical index which compares a person’s weight
and height; this index is relevant in estimating a healthy weight;
BMR – Basal Metabolic Rate is the amount of energy expended while at rest in a
neutrally temperate environment; this release of energy in this state is sufficient
only for the functioning of the vital organs;
FMI – Fat Mass Index is the amount of fat reported to the muscular mass and the
total weight of a person;
LBM – Lean Body Mass represents mass of the body – the fat.
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88
The BMI index can be calculated based on the following formula in International Systems
of Units – SI:
BMI = weight (Kg)/height
2
(m
2
)
Based on the values that result from the following formula a person can be classified in
one of the following categories presented in [04], table 3:
Table 3 – BMI ranges
Category BMI range – kg/m
2
Severely underweight less than 16.5
Underweight from 16.5 to 18.5
Normal from 18.5 to 25
Overweight from 25 to 30
Obese over 30
Basal Metabolic Rate is calculated different for man and woman. This is due to
differences in metabolic activities and processes that appear on both genders. Basal Metabolic
Rate has the following formula:
for man:
for woman:
Calculating BMR, for people who suffer of metabolic diseases and are overweight or
obese, with the formula presented above can be insignificant because of their excess fat
deposits. As optimization the Basal Metabolic Rate is calculated based on the LBM, Lean
Body Mass using the next formula:
,
where LBM is differentiated by gender.
The LBM is calculated as follows:
for men:
LBM = (1.10 x Weight(kg)) – 128 x ( Weight(kg)
2
/Height(m)
2
)
for women:
LBM = (1.07 x Weight(kg)) – 148 x ( Weight(kg)
2
/Height(m)
2
)
This approach is useful for determining our body’s needs for calories and gives precise
directions in lowering, maintaining or growing our body fat mass implicit our weight.
4. Distributed application for daily calorie optimization
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89
A distributed application is a program who has components structured on several layers
and which resides on different machines. For daily calorie consumption, a distributed
application was build helping to determine the body calorie needs based on several input data
like weight, height and age. The Application for daily calorie need based on the body mass
index and the effort intensity is formed of 2 layers:
application layer;
database layer.
These two layers communicate to offer users a helpful experience in the calculation of the
following indicators:
Body Mass Index, BMI;
Basal Metabolic Rate, BMR;
Lean Body Mass, LBM;
Daily Calorie Need, DCN based on effort
intensity;
the combination menu, breakfast, lunch and
dinner optimized for DCN.
For all of the previous indicators and results the
application looks as follows, figure 3:
Step1 – Input data:
This form is used to gather information about the
individual who access the application. For calculating
body mass index, basal metabolic rate, lean body mass
the application needs as input data information about
the person who accesses it, like:
age;
weight;
height.
Step2 – Calculating BMI, BMR, LBM:
After the first step, input data where processed and according to the gender mentioned
calculation are made applying the formula presented in the previous chapter, resulting the
indicator BMI, BMR and LBM presented in figure 4:
Fig. 3 – Input form
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90
Fig. 4 – Application first results
From this numbers, result that unlike female, male have a higher metabolic rate and a
surplus of fats much lower than females. In the table 4 results are presented in comparison:
Table 4 – Correlation results
Gender/Indicators
BMR
1
LBM
2
Weight
3
Body Fat
(Weight – LBM)
4 = 3- 2
BFP –Body Fat
Percentage
5 = 4/3
Men 2088 57 69 12 17.39%
Women 1765 52 69 17 24.63%
Based on this value of fat percentage we can tell the category in which an individual is,
just like the BMI classification, as presented in table 5:
Table 5 – Fat percentage category
Category Men Women
Essential fat 2-4% 10-12%
Athletes 6-13% 14-20%
Fitness 14-17% 21-24%
Acceptable 18-26% 25-31%
Overweight 27-37% 32-41%
Obese 38%+ 42%
From this we can tell that both man and woman are situated at the end of the Fitness
category with a value of 17.39% for man, respective 24.63% for woman.
Step3 – Calculation of the daily calorie needs and the meal combination:
In the figure 5, can be viewed the level of calorie that is need based on the intensity effort
made in a particular day. Based on this level of calorie consumption a combination of meals
Bodybuilding Journal Vol. 1, no. 1, 2009
91
are calculated in such a manner that the column Difference which represents the difference
between the calories need and the sum of calories on the whole three meals to be minimum.
Fig. 5 – Daily calorie consumption
All combinations of meals are given in such a way that none should repeat in two or more
days, all combinations being unique for every single day.
Step4 – Evaluating the final results
This step is for visualizing the whole three meals by clicking on the number associated in
the Total column. In figure 6, is presented a combination of recommended meals for Tuesday,
having a total of calories of 2870 and based on the intensity effort set to Less Active with a
calculated calorie need of 2871 and a difference of 1 calorie needed.
Fig. 6 – Meal combination for calorie consumption
Every meal is formed of one or more ingredients presented in DESCRIERE field,
having a total number of calories presented in column NRKCAL.
5. Algorithm efficiency and improvements
The algorithm used is based on the minimization of differences between the amount of
calories needed for consumption reported to the intensity effort made and the total number of
calories formed by summing each meal.
Bodybuilding Journal Vol. 1, no. 1, 2009
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The amount of calories needed for one day based on the type of effort made is calculated
using the following formulas presented in table 6:
Table 6 – Total daily energy expenditure - TDEE
Category BMR coefficient Description
TDEE
SEDENTARY
1.2 x BMR Sedentary activity – television or office work
TDEE
LESS ACTIVE
1.375 x BMR Light activity – exercise workout 1 – 3 day per week
TDEE
ACTIVE
1.55 x BMR Moderate activity – exercise workout 3 – 5 day per week
TDEE
VERY ACTIVE
1.725 x BMR High activity – exercise workout 6 – 7 days per week
TDEE
EXCESSIVE
1.9 x BMR Extreme activity – exercise workout two times per day
Efficiency is given by the database usage which allows users to have lots of meals combinations
covering almost all possibilities of effort intensity and BMR indexes.
The method of calculating the menu combination is by simulation optimization [05],
described in the following figure 7:
Fig. 7 – Solution generation
For better results, an optimization can be made for the meal generating stage under which
every meal will have an exact percentage of calories from the total amount. Studies had
shown that our body needs calories distinctively by the day period as follows:
30% of calories at breakfast;
50% of calories at lunch;
20% of calories at dinner.
In this way equilibrium would be achieved and it will make us more efficient in our future
research.
YES
N
O
Solution S
k
Meal database
Solution S
initial
S
k
better
than S
initial
STOP
S
initial
= S
K
Bodybuilding Journal Vol. 1, no. 1, 2009
93
6. Conclusions
In a world where everything is done remotely or automated using performant
machines our lack of concern can drive us in no time to overweight even obese persons. That
is why all the knowledge gained as legacy from our past generations must put the break and
help us to manage our daily calorie consumption doing the three things to have a good and
wealthy health:
eating well;
eating as much as we need;
eating when we need.
It is true that things in now days are done much rapidly using the state of the art
technologies and that we have more time at our disposal but also, it is true that our
expectation have increased and we are more and more caught in the middle of our daily life.
Acknowledgements
This article is a result of the project „Doctoral Program and PhD Students in the education
research and innovation triangle”. This project is co funded by European Social Fund through
The Sectorial Operational Programme for Human Resources Development 2007-2013,
coordinated by The Bucharest Academy of Economic Studies.
Bibliography
[01] (2009, Aug.) Food calorie list. [Online] http://www.weightlossforall.com/food-calories-
list.htm
[02] (2009, Aug.) America’s Authority of Fitness. [Online]
http://www.acefitness.org/FITFACTS/fitfacts_display.aspx?itemid=322
[03] (2009, Aug.) Wikipedia Site. [Online] www.wikipedia.com
[04] (2009, Aug.) BMI Ranges. [Online] http://en.wikipedia.org/wiki/Body_mass_index
[05] Ion IVAN, Cătălin BOJA – Practica optimizării aplicaţiilor informatice, ASE Printing House,
Bucharest, 2007, ISBN 978-973-594-932-7, 483 pg.
Mihai DOINEA attended the Faculty of Economic Cybernetics, Statistics
and Informatics of the Academy of Economic Studies, graduating in 2006,
Computer Science specialization. Having a master degree in Informatics
Security, promotion 2006-2008, he is currently a PhD candidate,
Economics Informatics specialty in the same university, also teaching as
assistant to Data Structure and Advanced Programming Languages
disciplines. Following are the fields of interests in which he wrote a
number of papers in collaboration or as single author concerning: security, distributed
applications, e-business, security audit, databases, and security optimization.
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