KOEFICIENT NA OPTOVARENOST NA ROTIRA^KI BAGER
Health Sciences Year IX Volume 11 June 2013
Bitola
Publisher: University St.Kliment Ohridski-Bitola For the publisher:
Prof. Zlatko Zhoglev, PhD, Rector International Editorial Board
Prof. Ljupcho Trpezanovski, PhD, University St. Kliment
Ohridski-Bitola, R. Macedonia Prof. Mile Stojchev, PhD, University
of Nis, R.Srbia Prof. Cemal Talug, PhD, University of Ankara,
R.Turkey Prof. Tomaz Tollazzi, PhD, University of Maribor,
R.Slovenia Prof. Kostadin Vasilev, PhD, University of food
technology-Plovdiv, R.Bulgaria Prof. Jovica Jovanovik, University
of Nis, R.Srbia Prof.Mile Stankovski, University Ss. Cyril and
Methodius-Skopje, R.Macedonia Editorial Committee Prof. Pere
Aslimoski, PhD, vice-rector Prof. Sasho Atanasoski, PhD,
vice-rector Prof.Nikola Krstanoski, PhD, vice-rector Prof. Jovanka
Tuteska, PhD, vice-rector Ofelija Hristovska, MA, Secretary General
Editor: Elena Kitanovska-Ristoska, MA
ISSN 1857- 8578 Print: AD Kiro Dandaro-Bitola, printing copies:
200
Dear readers, The public has almost become a kind of used to the
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Sincerely, The editing board
CONTENT Ivo Kuzmanov, MSc, Zore Angelevski, PhD, Silvana
Angelevska, PhD; Survey of key indicators in accordance with the
internationlan standard ISO 9001:2008 in real industrial
systems..............................................................
9 Aleksandar Kotevski, MSc, Gjorgi Mikarovski, MSc; Using vector
space model for text classifying in e-learning
system............................................. 15 Mirka
Popnikolova Radevska, Blagoja Arapinoski, Vesna Ceselkoska;
Electromagnetic field analysis of three phase synchronous motor in
3D..... 21 Sashko Martinovski, MSc, Gjorgji Mancheski, PhD; GIS
modelling for the strategic urban development planing regarding the
Republic of Macedonia
...........................................................................
31 Vaska Atanasova, Lidija Markovik; Transport demand forecast by
applying software package PTV vision visum
.............................................................43
Dmytro Zubov, PhD, Volodymyr Osypenko, PhD; “Exam as Additional
Training” Concept: Two Semesters Experience of the Special Test
Software’s Implementation
...........................................................................
53 Jordan Martinovski, Sasko Martinovski, MSc; Using geogebra in
primary schools
..........................................................................................................
63 Zivko Gacovski, Sasko Stojanovski; Investigating the genetic
potential of grain yield of wheat varieties cultivated in the
Bitola part of Pelagonija .... 69 Vera Pande Simovska - Jarevska;
Targeted “lifestyle” intervention programmes to reduce
cardiometabolic risk at abdominal obese individuals
........................................................................
75 Lenche Mirchevska, Snezhana Mojsoska; Socio-medical aspects of
smoking to examined population in
Bitola..................................................................
85
9
udc 006.83:658(497.7)
SURVEY OF KEY INDICATORS IN ACCORDANCE WITH THE INTERNATIONLAN
STANDARD ISO
9001:2008 IN REAL INDUSTRIAL SYSTEMS FP
1
The global way of organization activity has completely changed
the
organizational approach to work. Considering three key elements of
today's market society: the period of delivery, cost and quality,
it can be concluded that quality is a key element for market
success. A key aspect in favor of this conclusion is the identical
delivery, and the changed habits of the customers. The change in
buying habits has led to a situation where the buyer is willing to
pay a higher price for distributed quality. In this way the quality
of product or service is the key differential element. Regarding to
this conclusion the implemented quality system in the form of ISO
9001:2008 international standard is one of the ways for perfecting
quality in global markets. But the real question that arises is the
following: What is the situation about the standard after the
certification? Do organizations maintain it?
The purpose of this paper is the survey on several key indicators
in accordance with the standard, realized in 82 business entities
in Republic Macedonia.
Key words: quality, ISO 9001:2008, key indicators regarding to the
requirements of the standard.
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HORIZONS
10
INTRODUCTION
The global way of market activity has led to changed market
conditions, which led to drastically changed purpose of industrial
systems. While in the past, the basic purpose of any industrial
system was profit, today priority is placed on quality of product /
service. The fact that the market conditions are dramatically
changed, can be recognized in today’s buyers habits. Nowadays the
customers are willing to pay a higher for quality.
One of the ways for differential recognition of organizations, is
practically the implemented quality system, shown in the form of
ISO 9001:2008 standards. Although the basis of the standard is
documenting the processes and activities, numerous organizations
don’t understand the basic concept of the standard. This can
particularly be seen from the research conducted on real industrial
systems in the Republic. Macedonia.
In fact most of the organizations, the complete documentation have
"prescribed" from another organizations, or their sister
organization has rented a consulting company with purpose just to
get a certificate. In this matter the essence of the standard,
which if properly implemented, brings numerous benefits, is
completely wasted.
But the situation is not so "black". This can be seen in numerous
of the organizations implementing the standard as a part of a long
term strategy. In this way the functionality of the standard leads
to continuous quality improvements.
THE RESEARCH OF THE KEY INDICATORS
Taking in consideration the nature of the standard and the
applicability of the same in any organization regardless of type,
size, position and organizational structure, there is a wide field
for research in this area. One of the key elements of the standard
is to improve the quality in all organization levels. In this
direction was the conducted research on several key indicators in
82 business entities in the Republic of Macedonia who have
implemented the ISO 9001:2008 standards.
The key indicators that were taken into the conducted survey were:
• Indicator – supplier • Indicator – training • Indicator -
fulfillment of the customer’s requirements • Indicator - use of
methods and techniques for validation of business processes
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• Indicator - relationship with a supplier in accordance with
established methodology according to ISO 9001 standard • Indicator
– nonconforming product • Indicator - alternative actions
nonconforming product • Indicator – ways for identifying the
product • Indicator – use of the benchmarking process
The purpose of the conducted research was to get information for
the use of these key indicators with the requirements of
international standard for quality, in the so-called
cross-certification period (time frame of 3 years).
Research as previously stated was conducted on 82 businesses that
are certified under the requirements of the standard. When choosing
business entities, despite the availability of information and the
possibility of cooperation, as elements taken into account were:
organizations from different industrial branches, with varying
degrees of development, different organizational structure and a
different way of management.
In this way the sample taken into research in the survey is
representative and the results can be taken as a result of the
population (subjects who have implemented the standard and
operating in the territory of the Republic of Macedonia).
SOME OF THE INDICATORS TAKEN INTO THE CONDUCTED
RESEARCH
Indicator supplier
The demands of the standard ISO 9001:2008, into paragraph 7.4.2
(information suppliers), require evaluation of suppliers, which are
an essential element. These key elements are inputs into business
that lead to an increase or decrease of the final product
quality..
The criteria that were used for this part of the research and the
results of the analysis are given into tabular display 1.
Used Not used Num. Criteria
Frequency % Frequency % 1 „Just in time“ delivery 78 95.1 4 4.9 2
Quality of the delivered product 75 91.4 7 8.6 3 Nonconforming
products in the
last period / 0.0 82 100.0
4 Price 82 100.0 / 0.0 5 Suppliers capacities 24 29.2 58 70.8 6
Other criteria 3 0.7 79 96.3
Tabular display 1. Research results for the indicator
supplier
HORIZONS
12
According to survey results in relation to the specified indicator,
businesses during the process of supplier choosing, primarily use
the cost criterion as a key element in 100% of the cases, then the
quality of raw materials as a criteria. On the other hand, the
facts shows that most businesses have a partner supplier that have
constant quality of the materials delivered.
Indicator – nonconforming product Each organization MUST pay
attention to identifying the products that
does not comply with the requirements. In the context of the above
mandatory requirement, the paragraph 8.3 (Managing nonconforming
product) of the standard, is with aim to prevent unintended use or
delivery. Management with non-harmonized product must be defined in
a documented procedure.
There are several ways to "treat" non-harmonized product in
organizations such as:
Taking action to remedy the identified non harmonized shortcoming
Approval for its use, additional permit given from the
relevant
authority, sometimes from the user Taking measures to prevent its
original intended use or application.
In accordance with the requirements of ISO 9001:2008 standard, and
taking into consideration the identified gaps, each non-compliance
must be properly documented and appropriate action MUST be taken
for further treatment of non-harmonized product. In this direction
are given the results from the researched criteria for the
indicator nonconforming product, shown in Table display 2.
Used Not used Num. Criteria
Frequency % Frequency % 1 Identified nonconforming
product into the process of production
2 2.4 80 97.6
76 92.6 6 7.4
82 100. 0
/ 0.0
Table display 2. Results from the research on the indicator
nonconforming product
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Indicator - Product identification
According to the paragraph 7.5.3 (Identification and Monitoring)
each organization must provide adequate documented way to track the
product through production stages. Methods of recording and
traceability are different and depend on the subjective decision of
the management team. Research results are presented into the
tabular display 3.
Used Not used Num. Criteria Frequency % Frequency %
1 Work order 77 93.9 5 6.1 2 Serial number 59 71.9 23 28.1 3 Date
of production 1 1.2 81 98.8 4 Identification card 7 8.5 75
91.5
Table display 3. Results from the research on the indicator –
product identification
CONCLUSION
Taking into consideration the initial hypothesis of the study, that
the
largest percentage of Macedonian businesses, quality systems have
on paper, and without proper use benefits, the results of the
survey has proven quite the opposite. Namely the largest percentage
of organizations properly identify products, identify
non-compliance and evaluate their suppliers.
However the results from the indicator nonconforming product showed
that in 97.6% of cases the records is after the occurrence of non-
compliance, and not in the process of production. This conclusion
opens the field for further research.
REFERENCES
1. Msc. Ivo Kuzmanov, Branding and application of ISO 9001:2008
standard and OSHAS 18001 as a model for continuous improvement of
industrial systems, PhD dissertation, Technical Faculty in Bitola,
2012 2. Ray Tricker, ISO 9001:2008 for Small Businesses, Fourth
Edition, With free customizable Quality Management system files,
2009 3. Msc. Ivo Kuzmanov, research on business entities, Technical
Faculty in Bitola, 2012 4. Erik V. Myrberg, A practical field guide
for ISO 9001:2008, 2009
HORIZONS
14
15
USING VECTOR SPACE MODEL FOR TEXT CLASSIFYING IN E-LEARNING
SYSTEMFP
2
[email protected]
ABSTRACT
This work proposes a model of an intelligent e-learning system
by
classifying the learning contents published by teachers using
Vector Space Model. The most materials in the case of e-learning
are stored in a textual unstructured form. A means to provide
high-quality information from unstructured text is text mining. Our
proposal uses vector space models to classify learning materials
into different appropriate categories. In order to make the process
of information retrieval efficient, each category contains a list
of synonyms and keywords, and the categories are manageable by
administrator and users.
Key words: Data mining, intelligent, learning system,
classification, phrases
INTRODUCTION
Because the most learning materials are present in textual form,
there is one segment from data mining that is dedicate to mining
the unstructured and unrestricted documents, called text mining.
Namely, text mining is more complex process then data mining,
because data mining works with data with fixed and known structure,
for example traditional databases [1]. In
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HORIZONS
16
contrast, text mining works with unstructured data. That’s why text
mining involves a few steps for data processing and modeling.
In the proposed learning system, text meaning will be use for
searching through documents and learning articles that are
published by teacher. The result of text mining process will be
proposing the most relevant category for learning material.
Category list is dynamically and editable by system administrator.
This technique mainly relies on the analysis of keyword in the
documents and learning content. Also they use similarity
calculation through word and phrase matching.
VECTOR SPACE MODEL
The vector-space models for information retrieval are just one
subclass
of retrieval techniques that have been studied in recent years.
Although the vector-space techniques share common characteristics
with other techniques in the information retrieval hierarchy, they
all share a core set of similarities that justify their own class
[2]. The Vector Space Model (VSM) is probably the most widely used
model for retrieving information from text collections [3].
Vector-space models rely on the premise that the meaning of a
document can be derived from the document's constituent terms. They
represent documents as vectors of terms where is a non-negative
value denoting the single or multiple occurrences of term in
document D. Thus, each unique term in the document collection
corresponds to a dimension in the space. Similarly, a query is
represented as a vector where term is a non-negative value denoting
the number of occurrences of (or, merely a 1 to signify the
occurrence of term) in the query [4]. Both the document vectors and
the query vector provide the locations of the objects in the
term-document space. By computing the distance between the query
and other objects in the space, objects with similar semantic
content to the query presumably will be retrieved. Information
retrieval models typically express the retrieval performance of the
system in terms of two quantities: precision (ratio of the number
of relevant documents retrieved by the system to the total number
of documents retrieved) and recall (ratio of the number of relevant
documents retrieved for a query to the number of documents relevant
to that query in the entire document collection). Both precision
and recall are expressed as values between 0 and 1. An optimal
retrieval system would provide precision and recall values of 1,
although precision tends to decrease with greater recall in
real-world systems [5].
NATURAL SCIENCES AND MATHEMATICS, ENGINEERING AND TECHNOLOGY,
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IMPLEMENTATION
In this paper, the vector space model is used for classification
the learning content in different categories. This module is part
of intelligent e- learning system where teachers can upload
learning content in e-learning system. After textual file has been
uploaded, system will go through the text and detect which category
is the most appropriate. As a part of this paper was developed
simple web application, which contain two main parts:
- Manage the category (key words for selected category) - Upload
and categorization
User can manage the keywords for categories, by changing value in
text box:
Figure 1: Manage keywords for selected category
The main functionality of this system is proposing the most
appropriate category for learning content that user has been
uploaded.
Figure 2: Upload new learning content
HORIZONS
18
Vector space model is used for proposing new category by comparing
the most frequents words from learning content with keywords from
each category. The following algorithm is used for implementing
Vector space model:
Figure 3: Implementing Vector space model
Read text file
Extract Common Words
words with category keywords)
array
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RESULTS
After implementing the code for content categorization, we were
testing the system with 50 learning content from different
categories: programming, software, network and design.
Table 1: Results from Vector Space model testing
Test process gave precision result of 0.80 (40/50). It means that
from total 50 learning content, for 40 of them vector space model
proposed the correct category. That result is acceptable for
implementing vector space model in e- learning system.
File Category
Vector Space Model
1. adapter.txt Hardware 1 2. asp.txt Programming 1 3. barcode.txt
Hardware 1 4. c++.txt Programming 1 5. computer-network.txt
Networking 0 6. corel.txt Design 1 7. css.txt Design 1 8.
c-sharp.txt Programming 0 9. delphi.txt Programming 1 10.
design.txt Design 1
1 0 Total 8 2
Precision 0,80
HORIZONS
20
CONCLUSION
There are a lot of technologies that enable different ways to store
and share large amount of data. Some of them are useful for some
users, but it’s almost impossible to be found the most appropriate
date from tremendous amount of data [6]. But, using data mining
technique will produce efficient and easy access to useful
information. On the other site, implementing e- learning within the
educational process becomes more than necessary. If we make
combination from e-learning and data mining, undoubtedly will got
learning system that will be adaptable to users (teachers and
students) needs.
By using the Vector Space model, system can easy and effective
categorize the learning content to the most appropriate
category.
REFERENCES
1. Kent Ridge Digital Labs, Text Mining: The state of the art and
the challenges 2. Michael W. Berry, Introduction to Vector-Space
Models 3. Yannis Tzitzikas and Yannis Theoharis, Naming Functions
for the Vector Space Model, Computer Science Department, University
of Crete, GREECE, and Institute of Computer Science, FORTH-ICS,
GREECE 4. N. Belkin and W. Croft. Retrieval techniques. In M.
Williams, editor, Annual Review of Information Science and
Technology (ARIST), volume 22, chapter 4, pages 109--145. Elsevier
Science Publishers B.V., 1987. 5. Frakes and R. Baeza-Yates,
editors. Information Retrieval: Data Structures & Algorithms.
Prentice Hall, Englewood Cliffs, New Jersey, 1992. 6. Eduard Hovy,
Data and knowledge integration for egovernment, Information
Sciences Institute, University of Southern California, Marina del
Rey, California, U.S.A.
NATURAL SCIENCES AND MATHEMATICS, ENGINEERING AND TECHNOLOGY,
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ELECTROMAGNETIC FIELD ANALYSIS OF THREE PHASE SYNCHRONOUS MOTOR IN
3DFP
3 PF
[email protected]
[email protected]
In this paper a methodology for numerical determinations and
complex nonlinear analysis of electromagnetic fields in 3D domains
on three phase salient poles synchronous motor is presented. The
motor is numerically modeled and calculated with nonlinear and
iterative calculation using Finite Element Method. The program
package is also used for performing automatic generation of finite
element mesh. After defining material construction and their
properties, loading and excitation in both motor windings, the
distribution of electromagnetic field is calculated from which the
electromagnetic flux density in 3D motor domains can be
generated.
Key words: synchronous motor, electromagnetic field analysis.
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HORIZONS
22
INTRODUCTION
The three phase solid salient poles synchronous motor is rated
following data: nominal power 2.5 kW, nominal voltage 240V, current
of excitation 5.5A, voltage winding of excitation 30V, power factor
0,97, frequency 50Hz and speed of 1500rpm.
Finite elements method is proven tool for analyzing electromagnetic
phenomena in electrical machines and devices. This method enables
to enter “inside the machine” and to evaluate exactly magnetic
quantities such as air gap flux or flux density in any part of the
electrical motor.
MODELING OF SYNCHRONOUS MOTOR WITH FINITE
ELEMENT METHOD
Design and modeling of three phase solid salient synchronous motor
used program package for fully automatic design and modeling on
model geometry based on solving the empirical equations based on
his calculation by classical theory, using parts of the modern
theory [1]. In the case considered three-dimensional nonlinear
magnetic fields as expressed by the following system of
equations:
rotH=J
divB=0
B= H
rotA=B
(1.1) In this case the magnetic field is described by partial
equation:
rot( B rot(A))=J
(1.2) Equation 1.2, developed in differential form in 3D, takes the
form of Poisson-equation:
A A A B B B J(x,y,z)
x x y y z z
(1.3)
Equation (1.3), can-not be solved analytically because the
characteristic of magnetization is nonlinear. The solution is
obtained by
NATURAL SCIENCES AND MATHEMATICS, ENGINEERING AND TECHNOLOGY,
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reduction of its system of partial differential equations which are
solved using a computer.
Automatic computer design is performed in several stages, in
addition, the most important accurate definition of input data and
motor geometry.
The stator is outer lamination stack where the three phase windings
reside. Stator core is made from magnetic material with
characteristics of magnetization given on Fig. 1 a).
Fig.1.a. Magnetic characteristic of stator
Rotor core is made from solid iron with magnetic characteristic
given on Fig. 1.b.
Fig.1.b. Magnetic characteristic of rotor
The stator is equipped with a three phase winding that has a
sinusoidal
spatial distribution. Step of winding is reduced and is y=11/12,
while the rotor coil is performed as concentric. Part of motor
geometry with windings is shown on Fig. 2.
HORIZONS
24
PRE-PROCESING PART OF PROGRAM PACKAGE, DEFINING THE NECESSARY
VARIABLES
To obtain the magnetic field distribution and intensity of
magnetic
field in the overall 3D synchronous motor domain, have a need for
additional input the current densities and conductivity or magnetic
voltages in both motor windings.
In order program to be able to solve the problem boundary
conditions on the border areas must be defined. For analyzed three
phase synchronous motor Dirichlet boundary conditions are
used.
On Fig.3 motor model is presented and from figure very well see
whole 3D geometry, stator core with three phase winding and rotor
core with concentric windings.
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Fig.3. Three phase synchronous silent pole motor, 3D model
Mesh of finite elements is presented which is derived fully
automatically and is consisted of 483205 Tetrahedron and is
presented on Fig.4.
The exact solution is obtained over 60 successive iterations that
take place in 4 phases, during eight hours, configuration used
“Pentium i5” processor and 4GB of RAM.
The time required to resolve depends on the mesh density of finite
elements and the specified accuracy of the results. In this
analysis precision of the results is of the order 10P
-6 P.
Fig.4. 3D Finite element mesh
To get more accurate computations in some regions the mesh density
is increased, especially in the air gap on interface between two
different materials, there mesh of finite elements is densest.
Detailed view of increased mesh density is presented on Fig.
5.
Fig.5. Part of 3D finite element mesh in the air gap.
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ELECTROMAGNETIC CHARACTERISTICS IN 3D DOMAINS OF THREE PHASE
SYNCHRONOUS MOTOR
By solving a number of nonlinear equations and iterative
procedure
leads to the final distribution of the magnetic flux density in
overall 3D synchronous motor domain. Magnetic flux density in
overall 3D motor domains when both windings are excited with rated
currents is presented on Fig. 6.a.
Fig.6.a. The magnetic flux density in overall 3D motor
domains
Determines the value of magnetic flux density in all parts of the
synchronous motor is presented on Fig. 6. Because data of magnetic
flux density in air gap is one of the most important value. On
Fig.6.b. normal component of the vector of magnetic induction along
the line which is located in the middle of the air gap is
shown.
HORIZONS
28
Fig. 6.b. Normal component of the vector of magnetic
induction.
Direction of the vector of the magnetic flux density is presented
on
Fig.7, as magnetic field intensity distribution is presented on
Fig.8.
Fig.7. Direction of the vector of the magnetic flux density in
3D.
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CONCLUSION
In this paper is presented numerical modeling of three phase
synchronous motor, computation of the magnetic field distribution
and the magnetic field intensity, by nonlinear iterative numerical
method.
For this purpose is significant that the calculations are based as
the most suitable Finite element method in 3D motor domains.
It allows an accurate calculation of the magnetic flux density in
3D motor domains as: air gap, teeth of stator core and rotor solid
salient pole.
REFERENCES
1. Mirka Popnikolova Radevska, Blagoja Arapinoski, Computation of
solid salient poles synchronous motor electromagnetic
characteristic,10 P
th P
international conference of applied electromagnetic 2011, Nis,
Serbia, September, 2011. 2. . Cundev, L. Petkovska, M. Popnikolova
Radevska, Analyses of electrical machines synchronous tupe based on
3d fem, ICEMA International Conference on Electrical Machines and
Applications, Harbin, China, Septebmer 1996.
HORIZONS
30
3. B. Arapinoski, M. Popnikolova Radevska, “Electromagnetic and
thermal analysis of power distribution transformer with FEM” ICEST
2010, Ohrid, R.Macedonia 2010. 4. Blagoja Arapinoski, Mirka
Radevska and Dragan Vidanovski, “ FEM Computation of ANORAD
Synchronous Brushless linear motor” Proceedings of the twelft last
international conference on elektrical machines, drives and power
systems ELMA 2008, 16-18 October 2008 Sofia, Bulgaria. 5.
M.Popnikolova Radevska, V.Sarac, M.Cundev, L.Petkovska“ Computation
of Solid Salient Poles Synchronous Motor Electromechanical
Characteristics and Parameter” MedPower 2002, Atns, Greece, MED
02/227, 4-6, November, 2002. 6. M.Popnikolova Radevska, V.Sarac,
M.Cundev, L.Petkovska “ Computation of Solid Salient Synchronous
Motor’s Parameters by 3D-Finite Element Method, EPNC’2002, Belgium,
Leuven July 2002., p.p. 111-114. 7. Mirka Radevska, Blagoja
Arapinoski, “ Computation of Electromagnetic Forces and Torques on
Overline Magnetic Separator”, Proceedings of XLII international
scientific conferennce on information, communication and energy
sustems and technologies, ICEST 2007, Ohrid 24-27 June, 2007. 8.
Mirka Popnikolova Radevska: “Calculation of Reactances of solid
salient poles synchronous motor by Finite element method”, ACEMP`
2004, 26-28 May, Istanbul, Turkey.
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GIS MODELLING FOR THE STRATEGIC URBAN DEVELOPMENT PLANING REGARDING
THE
REPUBLIC OF MACEDONIAFP
[email protected] H
[email protected]
ABSTRACT
The Geographic Information System (GIS) is an important component
in the information technology, and it has come to be a very
important component in many different areas as well. It is commonly
used in the areas of state interest in the managing, analysis and
planning sectors. The purpose of this paper is to develop a
conceptual design of strategic urban development planning in the
Republic of Macedonia in order to improve the manner of planning
and help competent authorities to make quick, accurate, efficient
and exact decisions. This paper shows cases of a concept of
strategic urban development planning for the Republic of Macedonia
by using GIS Modelling. This concept can also be applied to
business models, and it has been implemented and tested on a
business model regarding the influence of the socio-economic
standing on the healthy nutrition of the population in the Republic
of Macedonia. As a result to this concept, the way of planning is
improved and the basic perception of it as planning changes into
one of an applied science.
Key words: Geographic Information System, GIS, GIS_MSUDP, GIS
Modelling, business models.
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HORIZONS
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INTRODUCTION
The Geographic Information System (hereafter referred to as GIS),
is one of the most prospective information technologies and it
represents a complex computer technology based on data processing
with a few simple components: data input, data management, data
retrieval, data manipulation and analysis and output data. GIS
integrates spatial and other types of information into a single
system and thus provides a permanent framework for analyzing
spatial data. In this context, GIS can be understood as a hardware,
software and procedures system, organized to support the input,
manipulation, procedures and analysis of data, as well as the
modelling and output of spatial reference data.
Application of GIS in the urban and spatial planning in the local
and national government is default, and its application in the
economy has always been useful and helpful when making business
models, but some might find it strange to say that GIS can be
applied even in the field of medicine. Some examples of this are
using GIS to analyze the human body, using it in the public-health
research in epidemiology- from identifying risk factors to the
making of plans and scenarios for the spreading and prevention of
diseases. The latest use of GIS is its application in analyzing and
planning habits for healthy nutrition of the population by region.
A new GIS model is being prepared by a team of researchers from our
University on the impact of the socio-economic status of healthy
nutrition of the population in Macedonia. These examples are
sufficient to understand the role and application of GIS as an
information technology.
Nowadays, we use various systems to support urban development
planning such as the Planning Support System (PSS) and the Spatial
Decision Support System (SDSS), including GIS. These systems are
constantly being developed, and one can find similar SDSS and PSS,
when reading on the subject, whose key common goal is planning
support. They are used in several European countries and many other
countries throughout the world.
ANALYSIS OF THE USE OF GIS IN THE REPUBLIC OF
MACEDONIA
The analysis of the importance and use of GIS in Macedonian
municipalities was done over a period starting from 2006 till
today. In the period until 2006, USAID and EAR donated some GIS
software for some municipalities in Macedonia (ArcMap and ArcView
from ESRI) as an incentive for development. In order for it to be
used properly, staff trainings
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were held in the urban planning departments in each municipality,
where such projects were being conducted. In 2006, out of all the
municipalities in Macedonia, only 8% of used GIS software, and when
asked how important was the introduction of GIS in their
municipality, they responded as follows: 51% believe it is very
important, 42% find it very useful, 5% find it moderately useful,
and 2% find it unnecessary. When asked where they use GIS the most,
regarding municipality activities, the answers ranged from: 35% on
urban planning, 20% in utilities, 14% on landscaping and use of
urban land, 10% in traffic 9% in environmentalism, 5% in social
activities, 4% on tourism, 2% for energy facilities and 1% for
other activities.
During this research, a number of discussions were held regarding
the ways of strategic urban development planning, with the
competent experts (urban planning experts, analysts, planners), in
the municipalities in the Republic of Macedonia in major urban
areas such as Skopje, as well as in smaller municipalities. The
research conducted in the municipalities considered their
municipality development planning strategy, the spatial and
analytical data used, the reviewing of the data, the need for
digitization of the same and the importance of GIS.
At present the general state of GIS is quite different. In the
majority of municipalities in Macedonia, especially in the larger
ones, it is already introduced or is being introduced presently
(GIS hardware, GIS software, GIS training, digitalizing of spatial
data). The state of GIS usage in Macedonia for spatial data
analysis and planning, is as follows: at the moment, about 10% of
urban planners and other municipality competent experts (especially
in smaller municipalities) are using classical methods of planning,
and another percentage, about 35 to 40%, use computers and
software, as well as digitized data for the analysis and planning
of spatial and analytical data, not a different system. The third
and largest part of them, about 50 to 55%, are already using or
implementing GIS, as a system of hardware, software and procedures,
but haven’t built a good concept for strategic urban development
planning and the application of GIS is only in urban planning. The
lack of easily accessible, accurate and complete data in the
process of policy making and strategic planning, has led the
national governments of the Member States of the European Union to
take measures to overcome this problem. The 2007 Directive of the
European Parliament and the Council aims to establish an
Infrastructure for Spatial Information in the European Community
(INSPIRE). The National Spatial Data Infrastructure of the Republic
of Macedonia in accordance with INSPIRE.
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PHASES OF GIS MODELLING FOR STRATEGIC URBAN DEVELOPMENT PLANING IN
MACEDONIA (GIS_MSUDP)
During the last years, many planning support systems have
been
developed and are available to urban planners to assist them in
their work. Many of them focus on the design and evaluation of
possible solutions to spatial planning problems. The first advocate
of the use the of PPS systems was Harris (1989), later on Harris
and Batty (1993), who believed in using these systems to provide
tools, models and information which can be used for planning, with
the help of information technologies (such as GIS). With the
advances in GIS, PSS became an even more important component (Brail
and Klosterman, 2001; Geertman and Stillwell, 2003; Yehetal, 2006).
Similar to the PSS, the SDSS developed planning through scenarios
(MacDonald 1996). Other SDSS and PSS were developed and introduced
the STEPP, a strategic means for integrating environmental aspects
into the planning process (Carsjens, Lihtenberg, 2007). Some of
them included a multi-agent modelling system.
GIS can be used in many areas of the business environment, for the
most part with examples such as: a model for the effective planning
and management of taxes; a model for promoting/encouraging
investments; a land use planning and natural resources management
model; an energy recovery planning model; a healthy nutrition of
the population planning model and many others.
Based on all the research, a concept for GIS_MSUDP has been
developed. Thus, new GIS products (GIS models) are created and can
be used for strategic urban development planning. The following
phases are a part of the process of GIS modelling: Application
Domain, Spatial Reasoning, Logical Model and Physical Model.
Similarly, GIS_MSUDP is divided into five phases, as presented in
Figure 1. The important feature of this concept is that all stages
are represented by entities. The existence of connections between
the phases and science and scientific disciplines is certainly
requisite for modelling, but we could say that typically this block
diagram is dynamic and it depends on the created field patterns.
For example, a healthy nutrition of a healthy population planning
model requires the involvement of the science that deals with
healthy nutrition, such as Nutrition and food technology and
biotechnology.
The suggested GIS_MSUDP concept uses entities and relations for
each stage, just like the E-R models in data organisation, enables
good organisation and can be applied for planning in the Republic
of Macedonia.
GIS models that can be applied to GIS_MSUDP are:
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o Binary models: Logical model - expressions; Map overlay; Sitting
analysis; spatial query.
o Index models: allocation and standardization of the values of
spatial elements of each layer.
o Regression models: are used to calculate/estimate. These models
can be divided into two types: Linear regression, when all the
variables are numerical and logical, and Logistic regression, where
all the variables are binary.
o Process models: integrate existing knowledge about the processes
occurring in the environment (real world) presented in a set of
relations and equations for the quantification of processes.
UPHASE 1- DETERMINING THE GOALS –INTERESTS
Every business model is the lifeblood of society and its true
meaning comes through a particular goal and interest (Figure
2).
Determining the goals is in a direct relation to the business model
and is presented as an entity with two fields: Goal (Model,
Goal)
Figure 1: Phases of GIS modelling and its correlation with
science
HORIZONS
36
From a business perspective, the basic national interest are tax
incomes, but practical areas such as arable land, mineral rights,
forests, etc. concessionary, are also of great interest. A parcel
is a cadastral unit, which is the spatial extent of past, present
and future rights and interests in real estate. (FGDC, 1999).
Figure 2: Goals and interests of a business model The interest in
relation to the goal and is represented as an entity with two
fields: Interest (Interest, Goal)
UPHASE 2 – SPATIAL REASONING
It is necessary for GIS_MSUDP to go through the stage of spatial
reasoning, after the goal and interests have been determined. That
is the reality, the number of phenomena we see, that really exist
in all parts of their complexity, the defining of relationships,
observation by making decision trees, legislation, it all depending
on the business model. The better the real
world is presented in a formal system, the better the spatial
reasoning will be (Figure 3). In order to understand spatial
reasoning and spatial phenomena we can use the help of the
geo-information science and GIS.
Spatial reasoning is in conjunction with the goal and can be
presented as an entity with two fields: Visualization
(Visualization, Goal)
Figure 3: Spatial reasoning
37
UPHASE 3 – CONCEPTUAL MODEL
The conceptual GIS_MSUDP model is enlists defining all the
necessary items in the following order:
1. Defining the output data 2. Defining the input data 3. Defining
modelling strategies
o Methods and techniques o Data queries o Cartographic processing o
Map algebra o Mathematics and statistics
U1. Defining Output Data
What sets this phase apart is that it starts by defining the output
data. It is best to define the output as a planning result in the
beginning. It is in conjunction with the goal of the business model
and is represented as an entity with two fields: Output (Output,
Goal). The output is one of the important factors for strategic
planning, and apart from analytical data it may come in the form of
reports, thematic plans through spatial data in the form of GIS
layers (thematic layers) and in the form of maps, satellite
imagery, orthophoto images, etc.
U2. Defining Input Data To obtain the output data is necessary to
define all the required input
data. The input is in conjunction with the output and can be
presented as an entity of two fields: Input (Input, Output).
Digitalized input data is needed for a good analysis, such as a GIS
layer with cadastral locations, satellite imagery, orthophoto, GIS
infrastructure layers, maps and many others. Also included in the
input are databases and legislation data (laws, regulations). When
defining the input, it is required to define its source. The data
source can be presented as an entity of two fields: Data Source
(Source, Input)
Data sources can include: the municipality, the surveying office,
other state agencies and other sources. It is important to
emphasize the need for digitization of spatial data.
U3. Defining Modelling Strategies GIS Methods and techniques
GIS_MSUDP uses GIS methods and techniques which can be applied to
get certain output data which could be used in the strategic
urban
HORIZONS
38
development planning. They are is in conjunction with the input and
can be presented as an entity of two fields: Methods-Techniques
(Method, Input) Methods and techniques that can be applied are:
geo-referencing, vector of layers, transformation, etc. Data
Queries To receive the output data, one can use the data queries
provided by GIS.
Data queries in GIS software (ESRI) are made as a SQL Query. Data
queries can be presented as an entity of two fields: Queries
(Query, Input) Cartographic processing
This is a frequently used possibility offered by GIS, which allows
overlapping, buffering, etc. using multiple GIS layers to obtain a
new GIS layer. Cartographic processing can be presented as an
entity of two fields: Cartographic processing (Processing, Input)
Map Algebra
This is a useful feature that allows GIS to make calculations from
maps. Map algebra is in conjunction with the input and can be
presented as an entity of two fields: Map algebra (Algebra, Input)
Mathematical and statistical calculations
Mathematical and statistical calculations are always needed for
strategic planning and can be presented as an entity of two fields:
Mathematics - Statistics (Calculation, Input)
UPHASE 4 - LOGICAL MODEL
Based on all entities of the previous phases, a logical model has
been built and represented as E-R diagram (Figure 4). Three
conjunctions are the most characteristic: business model/goals,
output/goals and output/input. For easier application of the
proposed logical model, a relational database has been created with
the same structure. A separate Windows application has also been
created in conjunction with this database, to serve for editing and
displaying data in the logical model entities.
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Figure 4: Logical model
UPHASE 5 - PHYSICAL MODEL
The physical model is created on the basis of the logical model.
The next block diagram shows a physical model (Figure 5). The
designing and testing of the physical model is made with the
existing GIS software. This is done by using the ArcMap - GIS
software by ESRI, and ModelBuilder, a graphical tool for designing
models. To test the proposed GIS_MSUDP concept, a distinctive
business model has been selected: the socio-economic impact on
healthy nutrition in Macedonia, and new GIS model has been created
through the GIS software. This business model was chosen for two
reasons: to demonstrate the application of the proposed concept in
economy and the healthy food technology, and the second reason is
that there is a database at the Faculty of Technical and
Technological Sciences in Veles, created by our own ongoing
research on the socio-economic impact on healthy nutrition, dietary
habits and healthy food in general. The spatial data used includes
maps and satellite photos of Macedonia.
HORIZONS
40
Figure 5: Physical Model The proposed concept is built on the basis
of several principles. The first principle is for the model to be
as simple as possible, rather than building a complex model that
offers more options. It is better to build two simple models rather
than one that is more complex. The concept we propose is much
simpler in comparison with other concepts such as PSS and SDSS
systems that are complex and hard to manage and the possibility of
a mistake is far greater. The second
principle is to use easily accessible data. PSS and SDSS systems
require a lot of input data, that aren’t always necessary for
certain decisions and accessing them is very difficult due to great
time complexity. The process of digitalisation of spatial data,
necessary for input, represents a comprehensive process that on
occasion requires a long time. The third principle is to avoid
building an ideal model that would fully describe the real world in
a formal system. This is not possible. The more one goes towards
the idealization of the real world in a formal system, the more
complex and bigger this system gets. The proposed concept makes
visualising the real world in a formal way only in certain areas
important for planning, but does not go on into idealizing.
CONCLUSION
The concept of modelling for the strategic urban development
planning represented in five phases does not allow for
improvisation and mistakes. This will improve the way of strategic
planning and thus help the competent authorities from the
municipalities, government and the citizens to quickly, efficiently
and accurately make correct and timely decisions. The new GIS model
obtained by GIS modelling for strategic urban development planning
can affect the performance of municipalities, and generally the
national government in terms of urbanism, but also in all other
parts of their jurisdiction. The created GIS model for strategic
urban development planning, with software support, can be applied
from both a theoretical and an applicative aspect, thus making its
importance even greater.
Logical Model
41
This concept has been practically applied and tested on a business
model for socio-economic impact on a healthy nutrition in the
Republic of Macedonia. The modelling is done with an existing
software (by ESRI) thereby creating a new GIS model.
BIBLIOGRAPHY
1. Francis Harvey, A Primer of Fundamental Geographic and
Cartographic Concepts, The Guilford Press New York London, 75 -
290, 2008 2. Shivanand Balram, Canada, Suzana Dragicevic, Advances
in Geographic Information Science, © Springer-Verlag Berlin
Heidelberg, str. 9-152, 2010 3. Ian J. Bateman, Andrew A. Lovett,
Julii S. Brainard, Applied Environmental Economics, A GIS Approach
to Cost-Benefit Analysis, Cambridge University Press, 158-250, 2003
4. Shashi Shekar, Hui Xiong (Eds.), Encyclopedia of GIS, Springer,
Science + Buisiness Media, LLC, 30 -1300, 2008 5. Paul A. Longley,
Michael F. Goodchild David J. Maguire, David W. Rhind 6.
Geographical Information Systems and Science, 2nd Edition , UK John
Wiley & Sons Ltd,, Chichester, England, 21-500, 2005 7.
Atsuyuki Okabe, GIS-Based Studies in the Humanities and Social
Sciences, Taylor & Francis Group, 79 -300, 2006 8. Matthias
Ruth, Bruce Hannon, Modeling Dynamic Systems, Springer- Verlag New
York, 18- 325 2004 9. Stephan T.P. Kamps, Cecile Tannier, A
Planning Support System for Assessing Stragies of Local Urban
Planning Agencies, 1-9, 2008 10. Richard K.Brail, Planning support
Systems for Cites and Regions, Lincoln Institute of Land Policy, 85
– 99, 2008 11. ESRI, Introduction to ArcGIS I ESRI, 1-1 9-15, 2006
12. ESRI, Data Management in the Multiuser Geodatabase, ESRI, 1-1
15- 15, 2006 HUhttp://www.gis.comU HUhttp://www.esri.comU
HORIZONS
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43
TRANSPORT DEMAND FORECAST BY APPLYING SOFTWARE PACKAGE PTV Vision
VISUMFP
5 PF
Vaska Atanasova
Lidija Markovik
[email protected]
[email protected]
ABSTRACT
Forecast is scientific prediction of some phenomena that are of
great
importance to human society. For making forecast on transport
demand there are a lot of software packages and one of them is the
software package PTV Vision VISUM. Using this software package
forecast is made on transport demand for the city of Ohrid.
The goal of this paper is, by using concrete example for the city
of Ohrid, to present the possible ways for making forecast on
transport demand using an appropriate software package. Three ways
of making forecast on transport demand will be presented and the
steps for making forecast will be explained and followed with
figures in order to get a clear picture for the work in the
software.
Keywords: demand, forecast, software
INTRODUCTION
The forecast has always been a big challenge for scientists who
conduct research in the field of future prediction and for others.
The forecast of certain phenomena becomes a need which rises in all
spheres of human activity (economy, traffic, etc.). The biggest
reason for this is that the forecast provides planning. Traffic
planning is specificly planned process
P
HORIZONS
44
that determines necessary capacity to satisfy the needs of
transport in the future on some planned space.
To make a forecast in the software package PTV Vision VISUM, first
calculation on transport demand must be done. First to go to this
section transport network of the city must be defined, zoning of
the city must be made and connectors be set The most important part
in the procedure for making forecast is creation of the demand
model. After that, calculation on transport demand is made and
modal values will be obtained so that, values calculated by the
software. Next is the process of making forecast.
Forecast can be done in several ways. In the following text three
ways of making forecast will be presented in the software package
PTV Vision VISUM.
TRANSPORT DEMAND FORECAST: APPROACH 1
One of the ways of making forecast is when we take into account
population growth for 10 years. We made an estimation of growth and
this data will be entered into software.
Entering data for residents in the software can be made on the
following way:
In the software package we choose List Zones because the data
for
residents are written in zones. (Figure 1).
Photo 1: Input data for zones
Now appears a table by using the command “Copy list to
clipboard”
copy and we put them in Excel document. In Excel document we
enter
NATURAL SCIENCES AND MATHEMATICS, ENGINEERING AND TECHNOLOGY,
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45
estimated data for residents for all zones. We take the assumption
that for 10 years the number of residents will be increased for 50
percent. After we change values for residents we return back to the
table into the software using the command “Past content from
clipboard”.
Figure 2 represented location of the command “Copy list to
clipboard”, and Figure 3 represented the table in Excel
document.
Figure 2: Location of the command “Copy list to clipboard”
Figure 3: Input estimated data for residents in Excel
document
Using the procedure for calculation of transport demand we will
make
the forecast on transport demand for the city of Ohrid, for 10
years, for cars. In the software after residential data changes are
made the next commands
should be given: Calculate Procedures Operations Execute.
Obtained forecasted values are represented on Figure 4.
HORIZONS
46
Figure 4: Forecasted values for trips in the city of Ohrid, for 10
years
TRANSPORT DEMAND FORECAST: APPROACH 2
The second way for making forecast is with input growth
factors.
Forecast is done the following way:
From menu Overview in software we choose Matrices All
matrices Zone matrices 1Cn1. Now appears matrix for the
first purpose, than we choose Projection tool. Figure 5 represented
locations of aforementioned commands.
Figure 5: Display of second way of making forecast
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“Multiply with factor” should be selected. We choose Projection
is
execute For the entire matrix which means that the
calculations
will be made for all matrix, (Figure 6); It is activated
“Parameters for reference type “entre matrix” factor”
where we write 3, which means that for all matrix we define growth
factor 3, (Figure 7);
Figure 6: Activation of command for forecast
Figure 7: Defined growth factor
In “Projection is execute” can be chosen “Singly constrained
production” or “Singly constrained attraction” which means to
specify factor for production and attraction for each zone
separately,
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48
(Figure 8), also can be chosen “Doubly constrained (multi –
procedure)” which means that are taken into account factors for
attraction and production for each zone separately. These factors
are entered in the section from parameters where by simply clicking
on appropriated zone factor is entered. (Figure 9).
Figure 8: Input factors for production
Figure 9: Input factors for production and attraction
After entering these factors the procedure for obtained
forecasted
values is repeated.
TRANSPORT DEMAND FORECAST: APPROACH 3
The third way of making forecast on transport demand is by means of
forming a new matrix. This way of making forecast will be
described.
In the software we choose the following commands:
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Matrices Combination of matrices and vectors Ok. On this
way we create a new matrix. (Figure 10); Now, we select the newly
formed matrix and go on “Selection
Matrix” (Figure 11). Appears dropdown menu where we choose “Cn1”
and click “Ok”. (Figure 12);
Figure 10: Creating a new matrix
Figure 11: Location of command “Selection Matrix”
HORIZONS
50
Figure 12: Selection matrix
Now we define matrix parameters. We choose “Parameters”. In
dropdown menu choose “Create” and now here in
Matrix/Attribute/Constant we call the matrix “1Cn1”, and in
“Coefficient” we write 1.05. Click “”. (Figure 13);
After the preformed steps we assign the command “Execute”.
Figure 13: Defining the parameters of the newly defined
matrix
With this we represented another way of forecast.
DISCUSSION FOR WAYS OF FORECAST
The way of forecast depends on the type of travelling: local
traffic, transit traffic or origin – destination travelling. At
local traffic the most appropriate ways of making forecast is by
four step model, where generation of travelling depends on number
of inhabitants, number of employed places, purpose area and
similar, namely first way of forecast. Data for transit and origin
– destination travelling can be obtained through automatic counters
or through counting by cordon, using the method with
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writing registration plates. There are in external zones and there
are no generations of travelling. For transit traffic forecast is
made by second described way with average factors of growth. At
origin-destination travelling motorization growth rate must be paid
attention using the third way of forecast where coefficient is
inserted.
CONCLUSION
The forecast on transport demand is prediction on traffic volume
for some goal year. Forecast on transport demand includes trip
generation, trip distribution, and traffic assignment and modal
split. Using the software package PTV Vision VISUM are made trip
generation and distribution, assignment and forecast on modal
values. Unlike manual calculations, software calculations allows
more precision and accuracy in the work, but also it is a good
possibility to see all network of the city and forecast transport
demand for goal year. Step by step we were able to represent three
ways of making forecast on transport demand using appropriate
software package.
REFERENCES
1. Vaska Atanasova, 1. Traffic planning, Bitola, page, 1-5, 2010.
2. Vaska Atanasova, 2. Collection and analysis on transport data,
Bitola, page, 97, 2011. 3. Traffic study for Bitola town, Agreement
number 08-1124/1, from 03.06.2010, during one year (June 1 2010 to
June 2011). 4. PTV America, VISUM User Manual, Version 7.50. 2.
MODEL DESCRlPTlON. 2.1. Network Model. 2-3. 2.1.1. Transport
systems, April 2001. 5. General urban plan of the city of Bitola, I
book, Institute of Urban Planning and Design, LLC, Bitola, Bitola,
1999. 6. Towards sustainable urban transport policies,
Recommendation for local authorities, SMILE project, European
Commission, 2004. 7. White Paper 2011, Roadmap to a Single European
Transport Area – Towards a competitive and resource efficient
transport system, European Comission, - COM/2011/0144 final/
Brussels, 28.03.2011.
HORIZONS
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53
udc 004.455.021:[378.4.096:004(497.771)
“EXAM AS ADDITIONAL TRAINING” CONCEPT: TWO SEMESTERS EXPERIENCE OF
THE SPECIAL
TEST SOFTWARE’S IMPLEMENTATIONFP
[email protected],
[email protected]
[email protected]
ABSTRACT
In this paper, the “Exam as Additional Training” concept is
discussed
on the basis of two-semester experience at the University for
Information Science and Technology “St. Paul the Apostle” in Ohrid.
The software’s final version includes a client (.NET Windows form)
and a server (test- system knowledge base) part. The main algorithm
is based on random selection of a question: the position of the
question is selected randomly, the position of the answer is
selected randomly and sets of answers are selected in compliance
with the appropriate question-answer pair (i.e. one question – one
set of answers). From the evaluation point of view, students
describe this approach as user-friendly and effective for subject
skills’ improvement.
Key words: education, test, software, random algorithm.
P
HORIZONS
54
INTRODUCTION
At the present time, test technique is the dominant approach of the
students’ knowledge estimation (i.e., validation) in up-to-date
university education system. This technique is often used in
Bologna process which one implements the standard educational
schemes in different countries. Moreover, tests allow to minimize
the human factor’s impact on the test system functioning, and
organize the distance process. In addition, correctly crated test
may improve the student’s skills. It is clear that test can include
the solution of the simple task(s). Therefore, the appropriate
subject(s) uses to have the special complicated complex multistage
practical projects within. The quality of the test system depends
on the next main factors (author’s subjective point of view plus
[1-18]):
1. Questions. It is necessary to cover the maximal part of the
subject’s information. It is two main (in a fact, polar) directions
to realize this requirement – to formulate (i.e., form) the highest
possible quantity of questions or, alternatively, split all
questions in the appropriate sections (e.g., subject “Web
Application Development with Microsoft® .NET Framework 4” with
sections “Developing Web Form Pages”, “Developing and Using Web
Forms Controls”, “Implementing Client-Side Scripting and AJAX”,
“Configuring and Extending a Web Application”, “Displaying and
Manipulating Data”, and “Developing a Web Application by Using
ASP.NET MVC 2”). Indeed, students have the limited amount of
questions in both directions.
2. Answers. It is necessary to formulate set of the relative
answers to appropriate question. It is two main (in a fact, polar)
directions to realize this requirement – to formulate (i.e., form)
sets randomly (it is acceptable because all questions and answers
have a concern with one subject) or, alternatively, teacher creates
these sets by oneself. Second approach is most laborious, but the
most objective in the students’ knowledge estimation.
3. Users’ profiles (collection of personal data associated to a
specific user). This information can be formed a priori by
supervisor before the test or during the test automatically (e.g.,
short preliminary questionnaire). Then, this information can be
used for the appropriate set of questions’ forming. Practice shows
that students are adapted very quickly to this system, and use the
appropriate behaviour to achieve highest grade in an easiest
way.
4. In addition, it is preferably to use the random algorithms for
the positions’ selection of answers and questions.
Upon till now, a lot of research was conducted for the test system
development (e.g., [1-18]). Particularly, it has the concern with
the standardized educational testing (e.g., [1, 7, 12-17]). Some
very interesting
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educational test technologies’ were achieved (in a fact, they are
some kind of recommendations). As an example, we can admit the
following. Gibson E.J. (et al.) [1] did very good comparative
analysis of web-based testing and evaluation systems including the
explanation component’s usage. Kun Hua Tsai (et al.) [2] showed the
necessity of the content’s changing dynamically. Hema Srikanth (et
al.) [3] underlined the fault proneness’s analysis. Shuaiwen Xu (et
al.) [4] paid a lot of attention on the data’s coding because of
secrecy’s aspect. Jií Dostál [6] discussed the computer games’
usage in the educational process – in a fact, it is possible to
extend this idea to the “Exam as Additional Training” concept. Said
Khalifa (et al.) [7] showed the importance of the user interface’s
friendliness. Lilley M. (et al.) [8] were talking about the
development and evaluation of the test software prototype including
the problem of the unification. It is possible to realize some of
the above ideas, and avoid some problems if knowledge base is
located separately on some web resource, and it can be changed by
supervisor on time.
But, the standard test system has not yet developed. In authors’
point of view, the main solution is to develop unique educational
test software taking into account all possible experience. Two main
reasons are singled out subjectively:
1. Heterogeneous students’ society – it is necessary to take into
account the features of different countries sometimes. For example,
in Hong Kong, the British A-level has been accused of grade
inflation, and thus over time the HKAL has become more strictly
graded compared to its British counterpart [16]. In author’s point
of view, Hong Kong students were more motivated than their British
colleagues.
2. The commodification of education – commercial test systems are
closed even for description in general (e.g., Prometric Services:
Testing and Assessment [14]).
In addition, it is necessary to emphasize the large amount of
information in IT branch (information content is increased twice
every two years approximately). For example, total question
quantity was 313 for the “Server and Client Systems” subject
(University for Information Science and Technology “St. Paul the
Apostle” (UIST), Ohrid, Macedonia; 2011/2012 educational year
autumn semester). Information technologies are integral part of
modern society, and, therefore, it is necessary to take into
account the above fact. In this case, concept of additional
training which one is based on the special software is proposed:
students use similar test software for preparation and for exam
(indeed, the limited part of questions are shown contemporaneously
– for example, 100 questions out of total 300). This approach’s
main advantages are:
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56
1. Students have additional training about the whole course
information.
2. Respondents overcome easy the psychological difficulties within
the exam (the same software and information).
3. The answers and questions interpretation’s factor disappears.
The interpretation problem is in vogue in countries with strong law
system (e.g., USA, UK).
This concept can be called as “Exam as Additional Training”. This
paper main goal is to show the two semesters experience of the
special test software’s implementation within the “Exam as
Additional Training” concept in UIST (2011/2012 educational
year).
STAGES OF THE SPECIAL TEST SOFTWARE’S IMPLEMENTATION
Special test software were used in subjects “Programming
III”,
“Programming IV”, “Clients/Server Systems” (autumn semester), and
“Assembly Language Programming”, “Network Architecture” (spring
semester). The implementation’s stages and results are almost the
same for above subjects. Therefore, “Programming III” subject is
discussed forth mainly.
Second year students had 7 educational weeks every half-semester
for the “Programming III” subject (the course is based on the C#
programming language).
1 P
st P midterm exam (totally random approach: position of the
question is selected randomly; position of the answer is selected
randomly; alternative answers are selected randomly). Test
questions’ quantity was 90 (out of total 172). 72 students were
tested. Quality middle value was 94.94 %, minimum – 62 %, maximum –
100 %. Students’ subjective opinion: exam is very easy because the
right answer is easy selected through heterogeneous answers.
Special test software was developed in the Visual Studio 2010
environment [19] (C# programming language) – screenshot is shown in
Figure 1. It is necessary to admit that it works in real time mode
(in opposition to the appropriate note in [5]). Two security
features are realized within this software:
1. Defocus’s detection – to avoid the tips usage. 2. Special
checking phrase (it is written in the question textbox) – the
software authentication. One disadvantage was detected during the
implementation – it wasn’t
possible to start the software on the laptop of Chinese student, up
to 10
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students didn’t bring their laptops (additional university laptops
were used). It was fixed within next 2P
nd P stage of implementation – the test printing option
was added (i.e., students without laptops pass the usual paper
test).
Figure 1. Screenshot of the special test software for the 1P
st P midterm exam
nd P midterm exam (quasi random approach: position of the
question is selected randomly; position of the answer is selected
randomly; alternative answers are selected randomly; theoretical
and practical questions and answers were split by teacher). Test
questions’ quantity was 50 (out of total 99). 73 students were
tested. Quality middle value was 97 %, minimum – 78 %, maximum –
100 %. Students’ subjective opinion: exam is very easy because the
insufficient quantity of questions, the right answer is easy
selected through heterogeneous answers. Special test software was
improved – the test printing option was added, questions and
answers were split.
3 P
rd P stage – final semester exam (question oriented random
approach:
position of the question is selected randomly; position of the
answer is selected randomly; sets of answers are selected in
compliance with the appropriate pair question-answer (one question
– one set of answers)). Test questions’ quantity was 100 (out of
total 172). 16 students were tested (these students were not tested
early or wanted to do it once more; the rest of students used
middle value from midterm exams as a grade for final exam). Quality
middle value was 77.25 %, minimum – 42 %, maximum – 93 %. In a
fact, these results are more close to known systems [15-17] than
from
HORIZONS
58
previous stages. Students’ subjective opinion: question oriented
random approach test system reflects the students’ skills
adequately.
Special test software was improved – the option about the forming
of the answers’ sets, and the link to appropriate question were
added (screenshot is shown in Figure 2).
Last remark. The test system’s support experience showed the
necessity of the split of the software and knowledge base. It was
realized by the appropriate files hosting. Moreover, the files
usage’s possibility was added (in case of the Internet connection
absent) – see Figure 3. It allows the knowledge base’s correction
in real-time mode if necessary.
Figure 2. Screenshot of the special test software
Figure 3. Screenshot of the special test software –
loading the knowledge base’ regime (NA – Network
Architecture)
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SUMMARY TO THE VALIDITY AND GENERALIZATION OF THE PAPER’S
RESULTS.
SOME THOUGHTS ABOUT THE DEVELOPMENT’S PERSPECTIVES
This paper results’ analysis shows the main advantage of the “Exam
as
Additional Training” concept – adequate testing of the students’
skills. It is clear that the validity and generalization of the
experiment’s results are complicated task. The main reasons
are:
1. The sampled population forming is not possible. 2. Heterogeneous
non-steady psycho-physiological parameters of
student groups and the teacher’s subjective point of view.
Obviously the test system’s questions and answers are theoretical
in
general. Therefore, it is necessary to emphasize the practical task
during the semester lessons.
In a fact, the test software uses the Windows Forms technology of
user’s interface. It is necessary to admit that initial idea was to
realize Web- Forms technique (ASP.NET [19]) or cloud application
[20], but limited hardware resources (unstable Internet connection,
not every student has laptop) didn’t allow to do it. This is the
main perspective of this concept’s development.
CONCLUSION
In this paper, the two semesters experience of the special test
software’s implementation within the “Exam as Additional Training”
concept in UIST (2011/2012 educational year autumn semester) was
shown.
This concept is based on the question oriented random approach:
position of the question is selected randomly; position of the
answer is selected randomly; sets of answers are selected in
compliance with the appropriate pair question-answer (one question
– one set of answers). Special test software was developed in the
Visual Studio 2010 environment (C# programming language). Test
results are very close to known systems (e.g., IB Diploma Programme
[15], GCE Advanced Level [16], Abitur [17]). Students’ subjective
opinion: question oriented random approach test system reflects the
students’ skills adequately. Obviously, the test system’s questions
and answers are theoretical in general. Therefore, it is necessary
to emphasize the practical tasks during the semester lessons.
As a main prospect, the secure improvement is important question
mostly because of the feature of .NET technology (it is possible to
read free
HORIZONS
60
some information in .exe file – in a fact, this file includes the
IL-code, not binary machine code).
BIBLIOGRAPHY
1. E.J. Gibson, P.W. Brewer, A. Dholakia, M.A. Vouk, D.L. Bitzer. A
comparative analysis of Web-based testing and evaluation systems.”
Proc. 4th WWW conference, Boston, 1995. 2. Kun Hua Tsai, Tzone I.
Wang, Tung Cheng Hsieh, Ti Kai Chiu, Ming Che Lee. Dynamic
computerized testlet-based test generation system by discrete PSO
with partial course ontology. Expert Systems with Applications
Journal, Vol. 37, Issue 1, January 2010, pp. 774-786. 3. Hema
Srikanth, Sean Banerjee. Improving test efficiency through system
test prioritization. Journal of Systems and Software, Vol. 85,
Issue 5, May 2012, pp. 1176-1187. 4. Shuaiwen Xu, Xiaoming Wang.
Network test system design and implementation. Proc. 2012
International Conference on Future Electrical Power and Energy
Systems, Published by Elsevier, pp. 694-699. 5. Sun Hong-mei, Jia
Rui-sheng. Research on the analysis and design of general test
database management system. Proc. 2012 International Workshop on
Information and Electronics Engineering (IWIEE), Published by
Elsevier, pp. 489-493. 6. Jií Dostál. Instructional software and
computer games – tools of modern education. Journal of Technology
and Information Education, 1/2009, Vol. 1, Issue 1, pp. 23-28. 7.
Said Khalifa, Chris Bloor, Walter Middelton, Chris Jones.
Educational computer software, technical, criteria, and Quality.
Proc. 2000, Information Systems Education Conference, pp.34-42. 8.
Lilley M., Barker T., Britton C. The development and evaluation of
a software prototype for computer-adaptive testing. .Computers
& Education Journal, August 2004, Vol. 43, Issue 1/2, pp.
109-124. 9. The Joint Committee on Testing Practices (JCTP): Code
of Fair Testing Practices in Education.
http://www.apa.org/science/programs/testing/fair- testing.pdf 10.
Torin Monahan. Just Another Tool? IT Pedagogy and the
Commodification of Education. The Urban Review, Vol. 36, No. 4,
December 2004. http://torinmonahan.com/papers/Just_another_tool.pdf
11. Torin Monahan. Built Pedagogies & Technology Practices:
Designing for Participatory Learning.
http://torinmonahan.com/papers/pdc2000.pdf 12. Torin Monahan. The
Rise of Standardized Educational Testing in the U.S.: A
Bibliographic Overview. http://torinmonahan.com/papers/testing.pdf
13. Diane Ravitch. The Uses and Misuses of Tests.
http://www.dianeravitch.com/uses_and_misuses.pdf
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HORIZONS
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63
7 PF
Jordan Martinovski
[email protected]
[email protected]
ABSTRACT
The introduction of computers into the educational process in
R.
Macedonia is a part of a fundamental transition from traditional
forms of learning to new forms that focus on quality teaching
techniques. GeoGebra is interactive software designed for teachers
and students that combines geometry, algebra, analysis and
application. The objective of this research is to analyze the
applicability and acceptance of GeoGebra in primary schools.
Method: Research was carried out on two groups of elementary school
students on specific topics algebra and geometry. One group was
taught in the classical way; the other using GeoGebra. Both groups
of students were tested and the results summarized. The results
have shown that Geogebra increases the students’s ability to
understand the content of mathematics, improve their learning,
encourage thinking and develop creativity.
INTRODUCTION
GeoGebra is a free of charge software for learning mathematics, and
it
is written in Java which makes it available for several platforms.
With the development of software for visualization of mathematical
problems, especially by using GeoGebra, fully translated in
Macedonian, it makes it very easy for students to master the
material by attracting and retaining their
P
HORIZONS
64
attention. GeoGebra is interactive and dynamic geometry software.
Solving tasks in GeoGebra is done using constructions which can be
made in a very simple manner by using points, vectors, segments,
lines, segments, polygons, inequalities, conic sections, implicit
polynomials and functions. GeoGebra has the ability to use
variables for numbers, find derivatives and integrals of functions
and commands such as Root or Extremum as well as making conjectures
and proving geometric theorems.
LEARNING WITH GEOGEBRA
The research has been conducted on 124 students from seventh-grade
who were divided into two groups of 62 students and were taught the
Pythagorean theorem and square of a binomial (curriculum for
seventh- grade education implemented in eight-year elementary
school and curriculum for eight-grade education implemented in
ninth-year elementary school).The first group of 62 students were
taught the Pythagorean theorem and the square of a binomial in the
traditional way, by using a textbook, and the second group of 62
students were taught by using GeoGebra.
When explaining the Pythagorean Theorem and the square of a
binomial using GeoGebra, the geometric constructions and algebra
window are shown at the same time, including software tools needed,
which contributes to better visualization as one of the main
differences from traditional teaching. The consequently created
GeoGebra products (for the Pythagorean Theorem and the square of a
binomial) are uploaded on video and Wiki pages. This enables
students to use them during the learning of the material.
GeoGebra uses the following concept for the Pythagorean Theorem: A
right-angled triangle is drawn and then a square is traced out for
each cathetus and the hypotenuse. The area of all squares is then
calculated (Figure 1). The calculations show that the area of the
square whose side is the hypotenuse (the side opposite the right
angle) is equal to the sum of the areas of the squares whose sides
are the two legs (the two sides that meet at a right angle). This
proves the Pythagorean Theorem in a striking and simple way. It is
important to emphasize the interactive learning and repetition of
the material, especially in the case of the Pythagorean Theorem,
one can change the values of the sides of the triangle by dragging
the vertices A and B, and can make conclusions from the obtained
results and visual demonstration.
With GeoGebra the following concept is used to determine the square
of a binomial: we draw a square one side equalling “a+b” which is
divided into two smaller squares and two smaller rectangles as
shown in Figure 2.
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The area of the bigger square P= (a+b) P
2 Pis equal to the sum of the areas of
the two smaller squares PR1R=a P
2 P, PR4R=bP
2 P and both rectangles PR2R=ab, PR3R=ab, i.e.:
P=PR1R+PR2R+PR3R+PR4R (a+b) P
2 P= P
2 P+2ab+bP
2 P. This helps prove the square of a
binomial using geometry in an easy and clearly visible way. By
dragging any of the marked points the values of the sides a and b
are changing, and thus enabling the students to make conclusions
for the square of a binomial from the obtained results and visual
demonstration. This interactive learning helps students to make
conclusions by themselves.
Figure 1: Pythagorean Theorem in GeoGebra
Figure 2: Square of a binomial in GeoGebra
HORIZONS
66
TESTING AND RESULTS
The two groups of students have been given the same problems
with
the Pythagorean Theorem and the square of a binomial. The problems
were: 1. Calculate the length of diagonal of rectangle with sides
a=3 cm and
b=4 cm. How much the diagonal of the rectangle will increase if the
length of the sides of the rectangles is doubled?
2. Calculate the length of the side of isosceles triangle with base
12 cm and height 8 cm.
3. Write the following polynomial: (a+2)P
2 P + (a+8)P
2 Pin a standard form.
4. How much the value of the square of binomial (a+b) P
2 P will increase if
the values of “a” and “b” are doubled? 5. Compute 55P
2 Pby using the formula for square of binomial.
The testing results can be seen in Table 1 and on the chart in
Figure 3. It can be seen in Table 1 and Figure 3 that the students
of Group 2 who have studied with the help of GeoGebra have
successfully mastered the material and have achieved better
results. The average success of this group is 4.42 which, is above
average compared to an average of 3.89 from the students of Group 1
who studied using the traditional way. It is notable that the
number of students with sufficient and insufficient success has
been significantly reduced and more precisely from the 10 who
studied using the classical way to just 2 students.
Table 1: Statistical Testing Results
Group 1 - Traditional
Learning
Number of
students Percentage
Number of
students Percentage
5 27 44% 37 60% 4 13 21% 16 26% 3 12 19% 7 11% 2 8 13% 2 3% 1 2 3%
0 0%
Total: 62 62
GPA: 3,89 4,42
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CONCLUSION
The research has shown that using Geogebra in the educational
process in primary schools enables greater success in mastering
mathematics. It is interesting that the part of students who find
solving mathematical problems a major difficulty have greater
success when using GeoGebra. Based on the results of this research
it can be concluded that Geogebra enhances the way of thinking
while solving