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Submit Paper / Call for Papers
Journal receives papers in continuous flow and we will consider articles
from a wide range of Information Technology disciplines encompassing the most
basic research to the most innovative technologies. Please submit your papers
electronically to our submission system at http://jatit.org/submit_paper.php in
an MSWord, Pdf or compatible format so that they may be evaluated for
publication in the upcoming issue. This journal uses a blinded review process;
please remember to include all your personal identifiable information in the
manuscript before submitting it for review, we will edit the necessary
information at our side. Submissions to JATIT should be full research / review
papers (properly indicated below main title).
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Journal of
Theoretical and Applied Information Technology
July 2021 | Vol. 99
No.13 |
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Title: |
A MULTIMODEL INTERNAL MODEL CONTROL APPROACH BASED ON NEURAL NETWORK |
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Author: |
AMIRA SLIMANI, AYACHI ERRACHDI, MOHAMED BENREJEB |
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Abstract: |
This paper proposes a multimodel internal model control approach based on neural
network, using a variable learning rate, for a nonlinear discrete system. The
multimodel controller consists of two blocks : an inverse model and an internal
model. Each block is based on neural network can be got directly, which
simplifies the control law design and analyses greatly. Meanwhile, the way of
model switch is developed based on neural network decision. This approach avoids
the complex calculation when adjusting the controller parameter and overcomes
the switch operation. By applying the proposed approach to a nonlinear system,
simulation results demonstrate that the strategy has advantage of multimodel
internal model control and could achieve better system performance than the
classical one. |
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Keywords: |
Multimodel Control, Internal Control, Neural Network, Nonlinear System, Learning
Rate |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
APPROACHES TO CYBERBULLYING DETECTION ON SOCIAL NETWORKS: A SURVEY |
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Author: |
ZAINA ALSAED, DERAR ELEYAN |
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Abstract: |
Cyberbullying is a continuously growing issue in the insecure environment of
social media networking platforms. It is common mostly among teenagers. To
achieve successful cyberbullying prevention, appropriate detection of
cyberbullying cases must be applied. This could be done through the application
of intelligent techniques to identify mistreating behaviors. Nevertheless,
automatic identification of potential online cyberbullying cases needs many
requirements, especially with the huge loads of available information uploaded
on the web. The primary objective of this paper is to highlight cyberbullying
detection techniques so that it contributes positively to control bullying
practices on social media. Its approach was reviewing existing attempts of
cyberbullying detection using machine-learning algorithms and hence recap each.
Overall, the outcomes are bright; however, they still have an opportunity to get
better. |
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Keywords: |
Cyberbullying, Machine learning, Social Networking |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
ATMOSPHERIC CORRECTION OF LANDSAT-8 / OLI DATA USING THE FLAASH ALGORITHM:
OBTAINING INFORMATION ABOUT AGRICULTURAL CROPS |
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Author: |
A.E.YERZHANOVA, S. YE.KERIMKHULLE, G.B.ABDIKERIMOVA, M.MAKHANOV, S.T.BEGLEROVA,
ZH.K.TASZHUREKOVA |
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Abstract: |
The article presents studies and proposes methods for determining the objects of
the underlying surface such as soil, water, soil moisture, agricultural crops
and their diseases, weeds, and monitoring plant growth over vegetative periods
based on the analysis of the spectral brightness coefficient of space images.
Recognition of plant species, soils, and territories from satellite images is an
applied task that allows you to implement many processes in agriculture and
automate the activities of farmers and large farms. These studies are aimed at
creating a scientific and methodological basis for an information system in the
form of a computer application on gadgets. The main tool for analyzing satellite
imagery data is the clustering of data that uniquely identifies the desired
objects and changes associated with various reasons.
Based on the data
obtained in the course of experiments on obtaining numerical values of SLC,
which are published in the press, the regularities of the behavior of the
processes of reflection of vegetation, factors that impede the normal growth of
plants, and the proposed clustering of the spectral ranges of wave distribution,
by which the type of objects under consideration can be determined. Recognition
of these causes through the analysis of the spectral brightness coefficient of
satellite images will allow creating an information system for monitoring the
state of plants and events to eliminate negative causes. SLC data is divided
into non-overlapping ranges, i.e., they form clusters reflecting the normal
development of plant species and deviations associated with negative causes. If
there are deviations, then there is an algorithm that determines the cause of
the deviation and proposes an action plan to eliminate the defect.
To
accomplish this task, the dependence of the state of plants on the types of
soils, their moisture content, the identification of weeds, the detection of
diseases, and the lack of mineral and organic fertilizers were taken into
account. Several negative causes associated with plant diseases require ground
monitoring due to the lack of experimental data on spectral analysis of these
diseases. It should be noted that the distribution of brightness spectra depends
on the climatic and geographical conditions of the plant species and is unique
for each region. This study refers to the Northern Kazakhstan region, where
crops are grown.
In all types of space and ground monitoring of plant growth,
measures are proposed to eliminate negative causes. |
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Keywords: |
Spectral Brightness Coefficients, Earth Remote Sensing, ERS, ENVI, Landsat-8,
Atmospheric Correction, FLAASH, Wavelength, Band |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
AUDIO BASED DANGEROUS EVENT RECOGNITION IN INDOOR ENVIRONMENT |
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Author: |
ZHANDOS DOSBAYEV, PERNEKUL KOZHABEKOVA, GULBAKHRAM BEISSENOVA, ZHANAR
AZHIBEKOVA, ZHALGASBEK IZTAYEV, VENERA NAKHIPOVA, MUKHTAR KERIMBEKOV, AIGERIM
SEITKHANOVA, NURBEK KONYRBAYEV, GAUKHAR SEIDALIYEVA |
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Abstract: |
In recent years, automatic systems that control the daily activities of a person
are becoming more common. Their main purpose is to ensure civil security, which
is achieved through surveillance in public places and the recognition of
potentially dangerous situations. Research in the field of automatic
surveillance systems is mainly focused on the detection of events using video
analytics. In turn, acoustic monitoring can be used as an additional source of
information, and being integrated with video surveillance systems, increase the
efficiency of event detection. Audio analysis has features that in some
situations allow you to solve monitoring tasks more efficiently than video
analysis systems, such as: a) low computational requirements, b) independence
from visibility conditions (for example, the presence of fog or insufficient
lighting). In this paper, we propose audioevent detection system using audio
analysis applying machine learning techniques. |
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Keywords: |
Audio Events, Detection, Classification, Machine Learning, Security. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
COMPLETE KAZAKH HANDWRITTEN PAGE RECOGNITION USING START, FOLLOW AND READ METHOD |
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Author: |
RUSLAN JANTAYEV, SHIRALI KADYROV, YEDILKHAN AMIRGALIYEV |
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Abstract: |
In this article we consider end-to-end full page Handwritten Text Recognition
for offline Kazakh text images written in Cyrillic alphabet using Fully
connected CNN and bidirectional LSTM. The model performs training of text
segmentation and recognition jointly using a new Kazakh text images dataset,
named Kazakh Handwritten Dataset (KHD). The novel method, which we introduce,
uses three steps: Start, Follow and Read (SFR). The proposed model makes use of
Region Proposal Network in order to find the starting coordinates of lines in
the page. For the case when lines are not straight, we introduce a method that
pursues text lines until the end of it and prepare it for the last recognition
step. The SFR model works for Russian language as well since Russian alphabet is
a subset of Kazakh alphabet. The experimental analysis shows that on average the
model provides 0.11 Character Error Rate. |
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Keywords: |
Computer Vision, HTR, CNN, Bidirectional LSTM, Kazakh Handwritten, Document
Processing, Text Line Follower, Text line cutting. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
INTELLIGENT SUPPORT IN MAKING TECHNICAL DECISIONS IN THE ENTERPRISE INFORMATION
INFRASTRUCTURE |
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Author: |
A.B.ZAKIROVA, E.A.BASINYA, M.A.KANTUREYEVA, A.ZH.AKHMETOVA, ZH.B.AKHAYEVA |
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Abstract: |
Today, intelligent information technology can act as a catalyst for the
development of almost all areas of society. The article discusses the current
state of affairs in the field of management and maintenance of the information
infrastructure of the enterprise. The problems of system and network
administration of technical objects and systems are described. The shortcomings
of the existing systems of intellectual support for engineers involved in their
support are described. The method of providing intellectual support when making
technical decisions in the enterprise’s information infrastructure, operating on
the basis of the TCP / IP protocol stack and the operating systems of the
Windows and Linux family, is submitted for review. The scientific novelty of the
proposed solution lies in the intellectual support in making technical and
managerial decisions based on previous experience and the ability to predict the
state of the system. Unlike existing approaches, safe forecasting of the
reaction of a technical object to certain external, internal or local influences
and changes, including those set forth in a declarative form, is provided. The
continuous operation of the object during its research and forecasting with the
possibility of applying influences / changes to the real system with successful
iterative testing is ensured. Optional parallelization of testing and research
processes in an isolated and safe environment is performed. The knowledge base
of system and network administration of the enterprise information
infrastructure is being formed, which allows solving complex and complex
incidents. These provisions are achieved by creating many model objects in
stealth mode (for example, by a volume shadow copy service) in an isolated
environment based on the ESXI hypervisor with virtual segmentation of VLAN
traffic and technology for automatic deployment and configuration of user and
server solutions (including Ansible). The method is integrated with the
previously developed by the author system of intellectual adaptive management of
the enterprise information infrastructure. |
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Keywords: |
Intellectual Support, Forecasting, Automation Of System And Network
Administration, Shadow Copying, Cloning, Model Objects, Hypervisor, Feedback,
Intelligent Adaptive Management, Knowledge Base. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
FRAMING ANALYSIS OF KAMALA HARRIS AS VICE PRESIDENT CANDIDATE IN MIDDLE EAST
ONLINE MEDIA (AL ARABIYA & AL JAZEERA) APER TITLE HERE |
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Author: |
RAMANOV BAREZKI, MUHAMMAD ARAS |
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Abstract: |
This research aims to analyze the mass media’s framing of Senator Kamala Harris
as Vice President Candidate. The focus of this research is to compare Kamala
Harris coverage by Alarabiya.net and Aljazeera.com based on Robert N. Entman’s
framing analysis and qualitative approaches. The data was obtained from online
media news that appeared between August and October 2020. Both online media have
been limited by news numbers; Alarabiya.net is four articles, and Aljazeera.com
is six articles, and we only chose news written by their own journalist. The
results of this study indicate that each of the two media has its own way of
delivering news related to the figure of Kamala Harris. Alarabiya.net news
coverage is more neutral by constructing Kamala Harris as Joe Biden’s running
mate and they more focused on the US Election. Meanwhile, AlJazeera.com featured
many articles related to Kamala Harris’s background and aggressively criticized
Donald Trump’s leadership. |
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Keywords: |
Kamala Harris, Framing Analysis, News Media, US Election |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
INNOVATIVE WORKING BODIES OF CONSTRUCTION PRODUCTION MACHINES WITH CYCLOIDAL
MOTION |
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Author: |
ONGDABEK RABAT, ASKAT KABASHEV, ALINA SALMANOVA, ULBALA MURZAKHMETOVA, ALTYNGUL
TUSSUPOVA, AKBOTA IZEMBAYEVA, MIREY NURGALIYEVA |
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Abstract: |
The paper presents new (innovative) designs of the working bodies of
construction machinery with cycloidal movement, developed by the authors.
Structural solutions of machines are obtained using the properties of cycloidal
curves and cycloidal bodies of constant width in working bodies that perform
complex (cycloidal) movement. The use of mutually bending satellite curves in
the working bodies of construction machinery and their cycloidal movement made
it possible to obtain rational geometric shapes of the working bodies with the
minimum possible specific energy consumption of the working process and to
expand the technological capabilities of the machines.
In the working body of
the machine, the properties of mutually bending cycloidal curves and bodies of
constant width are used. The cross-section of the working body is a flat
triangular shape. The points of this figure, when rotating around two parallel
axes, describe curved lines-hypocycloids with rectilinear branches. This feature
of the movement of the working bodies along the inter-envelope curves is used in
the slitting machine. It allowed you to get the minimum possible energy
consumption for the workflow. The cutting machine with cycloidal movement of
working bodies exceeds the performance of other basic machines in terms of
productivity, specific energy consumption for the working process and has
significantly smaller dimensions and weight, due to the cycloidal movement. |
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Keywords: |
Construction Machinery, Productivity, Cycloidal (Complex) Movement, Working
Body, Hypocycloid, Planetary Gear, Central Gear, Carrier, Satellite, Rotor. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
NEURAL NETWORK MODEL OF COUNTERING NETWORK CYBER ATTACKS USING EXPERT KNOWLEDGE |
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Author: |
IDEYAT BAPIYEV, GAUKHAR KAMALOVA, FARIDA YERMUKHAMBETOVA, AIMGUL KHAIRULLINA,
AKMARAL KASSYMOVA |
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Abstract: |
Research in the field of countering cyberattacks on network resources of
information systems has shown that most modern neural network models are focused
on learning using statistical data. Such models are not sufficiently adapted to
recognize new types of network cyberattacks. To eliminate this drawback, it was
proposed to form a training sample using expert knowledge presented in the form
of production rules. It was determined that among the classical types of neural
network models, the most suitable for such training is a probabilistic neural
network. On the basis of this network, an original neural network model was
created, its structure and software were developed. The use of the developed
model makes it possible to increase the recognition efficiency and expand many
types of network attacks, the characteristics of which are not presented in
statistical data. Another important advantage of the developed model is the
information content of the output signal, which is sufficient for flexible
setting of protective measures. |
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Keywords: |
Neural Network Model, Recognition Of Cyber Attacks, Model, Production Rule,
Expert Knowledge, Probabilistic Neural Network. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
REUSING OPEN DATA: AN EXPLORATORY STUDY IN ECUADOR |
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Author: |
DANILO PÁSTOR, IVONNE E. RODRÍGUEZ, ALEJANDRA OÑATE-ANDINO, GLORIA ARCOS-MEDINA |
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Abstract: |
The objective of this paper is to carry out an exploratory study on the reuse of
open data in Ecuador. For this purpose, thirteen open data portals initiatives
in the country have been selected, which were then analyzed based on the MELODA
metric, in order to determine the degree of reuse of the portals through five
dimensions: Legal, Technical Standards, Information Accessibility, Data Model
Sharing, Geolocated Information, and Real-time Information. In this way, the
average reuse level of 29.62%, was obtaining, corresponding to a basic reuse.
The Real-time information dimension had the lowest rating, while the Technical
Standards dimension reported the highest. In turn, of the thirteen active open
data portals in Ecuador, 69% reported a basic reuse level and 31% a limited
reuse level. |
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Keywords: |
Open Data Reuse, Open Data portals, MELODA, Open Government Data, Open
Government |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
NO HAMBURGERS FOR THE ELDERLY? BASED ON REGRESSION ANALYSIS METHOD |
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Author: |
MENG JIAJIA, OOK LEE |
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Abstract: |
Since the 21st century, China has become a super aging society, and researchers
have focused on societal burdens from a problem perspective, as well as new
market opportunities attuned to the perspectives and needs of the elderly,
creating a new mode of life, smart products and services. However,product
development trends indicate a need for adaptation, affordances, and an inclusive
design approach. This paper presents a case study of elderly ordering meals in
the hamburger shop through the self-service ordering machine, aims to research
the differences in user interface requirements between the elderly and young
people by combining the consumption characteristics of the elderly learned from
the literature. In this paper, I issued the questionnaires to get the
evaluations of the elderly and young people on the satisfaction of the design of
the hamburger shop's self-service ordering interface, and further concluded the
differences in user interface requirements between the elderly and young people
in the same scenario with some practical suggestions after finding out the
difference in operation interfaces for the elderly and young people through
linear regression method. We hope that this paper will draw the attention of the
market and merchants to make optimization, thus improving the dining experience
and the user proportion of the elderly in the restaurant market. |
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Keywords: |
The Elderly; Super Aging; Interface Design; Elderly UI;Linear Rregression
Analysis; Kiosk |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
MINING OF THE EXTRACTED SOCIAL NETWORK |
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Author: |
MAHYUDDIN K. M. NASUTION |
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Abstract: |
Social network mining (SNM) has become one of the main themes in the Semantic
Web agenda. Social network can be extracted from different sources of
information, and the resources – like documents/web pages - was growing
dynamically not only require a flexible approach, but need behavior recognition.
Each social network has the resources, but the relationship between resources
and information sources requires explanation. It is SNM and it is not social
network analysis, but it is possible to bridge social network and social network
analysis. There is the behavior of resources of social network, and this article
is to explore them by using the concept of clusters in theory and the
statistical computation for conducting an experiment. That is using
multiple-regression, where with applying graph as representation of relation
between resources the growing the resources depend on each other. In a
conclusion, there is a positive effect on the relations between resources for
growing the social networks, where the behavior also indirectly indicates the
extraction of engagement for the communities in the extracted social network. |
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Keywords: |
Superficial Method, Stand-Alone Cluster, Multiple-Regression, Association Rule,
Positive Effect, Research Group, Social Network Analysis. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
DEVELOPMENT OF IMPROVED SPEED AES BASED ON KEY DEPENDENT INTRA-ROUND OPERATIONS |
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Author: |
SANDEEP K. SHELKE, SANJEET K SINHA, GOVIND SINGH PATEL |
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Abstract: |
The modern day technological evolution in field of communication, improves our
life to significant extent. Most of recent evolution, in communication field is
governed by internet; on the other hand, the use of internet puts big concern
for data security. The crucial applications like surveillance, medical or
military; demands secured image transmission & storage. In order to provide
security to the images during its transmission, multiple techniques have been
developed, in last few decades. AES (Advanced Encryption Standard) is commonly
used technique for image security. This work introduces, the development of AES;
by making all the intra-round transformations (Sub-byte, Shift row & Mix
column); as a key dependent transformations, this key dependency of intra-round
transformations, results modification in the values of propagation & correlation
as, 2-150 and 2-75 respectively; these value ensures protection against
differential & linear attacks. For the development of proposed algorithm, c to
VHDL compilation framework based on loop unrolling technique is used. This loop
unrolling technique provides higher degree of parallelism for reconfigurable
architecture causing the significant increase in the speed of image encryption &
decryption. So the proposed AES provides high degree of security, that too at
high speed but with cost of larger area requirement. |
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Keywords: |
Linear Attacks; Differential Attacks; Image Security; Advanced Encryption
Standard; Loop Unrolling Technique. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
THE EFFECT OF DIGITAL GAP IN THE PANDEMIC SITUATION (CASE STUDY: HIGHER
EDUCATION STUDENTS) |
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Author: |
TANTY OKTAVIA, DIKA IMANULLAH THALIB, SONIA TIARA, NATHANIEL JASON ALVIANJI,
DENNY WINGSTOND, STEVEN EZEKIEL WIRAWAN, ADRIEL PERDANA HENDRAPUTRA |
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Abstract: |
The digital gap is one of the factors that could interrupt the learning process
in the higher education institution. Both internal and external factors have
large impact on higher education students. Since many students’ inability to
learn with new learning process, that is not affected by their competence or
skills, but by their inability to use the required technology. In accordance
with the current pandemic situation, it prompts the organization to transform
its business process more technology savvy, including in the higher education
institution as an organization that responsible to educate student. The
phenomenon of Covid 19 pandemic drives many studies to check the readiness of
digital transformation. The most important factor for higher education can adapt
with this situation is that they must analyse the current condition to shift
into the new digital learning process. Therefore, this study focusses to find
out the biggest factor in the scope of digital gaps from student side. This
study uses various data description analysis techniques to examine the
hypotheses. The result shows that most students encounter problems due to their
inability to adapt to certain digital technology tools, and their limited
financial capacity seems to affect their learning process. Other data shows that
online learning is not as effective as offline learning due to the student's
needs to learn both the new digital technology platform and the necessary
materials. |
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Keywords: |
Digital, Gaps, Education, Pandemic |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
DESIGN AND EVALUATION OF A MOBILE 3D ARCADE GAME WITH MESH CLIPPING |
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Author: |
YOUNGSIK KIM |
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Abstract: |
To cut a polygon of the 3D mesh object from a computer, it is necessary to
create a plane using the plane equation, calculate the distance between the
point and the plane, and calculate the intersection point and the plane. In this
paper, we propose a 5-step mesh clipping method to cut polygons in a 3D game.
The proposed method consists of (1) plane generation, (2) point separation
according to the distance between vertex and plane of polygon, (3) intersection
of plane and polygon, (4) separation of the triangle using intersection, and (5)
creation of cross-section. The proposed method is applied to the mobile 3D
arcade games. Experiments are conducted to measure the variation of the frame
rate (Frame Per Second (FPS)) according to the type of objects displayed during
the game. Moreover, computer experiments have verified that the mesh clipping
effect is natural and accurate. It can be confirmed that noticeable frame
deterioration does not occur when the cube is cut. On the other hand, if they
have a monster with a more significant number of triangles and vertices, they
may notice a slight frame drop. Also, we confirmed that the effect of the
degradation of rendering speed on game progress is insignificant when applying
the proposed mesh clipping to 3D games. |
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Keywords: |
Mobile 3D Arcade Game, Mesh Clipping, Computer Simulation, Rendering Speed,
Unity3D |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
CUSTOMER MOTIVATION ANALYSIS ON RETAIL BUSINESS WITH OCTALYSIS GAMIFICATION
FRAMEWORK |
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Author: |
FITRI MARISA, SHARIFAH SAKINAH SYED AHMAD, ZERATUL IZZAH MOHD YUSOH, DODIK
JATMIKA, TITIEN AGUSTINA, WIWIN PURNOMOWATI, ERRI WAHYU PUSPITARINI |
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Abstract: |
Small and Medium Enterprises (SMEs) are an important component of the country's
economy, but there are still many challenges to be resolved. Some of the common
problems of SMEs included limited marketing and service management problem. In
the service management problems, it is also important to examine how the
customer impression of the services and products offered, therefore, it can be
evaluated how the product opportunities are purchased. Adopting the point of
view of the gamification octalysis framework, that a behavior occurs because of
one or more core drives from within the individual. For this reason, it is
necessary to explore any encouragement that affects customer behavior,
therefore, the service level can be evaluated which ultimately aims to increase
sales. From the studies conducted, the gamification model can increase
individual retention and motivation towards the object. Then, the gamification
octalysis framework is used in this study to evaluate how the influence of a
retail Small Medium Enterprise services on customer motivation. The Likert scale
analysis result has concluded that 4 drives are at the "Very High" level and the
remaining are at the "High" level, while the range scale consists of "Very low",
"Low", "High", and "Very High". While the average value of the octalysis test
scale is 8.4 from the lowest value range of 1 and the highest is 10. The
recommendations of this study are in general the impression and motivation of
customers towards retail Small Medium Enterprise services is high enough,
therefore, that companies need to maintain service. Based on the results of this
study, it can be recommended that customer motivation analys can use
gamification, especially the Octalysis framework to find out which core drives
need to be improved or maintained in more detail. |
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Keywords: |
Gamification, Small Medium Enterprise, Customer Motivation, Octalysis Framework |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
A HYBRID ACO-CS BASED OPTIMIZED KNN CLASSIFIER ALGORITHM FOR RAINFALL DETECTION
& PREDICTION |
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Author: |
K. VARADA RAJKUMAR, Dr. K. SUBRAHMANYAM |
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Abstract: |
The detection and prediction of rainfall is an important task in recent years.
The usage of machine learning approach in agriculture has enhanced the
efficiency of farming. The rainfall detection and prediction will be helpful to
farmers to take appropriate actions on sowing, irrigation etc. In this paper,
the rainfall detection and classification are done, the investigation of various
machine learning approaches like Support Vector Machine, K-Nearest Neighbor
(KNN), Decision Tree Neural Networks were done using rainfall data. In this
paper we propose a new approach for the optimization of the nearest neighbor
numbers in KNN algorithm using a hybrid Ant colony optimization and Cuckoo
search algorithm for efficient rainfall detection. The experiments were
performed in MATLAB platforms using monthly rainfall data sets that are
downloaded from Indian meteorological Department (IMD). Monthly rainfall for
years 1901 to 2019 are taken for analysis. The performance of various
classification algorithm for rainfall data using the parameters like precision,
sensitivity, specificity, and accuracy has been done. |
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Keywords: |
ACO, Cuckoo search, SVM, neural networks, KNN. |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
THE APPLICATION OF FUZZY LOGIC TO IMPROVE ORIENTATION IN SYSTEM EDUCATION IN
MOROCCO |
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Author: |
TARIK BOURAHI, AZOUAZI MOHAMED, ABDESSAMAD BELANGOUR |
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Abstract: |
The aim purpose of this research that we realized in this study is to determine
the best orientation of the student after his high school while dealing with the
problem of uncertainty and ambiguity and applying fuzzy logic theory at an
university located in Casablanca in Morocco. Firstly, we introduce the
importance of education, and then we present the theory of fuzzy logic, its
inference system and its state of the art. Secondly, we present the criteria
that we choose for our research which are: "Grades, “Motivation” and
“Communication”, and the output which is “Orientation”. Next, we do the
fuzzification for the three criteria chosen. Moreover, we construct fuzzy-rule.
Then we apply defuzzification: We acquire diagrams and graphs which explain to
us according to the chosen situation the determination of the best orientation
according to each case which can be presented to the decision makers. We then
compare our research to other research carried out in the education sector,
specifying the difference in objectives. Finally we end by presenting the
efficiency of the application of the fuzzy logic method for this study and we
mention some of its limitations. |
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Keywords: |
Fuzzy Logic, Orientation in Morocco, Motivation, Grades, Communication |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
IMPLEMENTATION OF YOU ONLY LOOK ONCE (YOLO) AND SUPPORT VECTOR REGRESSION (SVR)
METHODS FOR TRAFFIC DENSITY CALCULATIONS BASED ON AREA OCCUPANCY |
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Author: |
FAHMI ANHAR CHOLID, KUSWORO ADI, WAHYUL AMIEN SYAFEI, MUHAMAD HADDIN |
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Abstract: |
This research discusses the implementation of traffic monitoring in calculating
the level of traffic density based on the level of service (LOS) value of in
homogeneous traffic or heterogeneous traffic. According to previous study,
object detection's accuracy is frequently questioned in congested traffic
situations. YOLO, on the other hand, can consistently detect objects and is
ideally suited for traffic density studies. It is feasible to determine traffic
density using a combination of SVR and occupancy area. The total number of
training data used by the YOLO method to detect vehicle types was 4665 samples
of vehicles consisting of types 1-6. The SVR method uses variables processed
using basic freeway segment for training data and occupancy area for test data.
The results show that the YOLO method can recognize vehicle types and obtain
75.16% accuracy in daytime traffic conditions. For the estimate of traffic
density based on occupancy the YOLO and SVR method is implemented. This is
represented with a polynomial kernel with epsilon optimization parameter = 1.0,
degree = 1, gamma = 0.0, and coef0 = 2.0 obtaining a MAPE score of 53.59; this
value is smaller than the use of a linear kernel getting a MAPE value of 55.5. |
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Keywords: |
Area Occupancy, Traffic Density, YOLO, SVR |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
ENSEMBLE LEARNING BASED FEATURE REDUCTION AND SELECTION METHODS FOR
NETWORK INTRUSION DETECTION SYSTEM |
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Author: |
SARA TAMY, HICHAM BELHADAOUI, NABILA RABBAH, MOUNIR RIFI |
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Abstract: |
The use of network intrusion detection systems based on machine learning
algorithms is currently emerging as one of the most effective solutions for
monitoring high dimensional network traffic and identifying anomalous flows with
high accuracy. Integrating feature reduction/selection techniques is also
essential to reduce the undserlying complexity of processing big data sets and
detect intrusions in real time. The purpose of this paper is to investigate the
possibility of using hybrid network intrusion detection system based feature
reduction/selection techniques and ensemble algorithms. First, we compare the
performance of six classifiers namely Naïve Bayes, Support Vector Machine,
Simple Logistic Regression, JRip, Part and J48 using the NSL-KDD dataset. After
analyzing the results, it is obvious that the algorithms take a lot of time to
build the model. Therefore, we applied three dimensionality reduction methods
namely: Information gain evaluation, correlation attribute evaluation and
OneRule attribute evaluation, to detect intrusions in the minimum possible time
without compromising accuracy. Then, we compared the performance of these
methods based on the time taken to build the model, accuracy, error rate and
other metrics to select the best one and associate it with Artificial Bee Colony
algorithm. Based on the experimental results the three best classifiers are
selected to be combined into a stacking model and a majority voting model. We
then evaluate them using several detection measures including accuracy,
precision, F-Measure, recall, time to build model, attack detection rate through
true positive rate and false positive rate, and confusion matrices. The results
are given and analyzed for each category of attack including R2L, Probes, DOS
and U2R to identify the weaknesses of each algorithm, in order to make it more
robust against new intrusions. Overall, no algorithm in the model of attack
detection performed very well in detecting new U2R and R2L intrusions,
nevertheless, the outcomes of our study demonstrate that stacking model, with
J48 as the model learner and Part with JRip as the base classifiers, has allowed
to increase the detection accuracy of R2L to 15. 20%, U2R up to 29.85%, Probes
to 84.55%, DOS to 84.04% and an accuracy score of 91.17% for normal traffic,
while reducing the time needed to build the model. |
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Keywords: |
Machine Learning, Feature Reduction, Feature Selection, Ensemble Classifier,
Naïve Bayes, Support Vector Machine, Simple Logistic, JRip, Part, J48, Network
Intrusion Detection System |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
GLOBAL OUTPUT TRACKING CONTROL FOR HIGH-ORDER NON-LINEAR SYSTEMS WITH
TIME-VARYING DELAYS |
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Author: |
KEYLAN ALIMHAN, NURBOLAT TASBOLATULY, AIGERIM YERDENOVA |
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Abstract: |
This paper studies the problem of global practical output tracking for a class
of high-order non-linear systems with time-varying delays under the weaker
conditions on the system nonlinearities. With the help of an appropriate
Lyapunov-Krasovskii functionals and by using the method of adding a power
integrator, a continuous state-feedback controller is successfully designed such
that all the states of the resulting close loop system are bounded while the
output tracking error converges to an arbitrarily small residual set. A
numerical example demonstrates the effectiveness of the result. |
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Keywords: |
Practical Output Tracking, State Feedback Control, Nonlinear Systems,
Time-Varying Delays, Lyapunov-Krasovskii Functionals |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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Title: |
CYBERSECURITY IMPLEMENTATION SUCCESS FACTORS IN SMART CITY |
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Author: |
RG GUNTUR ALAM, HUDA IBRAHIM |
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Abstract: |
Cybersecurity has proven to be a prominent topic in business and government
developments. Although most Smart City organizations have cybersecurity
strategies in place, they still face challenges in implementing them. The
implementation and adoption of appropriate cybersecurity are challenging and
knowledge-intensive and require the participation and support of policymakers
and IT units. However, although awareness of critical success factors (CSF) for
cybersecurity implementation is very beneficial in avoiding failure in Smart
City projects, this area has rarely been researched, especially with a focus on
Smart City development. Therefore, the contribution of this paper to research
and practice is the identification of critical factors that influence the
successful implementation of cybersecurity in smart cities. This study was
carried out through an interview study with officials and staff in the Jakarta
Smart City environment. As a result, we have 15 keys critical factor that has a
practical implementation and could include in the model of cybersecurity in
smart cities. |
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Keywords: |
Critical Success Factors, Cybersecurity, Smart City, Security of Smart City |
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Source: |
Journal of Theoretical and Applied Information Technology
15th July 2021 -- Vol. 99. No. 13 -- 2021 |
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