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Journal receives papers in continuous flow and we will consider articles
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basic research to the most innovative technologies. Please submit your papers
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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
January 2019 | Vol. 97
No.02 |
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Title: |
INCORPORATING DEOXYRIBONUCLEIC ACID IN AES SCHEME FOR ENHANCING SECURITY AND
PRIVACY PROTECTION |
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Author: |
OMAR G. ABOOD, MAHMOUD A. ELSADD , SHAWKAT K. GUIRGUIS |
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Abstract: |
This paper presents an algorithm based on AES through modifications of the
system. The algorithm developed herein is based on incorporating DNA computing
in AES algorithm instead of the mix-column stage. The modified algorithm
enhances the process to be more secure under the communicated signals used in
the smart grid especially in the self-healing process. The breaking time is
increased via using two keys whilst keeping the round times. Furthermore, the
encryption and decryption times are decreased which is a critical in many smart
grid applications. The work carried out a comparison within the study between
the modified and the conventional AES algorithms under the different methods of
control employed in the fault management. The total time needed to accomplish
the fault management process including the encryption and decryption times is
computed and evaluated. The assessment of the presented method is done through
MATLAB. The sample results are evaluated and discussed. |
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Keywords: |
SABRINE SLAMA, AYACHI ERRACHDI, MOHAMED BENREJEB |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
ADAPTIVE PID CONTROLLER BASED ON NEURAL NETWORKS FOR MIMO NONLINEAR SYSTEMS |
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Author: |
SABRINE SLAMA, AYACHI ERRACHDI, MOHAMED BENREJEB |
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Abstract: |
This paper proposes an adaptive tuning of Proportional-Integrate-Derivative
(PID) controller. This approach is developed to address a class of Multi-Input
Multi-Output (MIMO) nonlinear systems. The adaptive PID controller is built
based on neural networks combining the PID control and explicit neural
structure. The strategy of training consists of on-line tuning of the neural
controller weights using the back-propagation (BP) algorithm to select the
suitable combination of PID gains such that the error between the reference
signal and the actual system output converges to zero. The control scheme is
based on a neural network model, using a variable learning rate, of the system
that is adapted by gradient descent (GD) method to learn system dynamic. The
results of simulation show that improved and stable tracking is achieved with
the proposed adaptive PID controller. |
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Keywords: |
Adaptive PID Controller; Neural Network; Multivariable Nonlinear Systems. |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
EFFICIENT APPROACH OF CARDIAC CATHETERIZATION IMAGE ENHANCEMENT |
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Author: |
MAZEN ISMAEEL GHAREB, AWDER MOHAMMED AHMED, MUZHIR SHABAN AL-ANI |
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Abstract: |
Cardiac catheterization is the process of inserting a tube called a catheter
into the heart through an artery such as the femoral artery or aortic artery to
reach the left ventricle of the heart or coronary arteries for diagnostic
purposes such as ventricular injection left or coronary arteries that can
facilitate X-ray vision or the introduction of therapeutic equipment. Image
enhancement will be represented as one of the main areas of interest of most of
researchers. For human interpretation the subjective quality of images is so
important. Thus different image enhancement techniques have been used to provide
a better diagnosis. The aim of this paper is how to enhance the visualization of
the cardiac image to be more suitable to the doctor in order to make a correct
decision for the patient. This implemented system can be divided into many steps
including preprocessing, enhancement and decision making. The focus of this
research is on how to improve the features of the image so as to be clear to the
doctor. Two types of filters (Gaussian and Average) were applied and then the
results were compared for both types. The Gaussian filter showed better results
in improving the image parameters. |
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Keywords: |
2D-DWT, Image Enhancement, Cardiac Catheterization, Image Visualization, Image
Filtering |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
TWO SCOPES OF ACOUSTIC SIGNAL AND FUZZY-RELIEF ALGORITHM FOR IMPROVING AUTOMATIC
SPEAKER RECOGNITION |
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Author: |
EMAN S. AL-SHAMERY, WAFAA M. AL-HAMEED |
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Abstract: |
Speaker recognition is one of the important biometrics methods that have entered
into many applications such as security, marketing service, and bank transfers.
The main aim of this paper is to identify the speaker with high accuracy through
his or her voice. All previous research deal with recorded files for speakers as
only sound signals. This research introduces a new idea for dealing with the
recorded sounds in two scopes, one of which is dealing with the signal as an
acoustic file and the other as an image, which is picked from the sound signal.
These files are analyzed using Discrete Wavelet Transform (DWT), specifically
(Daubechies) db1 at three levels. Additionally, another contribution to the
development of the Relief method for feature selection has been proposed by
including a fuzzy inference system. The proposed Fuzzy-Relief method divides the
features into three groups that are ordered according to the importance degree
from the best up to the worst depending on the new membership function. The
first two groups are taken into account in the recognition process and neglected
the third group. Furthermore, The Logistic Regression (LR) method and
Multi-Layer Perceptron (MLP) neural network are employed with 3-cross-validation
for tspeaker recognition. The proposed system has been applied to the twenty
speakers, ten females and ten males, ten recordings and two different sentences
for each speaker, in normal room circumstances. The system is evaluated using
accuracy and some other measures resulting from the confusion matrix. After a
comparison between the two scopes, the recognition accuracy of acoustic is
varied from 78% as a worst to 96% as a best with a reduction percentage of
features reaches 62.5%. While, for image files, the recognition accuracy is
ranged from 92% to 100% with the reduction percentage reaches to 78.9%. In
general, the results of LR are better than MLP, and the results of Image files
are much better than acoustic files. |
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Keywords: |
Discrete Wavelet Transform, Fuzzy-Relief Algorithm, Image of Sound, Logistic
Regression, Multi-Layer Perceptron. |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
TOWARD TO BUILD STRONG IMAGE INTEGRITY SCHEME IN CLOUD COMPUTING ENVIRONMENT |
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Author: |
HAITHAM ALI HUSSAIN, AQEEL A. YASEEN |
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Abstract: |
Cloud computing aims to assist users in remotely preserving their data in a
cloud server and protect them from malicious attacks, such as an impersonation
attack. In addition, cloud computing gives users the ability to store and
process their data in an outsource cloud’s storage. With the rapidly increasing
use of medical images with a growing level of detail due to advances in
diagnostic medical images, cloud computing is used to store large amounts of
medical images. Although the cloud has considerable potential, it has many
security challenges, such as data integrity and unauthorised access of entities
to cloud resources. This paper aims to solve the issue of ensuring the integrity
of medical image data stored in cloud servers. Thus, we propose a robust scheme
that uses cryptohash function and k-nearest neighbour (KNN) to obtain the
metadata of images stored in the cloud, thereby protecting the medical images
owned by users against any editing, deleting or inserting operations performed
by an attacker. Our proposed scheme uses KNN to retrieve medical images to
ensure their integrity and has robust security and high performance |
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Keywords: |
Medical Image, Cloud Computing, Meta-Data, Crypto-Hash Function, Knn |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
CALIBRATING THE NELSON-SIEGEL MODEL CLASSES AND THEIR ESTIMATION USING
HYBRID-GENETIC ALGORITHM APPROACH: CASE STUDY OF INDONESIAN GOVERNMENT BONDS |
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Author: |
MUSLIM, DEDI ROSADI, GUNARDI, ABDURAKHMAN |
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Abstract: |
In this paper, we consider the problem of modelling the yield curve using
Nelson-Siegel model classes. Nelson-Siegel model classes discussed here are NS
model, BL model, NSS model, RF model, and our proposed NSSE models. NSSE model
is a model which extends the standard NS model as Nelson-Siegel model class by
adding some linear and non-linear parameters in which form the fourth hump of
the model class. The purpose of adding the hump is to accommodate the
possibility of having the following cases: the first, the condition when the
short term and the medium term yields are higher than the long term yield. The
second, the condition when the upper-value short term yields are higher than
both the short term yields on average and the long term yields. The third, the
case when the upper-value medium term yields are higher than both the medium
term yields on average and the long term yields. These considered cases make the
yield curve more likely to have minimum locals and therefore, the Nelson-Siegel
model classes become more difficult to be estimated. To overcome this problem,
in this paper we estimate the model using the hybrid-genetic algorithm approach
and compare it with the standard estimation based on NLS method. We provide an
empirical study using Indonesian Government-Bond Yield Curve (IGYC) data, and
found that the best model for IGYC is 6-factors model. |
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Keywords: |
Yield Curve, Nelson-Siegel Model, Hybrid Method, Genetic Algorithm, Nonlinear
Least Square, and Constrained Optimization |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
LAGGED MULTI-OBJECTIVE JUMPING PARTICLE SWARM OPTIMIZATION FOR WIRELESS SENSOR
NETWORK DEPLOYMENT |
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Author: |
ALI NOORI KAREEM, ONG BI LYNN, RBADLISHAH AHMED, HASNA AHMAD, MOHAMED SHUJAA |
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Abstract: |
Studies pertaining to wireless sensor network deployment (WSND) have escalated
in recent years due to its exceptional function in planning configurations for
sensor networks in order to attain maximum coverage and lifetime in a
cost-effective manner. Although the approach of meta-heuristic searching
optimization has been commonly applied, it has failed in addressing several
issues related to multiple objectives and intricate optimization surface. As
such, this work developed a novel multi-objective optimization (MOO) called the
lagged multi-objective jumping particle swarm optimization (LMOJPSO) in order to
overcome the drawbacks of WSND. It aims at finding the best locations and
configuration of sensors in 2D environment in order to prolong the life time of
the network with obtaining the best coverage and other performance measures.
Three types of Pareto front, which were global, iteration (including lag), and
local, had been incorporated for optimization search. Upon application to WSND,
the proposed algorithm appears to ascertain network coverage and connectivity.
When the outcomes of LMOJPSO were compared with the state-of-the-art NSGA-II
method, the proposed algorithm seemed to display superior outputs for (MOO). |
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Keywords: |
Multi-Objective, WSND, NSGA-II, Coverage, Connectivity, LMOJPSO, Optimization |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
A SYSTEMATIC LITERATURE REVIEW ON METHODS FOR SOFTWARE EFFORT ESTIMATION |
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Author: |
ROBERT MARCO, NANNA SURYANA, SHARIFAH SAKINAH SYED AHMAD |
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Abstract: |
There have been many researchers who proposed research in an effort to develop
the field of improving accuracy in the Software Effort Estimation (SEE).
Collected results from a series of studies selected in the Software Effort
Estimation, which was published in the period 2000-2017, using systematic
mapping and review procedures. The purpose of this review is to provide a
classification of study areas of SEE related to publication channels, research
approaches, types of contributions, techniques used in combination. To analyze:
1) The precise estimation of SEE techniques; 2) Accuracy of the SEE model
estimate compared with other models; 3) A favorable outcome context for the use
of the SEE model; and 4) The impact of other techniques into the SEE model by
combining models and implementation for models and tools. We have identified 74
major studies that are relevant to the purpose of this study. After
investigating, we found that eight types of techniques were used in the Software
effort estimation model. that techniques used for SEE usually produce acceptable
estimation accuracy, and the facts are more accurate. |
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Keywords: |
Systematic Literature Review, Software Effort Estimation, Datasets, Methods,
Validation. |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
A REPRODUCING KERNEL HILBERT SPACE APPROACH AND SMOOTHING PARAMETERS SELECTION
IN SPLINE-KERNEL REGRESSION |
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Author: |
RAHMAT HIDAYAT, I NYOMAN BUDIANTARA, BAMBANG W. OTOK, VITA RATNASARI |
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Abstract: |
Regression analysis studies the form of the relationship between one or more
predictor variables with one response variable. The relationship of the response
variable with several predictor variables in nonparametric regression does not
always using one type of approach such as Spline, Kernel, or Fourier series.
This fact is found in many nonparametric regression, between one predictor
variable and another predictor variable that has a different pattern with the
response variable. This study proposes a model that has ability to handle the
different patterns in the nonparametric regression. This model was developed by
adding Kernel functions to the goodness of fit component in completion of the
smoothing Spline. Empirical analysis is carried out on fuel consumption data in
Indonesia. The performance of the proposed model is evaluated by looking at the
GCV value and comparing its coefficient of determination with the parametric
regression. The result of the study shows that the proposed model is better than
the compared model. In addition, this model has a highly accuracy in making
predictions or forecasting. |
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Keywords: |
Nonparametric, Regression, Spline, Kernel, GCV, Fuel Consumption |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
APPLIED FUZZY AND NASA TLX METHOD TO MEASURE OF THE MENTAL WORKLOAD |
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Author: |
ADI BANDONO , OKOL S SUHARYO , RIONO |
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Abstract: |
In carrying out its main duty as a guardian of the sovereignty State of republic
Indonesia, especially at sea, the strength of the Navy is directed as a
strategic force developed under the SSAT. The strength of the Navy can be
measured by the arsenal and the quality of the personnel who are responsible for
it. The performance, quality of personnel is strongly influenced by the work
load it receives. Measurement of personnel workload in KRI to determine the
class of his current position using the Factor Evaluation System (FES) method
that is more oriented on the volume of work and work time. While the mental
workload has not been accommodated in the measurement of workload using this
method. In this research will carry out the measurement of mental workload of
Indonesian Warship personnel for each type of work when the Indonesian Warship
operates, using the NASA TLX method integrated with the Fuzzy method. The
questionnaire data collection was obtained from 82 respondents Indonesian
Warship personnel. From the research results obtained data that of 11 (eleven)
types of work in Indonesian Warship at the time of operation, the Main Engine
Operator is the work that has the highest mental workload with a value of 74.33.
While the type of work that most low-level mental work is to electronics
operators with a value of 58.83. with the known mental workload of each
personnel, it can be used to determine a policy so that personnel do not get
excessive workload. |
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Keywords: |
NASA TLX, Workload |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
NEWS RETRIEVAL BASED ON SHORT QUERIES EXPANSION AND BEST MATCHING |
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Author: |
ZAINAB A. KHALAF, INTISAR A. SHTAET |
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Abstract: |
An information retrieval (IR) is a system that locates information in
collections of unstructured or semi-structured document which are relevant to
the user query. Usually, the query represented by short query that have a few
features or keywords that used to describe the user needed of information. These
short queries containing only a few words can be vague and ambiguous. As a
result, IR system returns documents that are generally not relevant to the
user’s information needs. In this paper, an automatic approach of query
expansion is proposed based on latent semantic indexing (LSI) method in order to
enhance the performance of the information retrieval system. Development
database of queries are used to find the best match between the user query and
the development queries by using LSI algorithm. The best result that obtained
from LSI will combine with the user query to create a new query that used later
as new input in information retrieval system to retrieve the documents. To
evaluation, the information retrieval system is compared before and after query
expansion by using latent semantic indexing (LSI) method. The proposed approach
improved the retrieval system performance from 70% to 75% F-measure with an
average relative improvement of 7.2%, and it is better than the conventional LSI
approach. |
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Keywords: |
Information Retrieval; Latent Semantic Indexing; Query Expansion; News
Retrieval. |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
DETERMINATION OF THE LOCATION INTERCITY BUS TRANSIT IN MAKASSAR CITY USING
EXPERT SYSTEM MODEL AND GIS |
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Author: |
ASHARI ABDULLAH , ANANTO YUDONO , SAKTI ADJI ADISASMITA , ARIFUDDIN AKIL |
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Abstract: |
This research adapts Intercity Bus transit (ICBT) Index according to the
variables developed by Abdullah et al., [7]. The ICBT index is used to measure
potential location to be used as transit location of intercity bus passengers.
The ICBT variables used consist of Commercial facility area (CO), Traffic
Seamless (TR), Housing coverage area (L), distance to main road (DR) and
capacity of road (RC) which then called as ICBT supported area. This research
adds ICBT category of unacceptable area consisting of natural disaster area ,
transportation infrastructure area, and ICBT category of limited area consisting
of military and policy private area, city engineering service area, slope
steepness, and flood risk area. This research uses expert system analysis with
IF-THEN rules as well as GIS analysis. Research population is grid-based
location with size of 100x100. Case study is conducted in Makassar city. First
research results show that most of ICBT with high value is close to center of
city in arterial roads. Both methods can be used to determine potential transit
location to serve intercity bus passengers. |
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Keywords: |
Intercity Bus Transit, Location Index, Expert System, GIS |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
HYBRID GPS + UWB POSITIONING THROUGH UKF WITH RSS AND TOA |
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Author: |
YOUAN BI TRA J.C, TRAORE BRAHIMA, OBROU K. OLIVIER |
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Abstract: |
The Global Positioning System (GPS) is an accurate positioning system. However,
this system encounters difficulties in so-called constrained environments
(indoor environments, presence of obstructions, etc.) where GPS signals are very
often masked or reflected. To mitigate this situation, another technique such as
Infra Red (IR) technology or GPS repeaters are used to perform well for
constrained positioning. In this document, we propose a hybrid GPS - UWB
positioning system that provide better positioning accuracy as compared to UWB
or GPS system only. For this purpose, we use pseudo-range metrics for the GPS
system and Received Signal Strength (RSS) for Ultra Wideband (UWB) technology
that we simultaneously couple through the Unscented Kalman Filter (UKF). The
performance of this hybrid positioning technique is highlighted in different
scenarios. Simulation results show that the proposed algorithm is more accurate
than GPS alone. Also, it is better than the results of GPS and UWB coupling
through the Extended Kalman Filter (EKF). |
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Keywords: |
GPS, UWB, Hybrid positioning, UKF, EKF |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
CHOOSING CHILI SEEDS USING ANALYTIC HIERARCHY PROCESS (AHP) METHOD : AN ANALYSIS
AND INTERFACE APPLICATION DESIGN |
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Author: |
ONNY MARLEEN, SUHARNI, 3ANGGRAENI RIDWAN, RANI PUSPITA |
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Abstract: |
Selection of cayenne chili seeds affects the yield. Of the many varieties of
cayenne chili varieties that have been issued by the Government, not necessarily
all varieties are in accordance with the expectations of farmers. Farmers need
to know which varieties are suitable or close to their expectations. Application
of selection of cayenne chili seeds helps farmers to find out which varieties
suit their expectations. AHP is one method to assist in the selection of
decisions of cayenne chili seeds. By using 10 criteria selected by farmers,
analysis and design of applications is made using the UML method. |
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Keywords: |
Decision making, design, application, AHP,UML |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
FACTORS AFFECTING INSTRUCTORS’ ADOPTION OF LEARNING MANAGEMENT SYSTEMS: THE CASE
OF PALESTINE |
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Author: |
NAHEL A O ABDALLAH, ABD RAHMAN AHLAN, ODEH ABDULLAH |
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Abstract: |
Although web-based learning systems are emerging as a useful tool for
facilitating teaching and learning activities, instructors’ use of learning
management systems in higher educational institutions is still limited. In this
context, this empirical research investigates factors that can potentially
contribute to learning management system adoption in Palestinian institutions of
higher education. In addition, the study also developed an integrated model of
instructor adoption of learning management systems by incorporating existing
literature and multiple empirically verified theories, including the technology
acceptance model and DeLone and McLean’s information system success model.
Survey data collected from 365 university instructors were examined to evaluate
the influence of various constructs on lecturers’ adoption of learning
management systems using structural equation modeling. The research results show
that perceived usefulness, perceived ease of use, system quality, information
quality, service quality, management support, resistant to change, personnel IT
innovativeness, attitude toward the system, computer efficacy and subjective
norms influence instructors’ intention to use learning management systems.
Findings of this research will be valuable for academicians and practitioners in
implementation, management and continuous improvement of learning management
systems. |
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Keywords: |
IS Success Model, Learning Management Systems (LMS), LMS Adoption, Structural
Equation Modeling, Technology Acceptance Model (TAM). |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
A SURVEY ON THE VEIN BIOMETRIC RECOGNITION SYSTEMS: TRENDS AND CHALLENGES |
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Author: |
MOHAMMED SABBIH HAMOUD AL-TAMIMI |
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Abstract: |
Vascular patterns were seen to be a probable identification characteristic of
the biometric system. Since then, many studies have investigated and proposed
different techniques which exploited this feature and used it for the
identification and verification purposes. The conventional biometric features
like the iris, fingerprints and face recognition have been thoroughly
investigated, however, during the past few years, finger vein patterns have been
recognized as a reliable biometric feature. This study discusses the application
of the vein biometric system. Though the vein pattern can be a very appealing
topic of research, there are many challenges in this field and some improvements
need to be carried out. Here, the researchers reviewed the different research
papers in this area, determined the strengths and weaknesses of these studies,
investigated the various improvements made in this fields and the drawbacks
which have to be resolved. |
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Keywords: |
Vein, Biometric, Recognition, Vein Features, Vein Pattern. |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
REVIEW OF DCT AND CHAOTIC MAPS IN SPEECH SCRAMBLING |
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Author: |
NIDAA ABDULMOHSIN ABBAS , ZEINA HASSAN RAZAQ |
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Abstract: |
The communication technology improved recently in many important fields in daily
life, this increases the demands for techniques which are more suitable to these
situations. Recently the orthogonal transformation represents a good choice for
security especially if it combined with a studied way for permutation, this can
be provided by chaotic mapping which provides perfect mechanism for permutation.
In this paper, we concentrate on the most popular chaotic maps and what are the
mappings that used with DCT as an example in our research for orthogonal
transformation and finally summarize the performance of this works to give a
hint for the researchers to decide the suitable combination for their problems
according to their requirement. |
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Keywords: |
Discrete Cosine Transform (DCT), Wavelet Transform( WT), Speech Scrambling,
Inverse Discrete Cosine Transform (IDCT), Chaotic Pseudo-Random Number
Generators (CPRNGs), Chaotic System (CS) |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
E-GOVERNMENT ADOPTION SUCCESS FACTORS AND THEIR WEIGHT ANALYSIS: A CITIZEN
PERSPECTIVE |
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Author: |
MUSTAFA A. A., FAIZAL M.A., NURUL AZMA ZAKARIA |
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Abstract: |
Since there are many theories, models and factors to choose when investigating
the e-government adoption, the issue of how to choose the appropriate factors
arises. Hence, this study’s purpose is to overcome this issue by highlighting
e-government adoption success variables by performing a weight analysis of the
variables relationships. Data were gathered from 141 studies associated to the
e-government adoption. Out of those 141 studies, only 94 utilized a variety of
constructs with appropriate values of correlation that are required to perform a
weight analysis. Both non-significant and significant relationships from all 94
publications are also presented in a diagram. Our findings shows that 15
independent variables were found to be categorized as best predictors, 7
independent variables were found to be categorized as promising predictors, and
12 independent variables were found to be categorized as least effective
predictors. This paper contributes by implementing an up to date variables
weight analysis, moreover it contributes theoretically to the literature body of
e-government and suggests further future work directions. |
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Keywords: |
E-government, E-government Adoption, Weight Analysis, Citizen Adoption, Success
Factors. |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
AFFINE PROJECTION ALGORITHM BASED DECISION FUSION FOR COOPERATIVE SPECTRUM
SENSING IN COGNITIVE RADIO NETWORKS |
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Author: |
ALI JAMOOS, LAMA AYYASH |
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Abstract: |
Spectrum sensing is a main function in cognitive radio networks to detect the
spectrum holes or unused spectrum. Cooperative spectrum sensing schemes are
recently suggested and they provide fast and accurate results. In this paper, we
suggested a new adaptive and cooperative spectrum sensing technique based on the
affine projection algorithm (APA). In this method, each secondary user (SU)
takes a binary decision by its local sensing of the spectrum using energy
detector. Local decisions are then forward to the fusion center (FC), where
definitive decision is taken on the status of the spectrum using adaptive
filters. In our suggested technique, APA updates the weights of the adaptive
filter by using the current and the L-1 delayed input signal vectors. Simulation
results indicate that the suggested approach provides faster convergence speed
and less steady state mean square error than the existing methods that are based
on the normalized least mean square (NLMS) or the so-called kernel least mean
square (KLMS) algorithm. |
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Keywords: |
Cooperative spectrum sensing, decision fusion, adaptive filters, APA algorithm,
cognitive radio networks. |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
EMBEDDING MACHINE LEARNING IN AIR TRAFFIC CONTROL SYSTEMS TO GENERATE EFFECTIVE
ROUTE PLANS FOR AIRCRAFTS IN ORDER TO AVOID COLLISIONS |
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Author: |
MUKESH MADANAN, NORLAILA HUSSAIN, NITHA C VELAYUDHAN, BIJU T SAYED |
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Abstract: |
Air Traffic Controllers play a vital role in managing and directing flights both
in and off the air. The most challenging task assigned to the controllers is to
avoid collisions and to plan routes for the flights and make sure that these
flights take off and reach the destination airports in time. Most of the route
planning in such cases is done in accordance with humans and the decision making
is solely dependent on human intelligence which is sometimes time consuming and
error-prone. Artificial intelligence capabilities could be embedded in these
controllers to make quick decisions and be free of human interventions. The
paper focuses on the route planning activity of the controllers and has an in
depth consideration towards the pros and cons of designing and implementing an
artificial intelligence system to the air traffic controllers. The paper also
focuses on the issues faced by air traffic controllers in order to maintain
airspace suitable for safe flying. |
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Keywords: |
Artificial Intelligence, Air Traffic Control, Machine Learning, Plan generator,
Route Plan |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
DATA TRAFFIC CONTROL OVER 5G NETWORKS USING SOFTWARE-DEFINED MULTIPLE ACCESS |
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Author: |
AHMED ALSHAFLUT, VIJEY THAYANANTHAN |
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Abstract: |
Recently, user requirements have been increased in different networks
environments. However, massive users have been promised to be served at the
minimum range of latency. For that, researchers have investigated the effects of
the gradual increase. Traffic control has been considered as one of the most
sensitive issues in 5G environments. In this paper, the data traffic control has
been addressed to serve wireless network users at best over 5G applications.
Thus, it has proposed Data Traffic Control Over 5G Networks (DTC5GN) model for
managing traffic in wireless networks with a massive number of users. It has
followed classifying any received request and based on that direct the request
to the best routing map. Furthermore, this work would enhance traffic management
in massive networks to get user’s satisfaction. Additionally, this model has
discussed the traffic issues, starting from the access step till the service
delivery. |
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Keywords: |
Traffic control; Software Defined Multiple Access; Wireless traffic models;
Traffic Predictions; Dynamic Spectrum Sharing; 5G networks |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Text |
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Title: |
THE STATISTICAL RESEARCH OF PROBLEMS OF INFORMATION SUPPORT FOR INNOVATIVE
ACTIVITY OF ENTERPRISES IN KAZAKHSTAN |
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Author: |
UTEPBERGENOV I.T., BAIZYLDAYEVA U.B., BURANBAEVA A.I., TOIBAYEVA SH.D. |
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Abstract: |
In this research paper the actuality and importance of the provision of business
with up-to-date innovations achievements are considered with comparative
analysis of the existing innovations news and observations sources. For the
beginning of the research of innovative activity of Kazakhstani enterprises we
decided to investigate the state of things with innovation with questionnaire
method as a productive way to research current statements of business
environment. In the paper the general approach to the analysis of survey results
is set with some overall conclusions for further detailed analysis. This paper
is to serve as our start point to understanding and analysis of innovative
activity of Kazakhstani enterprises. This research will be continued for further
clarification, analysis and development of useful instruments to support
innovative activities of Kazakhstani enterprises |
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Keywords: |
Innovation Management, Information Support, Descriptive Statistics, Regression
Analysis, Visualized Analysis, IBM SPSS, Microsoft Power BI, Google Analytics. |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Title: |
SEMANTIC INFORMATION EXTRACTION APPROACH FOR E-COMMERCE SEARCH ENGINE BASED ON
GOODRELATIONS ONTOLOGY |
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Author: |
ABDELHADI BAHAFID, KAMAL EL GUEMMAT, EL HABIB BEN LAHMAR, MOHAMED TALEA |
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Abstract: |
Internet for e-commerce is the main source of information, this information is
not directly exploitable by computers, hence many methods and approaches to
extract this information, in order to use them. Search engines [1] use these
methods or approaches to extract and index the information contained in the web
pages.
Users use search engines to find useful information about the products
they need, which shows the importance of search engines and having to equip them
with good extraction methods to respond more accurately and in a relevant way to
the need of users.
Most of these search engines are based on keywords [2] to
extract and index data from web pages, which explains the quality of the search
results [3] of these engines which often return results that does not match the
search performed, the result is not always relevant, hence the approach proposed
in this article, it is a new approach that consists of linking the CSS
incorporated on the e-commerce web page and GOODRELATIONS ontology used to index
these web pages by means of a database, and from these CSS classes, generate a
Wrapper to extract all the information about the products, which allow us to
know the attribute of each product, it corresponds to which attribute of the
ontology, i.e. its semantics, this will improve the relevance of the results of
the research and respond more precisely to the need of the user. |
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Keywords: |
Web Semantic, Information Extraction, Information Retrieval System, Semantic
Indexing, E-Commerce, Ontology, GOODRELATIONS |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Full
Text |
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Title: |
INTELLIGENT CLASSIFICATION ALGORITHMS IN ENHANCING THE PERFORMANCE OF SUPPORT
VECTOR MACHINE |
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Author: |
HIBA BASIM ALWAN, KU RUHANA KU-MAHAMUD |
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Abstract: |
Performing feature subset and tuning support vector machine (SVM) parameter
processes in parallel with the aim to increase the classification accuracy is
the current research direction in SVM. Common methods associated in tuning SVM
parameters will discretize the continuous value of these parameters which will
result in low classification performance. This paper presents two intelligent
algorithms that hybridized between ant colony optimization (ACO) and SVM for
tuning SVM parameters and selecting feature subset without having to discretize
the continuous values. This can be achieved by simultaneously executing the
selection of feature subset and tuning SVM parameters simultaneously. The
algorithms are called ACOMV-SVM and IACOMV-SVM. The difference between the
algorithms is the size of the solution archive. The size of the archive in ACOMV
is fixed while in IACOMV, the size of solution archive increases as the
optimization procedure progress. Eight benchmark datasets from UCI were used in
the experiments to validate the performance of the proposed algorithms.
Experimental results obtained from the proposed algorithms are better when
compared with other approaches in terms of classification accuracy. The average
classification accuracies for the proposed ACOMV–SVM and IACOMV-SVM algorithms
are 97.28 and 97.91 respectively. The work in this paper also contributes to a
new direction for ACO that can deal with mixed variable ACO. |
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Keywords: |
Support Vector Machine, Ant Colony Optimization, Parameter Optimization, Feature
Subset Selection, Evolutionary Approach |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Full
Text |
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Title: |
THE SEARCH OF BALANCE BETWEEN DIVERSIFICATION AND INTENSIFICATION IN ARTIFICIAL
BEE COLONY ALGORITHM TO SOLVE JOB SHOP SCHEDULING PROBLEM |
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Author: |
JEBARI HAKIM, RAHALI EL AZZOUZI SAIDA, SAMADI HASSAN, SIHAM REKIEK |
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Abstract: |
Several intelligent theories have been proposed to solve job shop scheduling
problems with the target of minimizing makespan such as hybrid metaheuristics.
The core advantage of hybridization is to improve the effectiveness of the
algorithm leading to better quality of solutions. The paper establishes seven
hybrid methods namely HABCGA according to sixteen configurations (four crossover
operators: PMX, OX, CX and PBX, and four mutation operators: swap, inversion,
insertion and displacement) to solve job shop scheduling problems with the
objective of minimizing makespan and to test these algorithms on 250 Benchmark
instances to evaluate the performance and to find the balance that can lead to
the optimal performance of the hybrid ABC. The results indicate how the multiple
hybridizations, the crossover operator type, and the mutation operator type
affect in a positive way the balance between diversification and intensification
in artificial bee colony algorithm to solve job shop scheduling problem. |
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Keywords: |
Scheduling, Job Shop, Multiple Hybridization, ABC, GA. |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Full
Text |
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Title: |
DIAGNOSES OF BREAST CANCER IN HISTOPATHOLOGICAL IMAGES BASED ON DEEP
LEARNING |
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Author: |
MOHAMAD MAHMOUD AL RAHHAL |
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Abstract: |
Detection and classification of cancer in histopathological images is one of the
biggest challenges for oncologists. Deep learning approaches have proved to be
very valuable tools in dealing with histopathological images, and the results
obtained from such approaches help the oncologists in the diagnosis of breast
cancer. In this paper, we propose a deep convolutional neural network approach
to generate a robust feature representation from histopathological images. We
employed three different pre-trained models, namely: Vgg_m, VeryDeep_16, and
Googlenet, and the method has been evaluated in two different scenarios. In the
first scenario (magnification dependent), we train networks separately depending
on image magnification (40x, 100x, 200x, and 400x). In the second scenario, we
utilize all available data in the training set independent of magnification. For
both scenarios, we demonstrate superior results at both patient and image levels
compared to state of the art methods |
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Keywords: |
Convolutional Neural Network, CNN, Histopathological Images, Imagenet,
Classification, Breast Cancer. |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Full
Text |
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Title: |
AQAS: ARABIC QUESTION ANSWERING SYSTEM BASED ON SVM, SVD, and LSI |
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Author: |
MOYAWIAH A. AL-SHANNAQ , KHALID M.O. NAHAR, KHALDOUN MK.H HALAWANI |
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Abstract: |
In alliance to the emerging internet technologies and services, the field of
questions answering was one of the most trending topics. It is being used in
multiple applications ranging from search engines to smart and complicated home
assistance devices. In this paper, we are proposing an enhanced method and
system for question answering that serve Arabic language questions. This system
provides accurate paragraph level answers that extract its information out of
documents dataset in different fields. The proposed system uses Support Vector
Machine (SVM), Single Value Decomposition (SVD), and Latent Semantic Index (LSI)
to classify the query in two phases. The method has been tested on a set of
queries in different fields (classes) against a documents dataset of size 10,000
documents in 10 classes. The testing shows promising and accurate output for
each of the test cases. Average classification accuracy reaches 98% using
document classification metrics. |
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Keywords: |
Support Vector Machine (SVM), Latent Semantic Index (LSI), Question Answering
System (QAS), Arabic Language, SVD |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Full
Text |
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Title: |
HYBRID APPROACH FOR FACIAL CUES BASED EMOTION PROFILE GENERATION |
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Author: |
BHARATI DIXIT, ARUN GAIKWAD |
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Abstract: |
Emotion analysis is very significant from the perspective of many applications
like E-learning, cognitive assessment, driver alert system, pain monitoring
system, healthcare services, interactive TV, animation etc. Outcome of the work
is depicted in the form of emotion profile which is defined as graphical
representation of the degree of presence or absence of all the universally
accepted seven emotions on a single scale. This simple but unique representation
helps in determining the presence of complex/naturalistic emotions. Complex
emotions represents the emotional state of a person when he/she is able to feel
and express more than one emotions simultaneously at the time of observation.
Emotion analysis through facial expressions is experimented on JAFFE and MIST
Database - a locally created context specific database of images. Images of the
subjects under study are captured and experimented for all seven universally
accepted emotions and depicted in the form of emotion profiles. Emotions are
categorized as neutral, positive and negative for MIST database and in seven
categories of emotions like happy, surprise, anger, sad, disgust, fear and
neutral for JAFFE database. Average accuracy obtained as 91.31% for MIST
database and 93.84% for JAFFE Database. FPR - false positive rate and FNR -
false negative rate, values for JAFFE database are 6.38% and 6.62% respectively.
FPR and FNR values for MIST database are 8.18% and 8.60% respectively. Emotion
recognition time for JAFFE database 1.108 sec and for MIST database 1.392 Sec.
These performance parameters especially the accuracy more than 90% which is at
par with the research results published in renowned journals in this domain
makes this work qualify to be used for various applications. Analysis of complex
emotions is typically useful for the professionals working in the field of Human
resource, clinical psychology, cognitive analysis etc. More accurate emotion
recognition is still challenging and open research problem |
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Keywords: |
Facial Expressions, Fusion Of Features, Emotion Analysis, Emotion Profiles,
Context Specific Image Database |
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Source: |
Journal of Theoretical and Applied Information Technology
31st January 2019 -- Vol. 97. No. 02 -- 2019 |
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Full
Text |
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