Open Access
ARTICLE
Supreet Kaur*, Vijay Kumar Joshi
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 217-226, 2020, DOI:10.31209/2018.100000064
Abstract Wireless sensor networks (WSNs) are susceptible to safety threats due to
cumulative dependence upon transmission, computing, and control
mechanisms. Therefore, securing the end-to-end communication becomes a
major area of research in WSNs. A majority of existing protocols are based
upon signature and recommended-based trust evaluation techniques only.
However, these techniques are vulnerable to wormhole attacks that happen due
to lesser synchronization between the sensor nodes. Therefore, to handle this
problem, a novel hybrid crossover-based ant colony optimization-based routing
protocol is proposed. An integrated modified signature and recommendationbased trust evaluation protocol for WSNs is presented. Extensive experiments
reveal that the proposed… More >
Open Access
ARTICLE
He Ni1,*, Yongqiao Wang1, Buyun Xu2
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 227-236, 2020, DOI:10.31209/2019.100000068
Abstract The paper presents a probabilistic clustering approach based on self-organizing
learning algorithm and recursive Bayesian estimation. The model is built upon
the principle that the market data space is multimodal and can be described by
a mixture of Gaussian distributions. The model parameters are approximated by
a stochastic recursive Bayesian learning: searches for the maximum a posterior
solution at each step, stochastically updates model parameters using a “dualneighbourhood” function with adaptive simulated annealing, and applies profile
likelihood confidence interval to avoid prolonged learning. The proposed model
is based on a number of pioneer works, such as Mixture Gaussian
Autoregressive Model,… More >
Open Access
ARTICLE
Ebtsam Adel1, Shaker El-sappagh2, Mohammed Elmogy3, Sherif Barakat1, Kyung-Sup Kwak4,*
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 237-251, 2020, DOI:10.31209/2019.100000151
Abstract Information technology is a beneficial tool for the healthcare industry. Health
informatics is concerned with using ICT within the healthcare system. Different
electronic health record (EHR) systems independently store large amounts of
medical data in various structures and formats. Achieving semantic
interoperability in EHR environments will improve the healthcare industry. In
our previous studies, we proposed a framework that identifies the different
heterogeneous medical data sources. In this paper, we move towards
implementing the first module of that framework. We expect our framework to
be a step towards improving performance and reducing both human mediation
and data losses. More >
Open Access
ARTICLE
Parvathavarthini S1,*, Karthikeyani Visalakshi N2, Shanthi S3, Madhan Mohan J4
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 253-260, 2020, DOI:10.31209/2019.100000155
Abstract Intuitionistic fuzzy clustering allows the uncertainties in data to be represented
more precisely. Medical data usually possess a high degree of uncertainty and
serve as the right candidate to be represented as Intuitionistic fuzzy sets.
However, the selection of initial centroids plays a crucial role in determining the
resulting cluster structure. Crow search algorithm is hybridized with
Intuitionistic fuzzy C-means to attain better results than the existing hybrid
algorithms. Still, the performance of the algorithm needs improvement with
respect to the objective function and cluster indices especially with internal
indices. In order to address these issues, the crow search algorithm… More >
Open Access
ARTICLE
S.Ilangovan1,*, A. Vincent Antony Kumar2
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 261-268, 2020, DOI:10.31209/2019.100000154
Abstract In this work, a Novel Feature selection framework called SU embedded PSO
Feature Selector has been proposed (SU-PSO) towards the selection of optimal
feature subset for the improvement of detection performance of classifiers. The
feature space ranking is done through the Symmetrical Uncertainty method.
Further, memetic operators of PSO include features and remove features are
used to choose relevant features and the best of best features are selected
using PSO. The proposed feature selector efficiently removes not only irrelevant
but also redundant features. Performance metric such as classification accuracy,
subset of features selected and running time are used for comparison. More >
Open Access
ARTICLE
Bhavithra Janakiraman1,*, Saradha Arumugam2
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 269-280, 2020, DOI:10.31209/2019.100000150
Abstract Personalization in recommendation system has been emerging as the most
predominant area in service computing. Collaborative filtering and content
based approaches are two major techniques applied for recommendation.
However, to improve the accuracy and enhance user satisfaction, optimization
techniques such as Ant Colony and Particle Swarm Optimization were analyzed
in this paper. For theoretical analysis, this paper investigates web page
recommender system. For experimentation, Diabetic patient’s health records
were investigated and recommendation algorithms are applied to suggest
appropriate nutrition for improving their health. Experiment result shows that
Particle Swarm Optimization outperforms other traditional methods with
improved performance and accuracy. More >
Open Access
ARTICLE
R.V.V. Krishna1,*, S. Srinivas Kumar2
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 281-290, 2020, DOI:10.31209/2019.100000121
Abstract In this paper, a color image segmentation algorithm is proposed by extracting
both texture and color features and applying them to the one -against-all multi
class support vector machine (MSVM) classifier for segmentation. Local Binary
Pattern is used for extracting the textural features and L*a*b color model is
used for obtaining the color features. The MSVM is trained using the samples
obtained from a novel soft rough fuzzy c-means (SRFCM) clustering. The fuzzy
set based membership functions capably handle the problem of overlapping
clusters. The lower and upper approximation concepts of rough sets deal well
with uncertainty, vagueness, and incompleteness… More >
Open Access
ARTICLE
Li-Hong Juang1,*, Yi-Hua Zhao2
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 291-301, 2020, DOI:10.31209/2020.100000164
Abstract Speech recognition is one of the most convenient forms of human beings
engaging in the exchanging of information. In this research, we want to make
robots understand human language and communicate with each other through
the human language, and to realize man–machine interactive and humanoid–
robot interactive. Therefore, this research mainly studies NAO robots’ speech
recognition and humanoid communication between double -humanoid robots.
This paper introduces the future direction and application prospect of speech
recognition as well as its basic method and knowledge of speech recognition
fields. This research also proposes the application of the most advanced
method—establishment of the… More >
Open Access
ARTICLE
Vijayalakshmi. K1,*, Anandan. P2
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 303-311, 2020, DOI:10.31209/2020.100000165
Abstract The advent of sensors that are light in weight, small-sized, low power and are
enabled by wireless network has led to growth of Wireless Sensor Networks
(WSNs) in multiple areas of applications. The key problems faced in WSNs are
decreased network lifetime and time delay in transmission of data. Several key
issues in the WSN design can be addressed using the Multi-Objective
Optimization (MOO) Algorithms. The selection of the Cluster Head is a NP Hard
optimization problem in nature. The CH selection is also challenging as the
sensor nodes are organized in clusters. Through partitioning of network, the
consumption of… More >
Open Access
ARTICLE
Detian Huang1, Peiting Gu2, Hsuan-Ming Feng3,*, Yanming Lin1, Lixin Zheng1
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 313-322, 2020, DOI:10.31209/2019.100000105
Abstract To tackle the problem of illumination sensitive, scale variation, and occlusion in
the Kernelized Correlation Filters (KCF) tracker, an improved robust tracking
algorithm based on KCF is proposed. Firstly, the color attribute was introduced
to represent the target, and the dimension of target features was reduced
adaptively to obtain low-dimensional and illumination-insensitive target features
with the locally linear embedding approach. Secondly, an effective appearance
model updating strategy is designed, and then the appearance model can be
adaptively updated according to the Peak-to-Sidelobe Ratio value. Finally, the
low-dimensional color features and the HOG features are utilized to determine
the target state… More >
Open Access
ARTICLE
Omer Berat Sezer*, Ahmet Murat Ozbayoglu
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 323-334, 2020, DOI:10.31209/2018.100000065
Abstract Even though computational intelligence techniques have been extensively
utilized in financial trading systems, almost all developed models use the time
series data for price prediction or identifying buy-sell points. However, in this
study we decided to use 2-D stock bar chart images directly without introducing
any additional time series associated with the underlying stock. We propose a
novel algorithmic trading model CNN-BI (Convolutional Neural Network with Bar
Images) using a 2-D Convolutional Neural Network. We generated 2-D images
of sliding windows of 30-day bar charts for Dow 30 stocks and trained a deep
Convolutional Neural Network (CNN) model for our… More >
Open Access
ARTICLE
Thamotharan B1,*, Venkatraman B2, Chandrasekaran S3
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 335-340, 2020, DOI:10.31209/2019.100000156
Abstract Accumulation of impurities within cold trap device results in degradation of
efficient performance in a nuclear reactor systems. The impurities have to be
identified and the device has to be replaced periodically based on the
accumulation level. Though there are a few techniques available to identify
these impurities from the cold trap device, there are certain limitations in these
techniques. In order to overcome these constraints, a new harmless and easy
approach for identifying and separating the impurities using the radiographic
images of cold traps is proposed in this paper. It includes a new segmentation
algorithm to segregate the deposited… More >
Open Access
ARTICLE
Xin Liu1,*, Yujuan Si1,2, Di Wang1
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 341-351, 2020, DOI:10.31209/2019.100000104
Abstract As a biological signal existing in the human living body, the electrocardiogram
(ECG) contains abundantly personal information and fulfils the basic
characteristics of identity recognition. It has been widely used in the field of
individual identification research in recent years. The common process of
identity recognition includes three steps: ECG signals preprocessing, feature
extraction and processing, beat classification recognition. However, the existing
ECG classification models are sensitive to limitations of database type and
extracted features dimension, which makes classification accuracy difficult to
improve and cannot meet the needs of practical applications. To tackle the
problem, this paper proposes to build… More >
Open Access
ARTICLE
Abid Nisar1, Waheed Iqbal1,*, Fawaz Bokhari1, Faisal Bukhari1, Khaled Almustafa2
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 353-365, 2020, DOI:10.31209/2019.100000159
Abstract The adaptive resource provisioning of cloud-hosted applications is enabled to
provide a better quality of services to the users of applications. Most of the
cloud-hosted applications follow the multi-tier architecture model. However, it is
challenging to adaptively provision the resources of multi-tier applications. In
this paper, we propose an auto-scaling method to dynamically scale resources
for multi-tier web applications. The proposed method exploits the horizontal
scaling at the web server tier and vertical scaling at the database tier
dynamically to maintain response time guarantees. We evaluated our proposed
method on Amazon Web Services using a real web application. The extensive… More >
Open Access
ARTICLE
Yao-Liang Chung1,*, Hung-Yuan Chung2, Yu-Shan Chen2
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 367-383, 2020, DOI:10.31209/2020.100000206
Abstract In this study, we introduce an algorithm which is based on a series of wellknown algorithms and mainly uses an improved dark channel prior algorithm
and the White-Patch Retinex algorithm (both are heterogeneous algorithms) in
order to effectively remove the haze from a single image. When used in
conjunction with a heterogeneous architecture, the value of the algorithm
becomes even greater. With an effective design and a novel procedure, the
proposed algorithm can not only restore a clear image, but also solve the halo
effect, color distortion, and long operating time issues resulting from the dark
channel prior. Rich experimental… More >
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