Abstract: Nature is a great source of inspiration for solving
complex problems in networks. It helps to find the optimal solution.
Metaheuristic algorithm is one of the nature-inspired algorithm which
helps in solving routing problem in networks. The dynamic features,
changing of topology frequently and limited bandwidth make the
routing, challenging in MANET. Implementation of appropriate
routing algorithms leads to the efficient transmission of data in
mobile ad hoc networks. The algorithms that are inspired by the
principles of naturally-distributed/collective behavior of social
colonies have shown excellence in dealing with complex
optimization problems. Thus some of the bio-inspired metaheuristic
algorithms help to increase the efficiency of routing in ad hoc
networks. This survey work presents the overview of bio-inspired
metaheuristic algorithms which support the efficiency of routing in
mobile ad hoc networks.
Abstract: The web’s increased popularity has included a huge
amount of information, due to which automated web page
classification systems are essential to improve search engines’
performance. Web pages have many features like HTML or XML
tags, hyperlinks, URLs and text contents which can be considered
during an automated classification process. It is known that Webpage
classification is enhanced by hyperlinks as it reflects Web page
linkages. The aim of this study is to reduce the number of features to
be used to improve the accuracy of the classification of web pages. In
this paper, a novel feature selection method using an improved
Particle Swarm Optimization (PSO) using principle of evolution is
proposed. The extracted features were tested on the WebKB dataset
using a parallel Neural Network to reduce the computational cost.
Abstract: The air transport impact on environment is more than
ever a limitative obstacle to the aeronautical industry continuous
growth. Over the last decades, considerable effort has been carried
out in order to obtain quieter aircraft solutions, whether by changing
the original design or investigating more silent maneuvers. The
noise propagated by rotating surfaces is one of the most important
sources of annoyance, being present in most aerial vehicles. Bearing
this is mind, CEIIA developed a new computational chain for
noise prediction with in-house software tools to obtain solutions in
relatively short time without using excessive computer resources. This
work is based on the new acoustic tool, which aims to predict the
rotor noise generated during steady and maneuvering flight, making
use of the flexibility of the C language and the advantages of GPU
programming in terms of velocity. The acoustic tool is based in the
Formulation 1A of Farassat, capable of predicting two important
types of noise: the loading and thickness noise. The present work
describes the most important features of the acoustic tool, presenting
its most relevant results and framework analyses for helicopters and
UAV quadrotors.
Abstract: This paper presents an efficient fusion algorithm for
iris images to generate stable feature for recognition in unconstrained
environment. Recently, iris recognition systems are focused on real
scenarios in our daily life without the subject’s cooperation. Under
large variation in the environment, the objective of this paper is to
combine information from multiple images of the same iris. The
result of image fusion is a new image which is more stable for further
iris recognition than each original noise iris image. A wavelet-based
approach for multi-resolution image fusion is applied in the fusion
process. The detection of the iris image is based on Adaboost
algorithm and then local binary pattern (LBP) histogram is then
applied to texture classification with the weighting scheme.
Experiment showed that the generated features from the proposed
fusion algorithm can improve the performance for verification system
through iris recognition.
Abstract: The inherent skin patterns created at the joints in the
finger exterior are referred as finger knuckle-print. It is exploited to
identify a person in a unique manner because the finger knuckle print
is greatly affluent in textures. In biometric system, the region of
interest is utilized for the feature extraction algorithm. In this paper,
local and global features are extracted separately. Fast Discrete
Orthonormal Stockwell Transform is exploited to extract the local
features. Global feature is attained by escalating the size of Fast
Discrete Orthonormal Stockwell Transform to infinity. Two features
are fused to increase the recognition accuracy. A matching distance is
calculated for both the features individually. Then two distances are
merged mutually to acquire the final matching distance. The
proposed scheme gives the better performance in terms of equal error
rate and correct recognition rate.
Abstract: As the use of geothermal energy grows internationally
more effort is required to monitor and protect areas with rare and
important geothermal surface features. A number of approaches are
presented for developing and calibrating numerical geothermal
reservoir models that are capable of accurately representing
geothermal surface features. The approaches are discussed in the
context of cases studies of the Rotorua geothermal system and the
Orakei-korako geothermal system, both of which contain important
surface features. The results show that models are able to match the
available field data accurately and hence can be used as valuable
tools for predicting the future response of the systems to changes in
use.
Abstract: Speech Segmentation is the measure of the change
point detection for partitioning an input speech signal into regions
each of which accords to only one speaker. In this paper, we apply
two features based on multi-scale product (MP) of the clean speech,
namely the spectral centroid of MP, and the zero crossings rate of
MP. We focus on multi-scale product analysis as an important tool
for segmentation extraction. The MP is based on making the product
of the speech wavelet transform coefficients (WTC). We have
estimated our method on the Keele database. The results show the
effectiveness of our method. It indicates that the two features can find
word boundaries, and extracted the segments of the clean speech.
Abstract: Neurons in the nervous system communicate with
each other by producing electrical signals called spikes. To
investigate the physiological function of nervous system it is essential
to study the activity of neurons by detecting and sorting spikes in the
recorded signal. In this paper a method is proposed for considering
the spike sorting problem which is based on the nonlinear modeling
of spikes using exponential autoregressive model. The genetic
algorithm is utilized for model parameter estimation. In this regard
some selected model coefficients are used as features for sorting
purposes. For optimal selection of model coefficients, self-organizing
feature map is used. The results show that modeling of spikes with
nonlinear autoregressive model outperforms its linear counterpart.
Also the extracted features based on the coefficients of exponential
autoregressive model are better than wavelet based extracted features
and get more compact and well-separated clusters. In the case of
spikes different in small-scale structures where principal component
analysis fails to get separated clouds in the feature space, the
proposed method can obtain well-separated cluster which removes
the necessity of applying complex classifiers.
Abstract: Currently, there is excessively growing information
about places on Facebook, which is the largest social network but
such information is not explicitly organized and ranked. Therefore
users cannot exploit such data to recommend places conveniently and
quickly. This paper proposes a Facebook application and an Android
application that recommend places based on the number of check-ins
of those places, the distance of those places from the current location,
the number of people who like Facebook page of those places, and
the number of talking about of those places. Related Facebook data is
gathered via Facebook API requests. The experimental results of the
developed applications show that the applications can recommend
places and rank interesting places from the most to the least. We have
found that the average satisfied score of the proposed Facebook
application is 4.8 out of 5. The users’ satisfaction can increase by
adding the app features that support personalization in terms of
interests and preferences.
Abstract: The study of the electrical signals produced by neural
activities of human brain is called Electroencephalography. In this
paper, we propose an automatic and efficient EEG signal
classification approach. The proposed approach is used to classify the
EEG signal into two classes: epileptic seizure or not. In the proposed
approach, we start with extracting the features by applying Discrete
Wavelet Transform (DWT) in order to decompose the EEG signals
into sub-bands. These features, extracted from details and
approximation coefficients of DWT sub-bands, are used as input to
Principal Component Analysis (PCA). The classification is based on
reducing the feature dimension using PCA and deriving the supportvectors
using Support Vector Machine (SVM). The experimental are
performed on real and standard dataset. A very high level of
classification accuracy is obtained in the result of classification.
Abstract: The industrial process adds to engineering wood
products features absent in solid wood, with homogeneous structure
and reduced defects, improved physical and mechanical properties,
bio-deterioration, resistance and better dimensional stability,
improving quality and increasing the reliability of structures wood.
These features combined with using fast-growing trees, make them
environmentally ecological products, ensuring a strong consumer
market. The wood I-joists are manufactured by the industrial profiles
bonding flange and web, an important aspect of the production of
wooden I-beams is the adhesive joint that bonds the web to the
flange. Adhesives can effectively transfer and distribute stresses,
thereby increasing the strength and stiffness of the composite. The
objective of this study is to evaluate different resins in a shear strain
specimens with the aim of analyzing the most efficient resin and
possibility of using national products, reducing the manufacturing
cost. First was conducted a literature review, where established the
geometry and materials generally used, then established and analyzed
8 national resins and produced six specimens for each.
Abstract: Image search engines rely on the surrounding textual
keywords for the retrieval of images. It is a tedious work for the
search engines like Google and Bing to interpret the user’s search
intention and to provide the desired results. The recent researches
also state that the Google image search engines do not work well on
all the images. Consequently, this leads to the emergence of efficient
image retrieval technique, which interprets the user’s search intention
and shows the desired results. In order to accomplish this task, an
efficient image re-ranking framework is required. Sequentially, to
provide best image retrieval, the new image re-ranking framework is
experimented in this paper. The implemented new image re-ranking
framework provides best image retrieval from the image dataset by
making use of re-ranking of retrieved images that is based on the
user’s desired images. This is experimented in two sections. One is
offline section and other is online section. In offline section, the reranking
framework studies differently (reference classes or Semantic
Spaces) for diverse user query keywords. The semantic signatures get
generated by combining the textual and visual features of the images.
In the online section, images are re-ranked by comparing the
semantic signatures that are obtained from the reference classes with
the user specified image query keywords. This re-ranking
methodology will increases the retrieval image efficiency and the
result will be effective to the user.
Abstract: This paper introduces novel approaches to partitioning
and mapping in terms of model-based embedded multicore system
engineering and further discusses benefits, industrial relevance and
features in common with existing approaches. In order to assess
and evaluate results, both approaches have been applied to a real
industrial application as well as to various prototypical demonstrative
applications, that have been developed and implemented for
different purposes. Evaluations show, that such applications improve
significantly according to performance, energy efficiency, meeting
timing constraints and covering maintaining issues by using
the AMALTHEA platform and the implemented approaches.
Furthermore, the model-based design provides an open, expandable,
platform independent and scalable exchange format between
OEMs, suppliers and developers on different levels. Our proposed
mechanisms provide meaningful multicore system utilization since
load balancing by means of partitioning and mapping is effectively
performed with regard to the modeled systems including hardware,
software, operating system, scheduling, constraints, configuration and
more data.
Abstract: The development, operation and maintenance of
Integrated Waste Management Systems (IWMS) affects essentially
the sustainable concern of every region. The features of such systems
have great influence on all of the components of sustainability. In
order to reach the optimal way of processes, a comprehensive
mapping of the variables affecting the future efficiency of the system
is needed such as analysis of the interconnections among the
components and modeling of their interactions. The planning of a
IWMS is based fundamentally on technical and economical
opportunities and the legal framework. Modeling the sustainability
and operation effectiveness of a certain IWMS is not in the scope of
the present research. The complexity of the systems and the large
number of the variables require the utilization of a complex approach
to model the outcomes and future risks. This complex method should
be able to evaluate the logical framework of the factors composing
the system and the interconnections between them. The authors of
this paper studied the usability of the Fuzzy Cognitive Map (FCM)
approach modeling the future operation of IWMS’s. The approach
requires two input data set. One is the connection matrix containing
all the factors affecting the system in focus with all the
interconnections. The other input data set is the time series, a
retrospective reconstruction of the weights and roles of the factors.
This paper introduces a novel method to develop time series by
content analysis.
Abstract: Solenoid operated electromagnetic control valve
(ECV) playing an important role for car’s air conditioning control
system. ECV is used in external variable displacement swash plate
type compressor and controls the entire air conditioning system by
means of a pulse width modulation (PWM) input signal supplying
from an external source (controller). Complete form of ECV contains
number of internal features like valve body, core, valve guide,
plunger, guide pin, plunger spring, bellows etc. While designing the
ECV; dimensions of different internal items must meet the standard
requirements as it is quite challenging. In this research paper,
especially the dimensioning of ECV body and its three pressure ports
through which the air/refrigerant passes are considered. Here internal
leakage test analysis of ECV body is being carried out from its
discharge port (Pd) to crankcase port (Pc) when the guide valve is
placed inside it. The experiments have made both in ordinary and
digital system using different assumptions and thereafter compare the
results.
Abstract: Karst term is the determiner of a variety of areas or
landforms and unique perspectives that have been formed in result of
the of the ingredients dissolution of rocks constituter by natural
waters. Shiraz area with an area of 5322km2 is located in the simple
folded belt in the southern part of Zagros Mountain of Fars, and is
surrounded with Limestone Mountains (Asmari formation). Shiraz
area is located in Calcareous areas. The infrastructure of this city is
lime and absorbing wells that the city can influence the Limestone
dissolution and those accelerate its rate and increase the cavitation
below the surface. Dasht-e Arjan is a graben, which has been created
as the result of activity of two normal faults in its east and west sides.
It is a complete sample of Karst plains (Polje) which has been created
with the help of tectonic forces (fault) and dissolution process of
water in Asmari limestone formation. It is located 60km. off south
west of Shiraz (on Kazeroon-Shiraz road). In 1971, UNESCO has
recognized this plain as a reserve of biosphere. It is considered as one
of the world’s most beautiful geological phenomena, so that most of
the world’s geologists are interested in visiting this place. The
purpose of this paper is to identify and introduce landscapes of Karst
features shiraz city and Dasht-e Arjan including Karst dissolution
features (Lapiez, Karst springs, dolines, caves, underground caves,
ponors, and Karst valleys), anticlines and synclines, and Arjan Lake.
Abstract: Web-based Cognitive Writing Instruction (WeCWI)’s
contribution towards language development can be divided into
linguistic and non-linguistic perspectives. In linguistic perspective,
WeCWI focuses on the literacy and language discoveries, while the
cognitive and psychological discoveries are the hubs in non-linguistic
perspective. In linguistic perspective, WeCWI draws attention to free
reading and enterprises, which are supported by the language
acquisition theories. Besides, the adoption of process genre approach
as a hybrid guided writing approach fosters literacy development.
Literacy and language developments are interconnected in the
communication process; hence, WeCWI encourages meaningful
discussion based on the interactionist theory that involves input,
negotiation, output, and interactional feedback. Rooted in the elearning
interaction-based model, WeCWI promotes online
discussion via synchronous and asynchronous communications,
which allows interactions happened among the learners, instructor,
and digital content. In non-linguistic perspective, WeCWI highlights
on the contribution of reading, discussion, and writing towards
cognitive development. Based on the inquiry models, learners’
critical thinking is fostered during information exploration process
through interaction and questioning. Lastly, to lower writing anxiety,
WeCWI develops the instructional tool with supportive features to
facilitate the writing process. To bring a positive user experience to
the learner, WeCWI aims to create the instructional tool with
different interface designs based on two different types of perceptual
learning style.
Abstract: Passing the entrance exam to a university is a major
step in one's life. University entrance exam commonly known as
Kankor is the nationwide entrance exam in Afghanistan. This
examination is prerequisite for all public and private higher education
institutions at undergraduate level. It is usually taken by students who
are graduated from high schools. In this paper, we reflect the major
educational school graduates issues and propose ICT-based test
preparation environment, known as ‘Online Kankor Exam Prep
System’ to give students the tools to help them pass the university
entrance exam on the first try. The system is based on Intelligent
Tutoring System (ITS), which introduced an essential package of
educational technology for learners that features: (I) exam-focused
questions and content; (ii) self-assessment environment; and (iii) test
preparation strategies in order to help students to acquire the necessary
skills in their carrier and keep them up-to-date with instruction.
Abstract: We have developed a new computer program in
Fortran 90, in order to obtain numerical solutions of a system
of Relativistic Magnetohydrodynamics partial differential equations
with predetermined gravitation (GRMHD), capable of simulating
the formation of relativistic jets from the accretion disk of matter
up to his ejection. Initially we carried out a study on numerical
methods of unidimensional Finite Volume, namely Lax-Friedrichs,
Lax-Wendroff, Nessyahu-Tadmor method and Godunov methods
dependent on Riemann problems, applied to equations Euler in
order to verify their main features and make comparisons among
those methods. It was then implemented the method of Finite
Volume Centered of Nessyahu-Tadmor, a numerical schemes that
has a formulation free and without dimensional separation of
Riemann problem solvers, even in two or more spatial dimensions,
at this point, already applied in equations GRMHD. Finally, the
Nessyahu-Tadmor method was possible to obtain stable numerical
solutions - without spurious oscillations or excessive dissipation -
from the magnetized accretion disk process in rotation with respect
to a central black hole (BH) Schwarzschild and immersed in a
magnetosphere, for the ejection of matter in the form of jet over a
distance of fourteen times the radius of the BH, a record in terms
of astrophysical simulation of this kind. Also in our simulations,
we managed to get substructures jets. A great advantage obtained
was that, with the our code, we got simulate GRMHD equations in
a simple personal computer.
Abstract: Nowadays social media information, such as news,
links, images, or VDOs, is shared extensively. However, the
effectiveness of disseminating information through social media
lacks in quality: less fact checking, more biases, and several rumors.
Many researchers have investigated about credibility on Twitter, but
there is no the research report about credibility information on
Facebook. This paper proposes features for measuring credibility on
Facebook information. We developed the system for credibility on
Facebook. First, we have developed FB credibility evaluator for
measuring credibility of each post by manual human’s labelling. We
then collected the training data for creating a model using Support
Vector Machine (SVM). Secondly, we developed a chrome extension
of FB credibility for Facebook users to evaluate the credibility of
each post. Based on the usage analysis of our FB credibility chrome
extension, about 81% of users’ responses agree with suggested
credibility automatically computed by the proposed system.