Abstract: In this paper, we describe an application for face
recognition. Many studies have used local descriptors to characterize
a face, the performance of these local descriptors remain low by
global descriptors (working on the entire image). The application of
local descriptors (cutting image into blocks) must be able to store
both the advantages of global and local methods in the Discrete
Cosine Transform (DCT) domain. This system uses neural network
techniques. The letter method provides a good compromise between
the two approaches in terms of simplifying of calculation and
classifying performance. Finally, we compare our results with those
obtained from other local and global conventional approaches.
Abstract: The traditional rhythms of the West African country
of Guinea have played a centuries-long role in defining the different
people groups that make up the country. Throughout their history,
before and since colonization by the French, the different ethnicities
have used their traditional music as a distinct part of their historical
identities. That is starting to change. Guinea is an impoverished
nation created in the early twentieth-century with little regard for the
history and cultures of the people who were included. The traditional
rhythms of the different people groups and their heritages have
remained. Fifteen individual traditional Guinean rhythms were
chosen to represent popular rhythms from the four geographical
regions of Guinea. Each rhythm was traced back to its native village
and video recorded on-site by as many different local performing
groups as could be located. The cyclical patterns rhythms were
transcribed via a circular, spatial design and then copied into a box
notation system where sounds happening at the same time could be
studied. These rhythms were analyzed for their consistency-overperformance
in a Fundamental Rhythm Pattern analysis so rhythms
could be compared for how they are changing through different
performances. The analysis showed that the traditional rhythm
performances of the Middle and Forest Guinea regions were the most
cohesive and showed the least evidence of change between
performances. The role of music in each of these regions is both
limited and focused. The Coastal and High Guinea regions have
much in common historically through their ethnic history and
modern-day trade connections, but the rhythm performances seem to
be less consistent and demonstrate more changes in how they are
performed today. In each of these regions the role and usage of music
is much freer and wide-spread. In spite of advances being made as a
country, different ethnic groups still frequently only respond and
participate (dance and sing) to the music of their native ethnicity.
There is some evidence that this self-imposed musical barrier is
beginning to change and evolve, partially through the development of
better roads, more access to electricity and technology, the nationwide
Ebola health crisis, and a growing self-identification as a
unified nation.
Abstract: Digital cameras to reduce cost, use an image sensor to
capture color images. Color Filter Array (CFA) in digital cameras
permits only one of the three primary (red-green-blue) colors to be
sensed in a pixel and interpolates the two missing components
through a method named demosaicking. Captured data is interpolated
into a full color image and compressed in applications. Color
interpolation before compression leads to data redundancy. This
paper proposes a new Vector Quantization (VQ) technique to
construct a VQ codebook with Differential Evolution (DE)
Algorithm. The new technique is compared to conventional Linde-
Buzo-Gray (LBG) method.
Abstract: In this paper, we present an application of Riemannian
geometry for processing non-Euclidean image data. We consider the
image as residing in a Riemannian manifold, for developing a new
method to brain edge detection and brain extraction. Automating this
process is a challenge due to the high diversity in appearance brain
tissue, among different patients and sequences. The main contribution, in this paper, is the use of an edge-based
anisotropic diffusion tensor for the segmentation task by integrating
both image edge geometry and Riemannian manifold (geodesic,
metric tensor) to regularize the convergence contour and extract
complex anatomical structures. We check the accuracy of the
segmentation results on simulated brain MRI scans of single
T1-weighted, T2-weighted and Proton Density sequences. We
validate our approach using two different databases: BrainWeb
database, and MRI Multiple sclerosis Database (MRI MS DB). We
have compared, qualitatively and quantitatively, our approach with
the well-known brain extraction algorithms. We show that using
a Riemannian manifolds to medical image analysis improves the
efficient results to brain extraction, in real time, outperforming the
results of the standard techniques.
Abstract: The use of wireless technology in industrial networks
has gained vast attraction in recent years. In this paper, we have
thoroughly analyzed the effect of contention window (CW) size on
the performance of IEEE 802.11-based industrial wireless networks
(IWN), from delay and reliability perspective. Results show that the
default values of CWmin, CWmax, and retry limit (RL) are far from
the optimum performance due to the industrial application
characteristics, including short packet and noisy environment. In this
paper, an adaptive CW algorithm (payload-dependent) has been
proposed to minimize the average delay. Finally a simple, but
effective CW and RL setting has been proposed for industrial
applications which outperforms the minimum-average-delay solution
from maximum delay and jitter perspective, at the cost of a little
higher average delay. Simulation results show an improvement of up
to 20%, 25%, and 30% in average delay, maximum delay and jitter
respectively.
Abstract: Prediction of maximum local scour is necessary for
the safety and economical design of the bridges. A number of
equations have been developed over the years to predict local scour
depth using laboratory data and a few pier equations have also been
proposed using field data. Most of these equations are empirical in
nature as indicated by the past publications. In this paper attempts
have been made to compute local depth of scour around bridge pier in
dimensional and non-dimensional form by using linear regression,
simple regression and SVM (Poly & Rbf) techniques along with few
conventional empirical equations. The outcome of this study suggests
that the SVM (Poly & Rbf) based modeling can be employed as an
alternate to linear regression, simple regression and the conventional
empirical equations in predicting scour depth of bridge piers. The
results of present study on the basis of non-dimensional form of
bridge pier scour indicate the improvement in the performance of
SVM (Poly & Rbf) in comparison to dimensional form of scour.
Abstract: Exact solution of an unsteady MHD flow of elasticoviscous
fluid through a porous media in a tube of elliptic cross
section under the influence of magnetic field and constant pressure
gradient has been obtained in this paper. Initially, the flow is
generated by a constant pressure gradient. After attaining the steady
state, the pressure gradient is suddenly withdrawn and the resulting
fluid motion in a tube of elliptical cross section by taking into
account of the porosity factor and magnetic parameter of the
bounding surface is investigated. The problem is solved in two-stages
the first stage is a steady motion in tube under the influence of a
constant pressure gradient, the second stage concern with an unsteady
motion. The problem is solved employing separation of variables
technique. The results are expressed in terms of a non-dimensional
porosity parameter, magnetic parameter and elastico-viscosity
parameter, which depends on the Non-Newtonian coefficient. The
flow parameters are found to be identical with that of Newtonian case
as elastic-viscosity parameter, magnetic parameter tends to zero, and
porosity tends to infinity. The numerical results were simulated in
MATLAB software to analyze the effect of Elastico-viscous
parameter, porosity parameter, and magnetic parameter on velocity
profile. Boundary conditions were satisfied. It is seen that the effect
of elastico-viscosity parameter, porosity parameter and magnetic
parameter of the bounding surface has significant effect on the
velocity parameter.
Abstract: In this paper, a comparative performance analysis of
mostly used four nonlinearity cancellation techniques used to realize
the passive resistor by MOS transistors, is presented. The comparison
is done by using an integrator circuit which is employing sequentially
Op-amp, OTRA and ICCII as active element. All of the circuits are
implemented by MOS-C realization and simulated by PSPICE
program using 0.35μm process TSMC MOSIS model parameters.
With MOS-C realization, the circuits became electronically tunable
and fully integrable which is very important in IC design. The output
waveforms, frequency responses, THD analysis results and features
of the nonlinearity cancellation techniques are also given.
Abstract: The subject of this paper is to review, comparative
analysis and simulation of selected components of power electronic
systems (PES), consistent with the concept of a more electric aircraft
(MEA). Comparative analysis and simulation in software
environment MATLAB / Simulink were carried out on the base of a
group of representatives of civil aircraft (B-787, A-380) and military
(F-22 Raptor, F-35) in the context of multi-pulse converters used in
them (6- and 12-pulse, and 18- and 24-pulse), which are key
components of high-tech electronics on-board power systems of
autonomous power systems (ASE) of modern aircraft (airplanes of
the future).
Abstract: People, throughout the history, have made estimates
and inferences about the future by using their past experiences.
Developing information technologies and the improvements in the
database management systems make it possible to extract useful
information from knowledge in hand for the strategic decisions.
Therefore, different methods have been developed. Data mining by
association rules learning is one of such methods. Apriori algorithm,
one of the well-known association rules learning algorithms, is not
commonly used in spatio-temporal data sets. However, it is possible
to embed time and space features into the data sets and make Apriori
algorithm a suitable data mining technique for learning spatiotemporal
association rules. Lake Van, the largest lake of Turkey, is a
closed basin. This feature causes the volume of the lake to increase or
decrease as a result of change in water amount it holds. In this study,
evaporation, humidity, lake altitude, amount of rainfall and
temperature parameters recorded in Lake Van region throughout the
years are used by the Apriori algorithm and a spatio-temporal data
mining application is developed to identify overflows and newlyformed
soil regions (underflows) occurring in the coastal parts of
Lake Van. Identifying possible reasons of overflows and underflows
may be used to alert the experts to take precautions and make the
necessary investments.
Abstract: The critical concern of satellite operations is to ensure
the health and safety of satellites. The worst case in this perspective
is probably the loss of a mission, but the more common interruption
of satellite functionality can result in compromised mission
objectives. All the data acquiring from the spacecraft are known as
Telemetry (TM), which contains the wealth information related to the
health of all its subsystems. Each single item of information is
contained in a telemetry parameter, which represents a time-variant
property (i.e. a status or a measurement) to be checked. As a
consequence, there is a continuous improvement of TM monitoring
systems to reduce the time required to respond to changes in a
satellite's state of health. A fast conception of the current state of the
satellite is thus very important to respond to occurring failures.
Statistical multivariate latent techniques are one of the vital learning
tools that are used to tackle the problem above coherently.
Information extraction from such rich data sources using advanced
statistical methodologies is a challenging task due to the massive
volume of data. To solve this problem, in this paper, we present a
proposed unsupervised learning algorithm based on Principle
Component Analysis (PCA) technique. The algorithm is particularly
applied on an actual remote sensing spacecraft. Data from the
Attitude Determination and Control System (ADCS) was acquired
under two operation conditions: normal and faulty states. The models
were built and tested under these conditions, and the results show that
the algorithm could successfully differentiate between these
operations conditions. Furthermore, the algorithm provides
competent information in prediction as well as adding more insight
and physical interpretation to the ADCS operation.
Abstract: Electronic mediums such as websites, feeds, blogs and
social media sites are on a daily basis influencing our decision
making, are improving our productivity and are shaping futures of
many consumers and service/product providers. This research
identifies that both customers and business providers heavily rely on
smart phone applications. Based on this, mobile applications
available on iTunes store were studied. It was identified that fruit and
vegetable related applications used by consumers can broadly be
categorized into purchase applications, diaries, tracking health
applications, trip farm location and cooking applications. On the
other hand, applications used by farmers can broadly be classified as:
weather tracking, pests / fertilizer applications and general social
media applications such as Facebook. To blur this farmer-consumer
application divide, our research utilizes Context Specific
eTransformation Framework and based on it identifies characteristic
future consumer-farmer applications will need to have so that the
current divide can be narrowed and consequently better farmerconsumer
supply chain link established.
Abstract: This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.
Abstract: Revenue leakages are one of the major challenges
manufacturers face in production processes, as most of the input
materials that should emanate as products from the lines are lost as
waste. Rather than generating income from material input which is
meant to end-up as products, losses are further incurred as costs in
order to manage waste generated. In addition, due to the lack of a
clear view of the flow of resources on the lines from input to output
stage, acquiring information on the true cost of waste generated have
become a challenge. This has therefore given birth to the
conceptualization and implementation of waste minimization
strategies by several manufacturing industries. This paper reviews the
principles and applications of three environmental management
accounting tools namely Activity-based Costing (ABC), Life-Cycle
Assessment (LCA) and Material Flow Cost Accounting (MFCA) in
the manufacturing industry and their effectiveness in curbing revenue
leakages. The paper unveils the strengths and limitations of each of
the tools; beaming a searchlight on the tool that could allow for
optimal resource utilization, transparency in production process as
well as improved cost efficiency. Findings from this review reveal
that MFCA may offer superior advantages with regards to the
provision of more detailed information (both in physical and
monetary terms) on the flow of material inputs throughout the
production process compared to the other environmental accounting
tools. This paper therefore makes a case for the adoption of MFCA as
a viable technique for the identification and reduction of waste in
production processes, and also for effective decision making by
production managers, financial advisors and other relevant
stakeholders.
Abstract: This paper evaluates the accrual based scheduling for
cloud in single and multi-resource system. Numerous organizations
benefit from Cloud computing by hosting their applications. The
cloud model provides needed access to computing with potentially
unlimited resources. Scheduling is tasks and resources mapping to a
certain optimal goal principle. Scheduling, schedules tasks to virtual
machines in accordance with adaptable time, in sequence under
transaction logic constraints. A good scheduling algorithm improves
CPU use, turnaround time, and throughput. In this paper, three realtime
cloud services scheduling algorithm for single resources and
multiple resources are investigated. Experimental results show
Resource matching algorithm performance to be superior for both
single and multi-resource scheduling when compared to benefit first
scheduling, Migration, Checkpoint algorithms.
Abstract: Imperialist Competitive Algorithm (ICA) is a recent
meta-heuristic method that is inspired by the social evolutions for
solving NP-Hard problems. The ICA is a population-based algorithm
which has achieved a great performance in comparison to other metaheuristics.
This study is about developing enhanced ICA approach to
solve the Cell Formation Problem (CFP) using sequence data. In
addition to the conventional ICA, an enhanced version of ICA,
namely EICA, applies local search techniques to add more
intensification aptitude and embed the features of exploration and
intensification more successfully. Suitable performance measures are
used to compare the proposed algorithms with some other powerful
solution approaches in the literature. In the same way, for checking
the proficiency of algorithms, forty test problems are presented. Five
benchmark problems have sequence data, and other ones are based on
0-1 matrices modified to sequence based problems. Computational
results elucidate the efficiency of the EICA in solving CFP problems.
Abstract: The health care must be a right for people around the
world, but in order to guarantee the access to all, it is necessary to
overcome geographical barriers. Telemedicine take advantage of
Information Communication Technologies to deploy health care
services around the world. To achieve those goals, it is necessary to
use existing last mile solution to create access for home users, which
is why is necessary to establish the channel characteristics for those
kinds of services. This paper presents an analysis of network
performance of last mile solution for the use of IPTV broadcasting
with the application of streaming for telemedicine apps.
Abstract: The UK is leading in online retail and mobile
adoption. However, there is a dearth of information relating to mobile
apparel retail, and developing an understanding about consumer
browsing and purchase behaviour in m-retail channel would provide
apparel marketers, mobile website and app developers with the
necessary understanding of consumers’ needs. Despite the rapid
growth of mobile retail businesses, no published study has examined
shopping behaviour on fashion mobile apps and websites. A mixed method approach helped to understand why fashion
consumers prefer websites on smartphones, when diverse mobile
apps are also available. The following research methods were
employed: survey, eye-tracking experiments, observation, and
interview with retrospective think aloud. The mobile gaze tracking
device by SensoMotoric Instruments was used to understand
frustrations in navigation and other issues facing consumers in
mobile channel. This method helped to validate and compliment
other traditional user-testing approaches in order to optimize user
experience and enhance the development of mobile retail channel.
The study involved eight participants - females aged 18 to 35 years
old, who are existing mobile shoppers. The participants used the
Topshop mobile app and website on a smart phone to complete a task
according to a specified scenario leading to a purchase. The
comparative study was based on: duration and time spent at different
stages of the shopping journey, number of steps involved and product
pages visited, search approaches used, layout and visual clues, as
well as consumer perceptions and expectations. The results from the data analysis show significant differences in
consumer behaviour when using a mobile app or website on a smart
phone. Moreover, two types of problems were identified, namely
technical issues and human errors. Having a mobile app does not
guarantee success in satisfying mobile fashion consumers. The
differences in the layout and visual clues seem to influence the
overall shopping experience on a smart phone. The layout of search
results on the website was different from the mobile app. Therefore,
participants, in most cases, behaved differently on different
platforms. The number of product pages visited on the mobile app
was triple the number visited on the website due to a limited visibility
of products in the search results. Although, the data on traffic trends
held by retailers to date, including retail sector breakdowns for visits
and views, data on device splits and duration, might seem a valuable
source of information, it cannot explain why consumers visit many
product pages, stay longer on the website or mobile app, or abandon
the basket. A comprehensive list of pros and cons was developed by
highlighting issues for website and mobile app, and recommendations
provided. The findings suggest that fashion retailers need to be aware of
actual consumers’ behaviour on the mobile channel and their expectations in order to offer a seamless shopping experience. Added
to which is the challenge of retaining existing and acquiring new
customers. There seem to be differences in the way fashion
consumers search and shop on mobile, which need to be explored in
further studies.
Abstract: This research presents the design and analysis of solar
air-conditioning systems particularly solar chimney which is a
passive strategy for natural ventilation, and demonstrates the
structures of these systems’ using Computational Fluid Dynamic
(CFD) and finally compares the results with several examples, which
have been studied experimentally and carried out previously. In order
to improve the performance of solar chimney system, highly efficient
sub-system components are considered for the design. The general
purpose of the research is to understand how efficiently solar
chimney systems generate cooling, and is to improve the efficient of
such systems for integration with existing and future domestic
buildings.
Abstract: Government reports and published research have
flagged and brought to public attention the deteriorating condition of
a large percentage of bridges in Canada and the United States. With
the increasing number of deteriorated bridges in the US, Canada, and
around the globe, condition assessment techniques of concrete
bridges are evolving. Investigation for bridges’ defects such as
cracks, spalls, and delamination and their level of severity are the
main objectives of condition assessment. Inspection and
rehabilitation programs are being implemented to monitor and
maintain deteriorated bridge infrastructure. This paper highlights the
state-of-the art of current practices being performed for concrete
bridge inspection. The information is gathered from the literature and
through a distributed questionnaire. The current practices in concrete
bridge inspection rely on the use of hummer sounding and chain
dragging tests. Non-Destructive Testing (NDT) techniques are not
being utilized fully in the process. Nonetheless, they are being
partially utilized by the recommendation of the bridge inspector after
conducting visual inspection. Lanes are usually closed during the
performance of visual inspection and bridge inspection in general.