Abstract: Graphene, a single-atom sheet, has been considered as
the most promising material for making future nanoelectromechanical
systems as well as purely electrical switching with graphene
transistors. Graphene-based devices have advantages in scaled-up
device fabrication due to the recent progress in large area graphene
growth and lithographic patterning of graphene nanostructures. Here
we investigated its mechanical responses of circular graphene
nanoflake under the nanoindentation using classical molecular
dynamics simulations. A correlation between the load and the
indentation depth was constructed. The nanoindented force in this
work was applied to the center point of the circular graphene nanoflake
and then, the resonance frequency could be tuned by a nanoindented
depth. We found the hardening or the softening of the graphene
nanoflake during its nanoindented-deflections, and such properties
were recognized by the shift of the resonance frequency. The
calculated mechanical parameters in the force-vs-deflection plot were
in good agreement with previous experimental and theoretical works.
This proposed schematics can detect the pressure via the deflection
change or/and the resonance frequency shift, and also have great
potential for versatile applications in nanoelectromechanical systems.
Abstract: One of the challenges that higher education faces is to
find how to approach the sustainability in an inclusive way to the
student within all the different academic areas, how to move the
sustainable development from the abstract field to the operational
field. This research comes from the ecoliteracy and the pedagogical
praxis as tools for rebuilding the teaching processes inside of
universities. The purpose is to determine and describe which are the
factors involved in the process of learning particularly in the
Greenhouse-School Siembra UV. In the Greenhouse-School Siembra UV, of the University of
Veracruz, are cultivated vegetables, medicinal plants and small
cornfields under the usage of eco-technologies such as hydroponics,
Wickingbed and Hugelkultur, which main purpose is the saving of
space, labor and natural resources, as well as function as agricultural
production alternatives in the urban and periurban zones. The sample was formed with students from different academic
areas and who are actively involved in the greenhouse, as well as
institutes from the University of Veracruz and governmental and nongovernmental
departments. This project comes from a pedagogic praxis approach, from filling
the needs that the different professional profiles of the university
students have. All this with the purpose of generate a pragmatic
dialogue with the sustainability. It also comes from the necessity to
understand the factors that intervene in the students’ praxis. In this
manner is how the students are the fundamental unit in the sphere of
sustainability. As a result, it is observed that those University of Veracruz
students who are involved in the Greenhouse-school, Siembra UV,
have enriched in different levels the sense of urban and periurban
agriculture because of the diverse academic approaches they have
and the interaction between them. It is concluded that the ecotechnologies
act as fundamental tools for ecoliteracy in society,
where it is strengthen the nutritional and food security from a
sustainable development approach.
Abstract: Background: To compare the thinning patterns of the
ganglion cell-inner plexiform layer (GCIPL) and peripapillary retinal
nerve fiber layer (pRNFL) as measured using Cirrus high-definition
optical coherence tomography (HD-OCT) in patients with visual field
(VF) defects that respect the vertical meridian. Methods: Twenty eyes of eleven patients with VF defects that
respect the vertical meridian were enrolled retrospectively. The
thicknesses of the macular GCIPL and pRNFL were measured using
Cirrus HD-OCT. The 5% and 1% thinning area index (TAI) was
calculated as the proportion of abnormally thin sectors at the 5% and
1% probability level within the area corresponding to the affected VF.
The 5% and 1% TAI were compared between the GCIPL and pRNFL
measurements. Results: The color-coded GCIPL deviation map showed a
characteristic vertical thinning pattern of the GCIPL, which is also
seen in the VF of patients with brain lesions. The 5% and 1% TAI
were significantly higher in the GCIPL measurements than in the
pRNFL measurements (all P < 0.01). Conclusions: Macular GCIPL analysis clearly visualized a
characteristic topographic pattern of retinal ganglion cell (RGC) loss
in patients with VF defects that respect the vertical meridian, unlike
pRNFL measurements. Macular GCIPL measurements provide more
valuable information than pRNFL measurements for detecting the
loss of RGCs in patients with retrograde degeneration of the optic
nerve fibers.
Abstract: At the present work, highly transparent strip type
quasi-solid state dye-sensitized solar cells (DSSCs) were fabricated
through inkjet printing using nanocomposite TiO2 inks as raw
materials and tested under outdoor illumination conditions. The cells,
which can be considered as the structural units of large area modules,
were fully characterized electrically and electrochemically and after
the evaluation of the received results a large area DSSC module was
manufactured. The module design was a sandwich Z-interconnection
where the working electrode is deposited on one conductive glass and
the counter electrode on a second glass. Silver current collective
fingers were printed on the conductive glasses to make the internal
electrical connections and the adjacent cells were connected in series
and finally insulated using a UV curing resin to protect them from the
corrosive (I-/I3-) redox couple of the electrolyte. Finally, outdoor tests
were carried out to the fabricated dye-sensitized solar module and its
performance data were collected and assessed.
Abstract: Adoption of Information Systems (IS) is receiving
increasing attention such that its implications have been closely
monitored and studied by the IS management community, industry
and professional gatekeepers. Building on previous research
regarding the adoption of technology, this paper develops and
validates an integrated model of the adoption of mobile banking. The
model originates from the Technology Acceptance Model (TAM) and
the Theory of Planned Behaviour (TPB). This paper intends to offer a
preliminary scrutiny of the antecedents of the adoption of mobile
banking services in the context of a developing country. Data was
collected from Pakistan. The findings showed that an integrated TAM
and TPB model greatly explains the adoption intention of mobile
banking; and perceived behavioural control and its antecedents play a
significant role in predicting adoption Theoretical and managerial
implications of findings are presented and discussed.
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: This contribution is focused on the methodology for
identifying levels of quality and improving quality through new
logistics model in railway transport. It is oriented on the application
of dynamic quality models, which represent an innovative method of
evaluation quality services. Through this conception, time factor,
expected, and perceived quality in each moment of the transportation
process within logistics chain can be taken into account. Various
models describe the improvement of the quality which emphases the
time factor throughout the whole transportation logistics chain.
Quality of services in railway transport can be determined by the
existing level of service quality, by detecting the causes of
dissatisfaction employees but also customers, to uncover strengths
and weaknesses. This new logistics model is able to recognize critical
processes in logistic chain. It includes service quality rating that must
respect its specific properties, which are unrepeatability,
impalpability, their use right at the time they are provided and
particularly changeability, which is significant factor in the
conditions of rail transport as well. These peculiarities influence the
quality of service regarding the constantly increasing requirements
and that result in new ways of finding progressive attitudes towards
the service quality rating.
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.