Abstract: Antimicrobial (AM) starch-based films were
developed by incorporating chitosan and lauric acid as antimicrobial
agent into starch-based film. Chitosan has wide range of applications
as a biomaterial, but barriers still exist to its broader use due to its
physical and chemical limitations. In this work, a series of
starch/chitosan (SC) blend films containing 8% of lauric acid was
prepared by casting method. The structure of the film was
characterized by Fourier transform infrared spectroscopy (FTIR), Xray
diffraction (XRD), and scanning electron microscopy (SEM).
The results indicated that there were strong interactions were present
between the hydroxyl groups of starch and the amino groups of
chitosan resulting in a good miscibility between starch and chitosan
in the blend films. Physical properties and optical properties of the
AM starch-based film were evaluated. The AM starch-based films
incorporated with chitosan and lauric acid showed an improvement in
water vapour transmission rate (WVTR) and addition of starch
content provided more transparent films while the yellowness of the
film attributed to the higher chitosan content. The improvement in
water barrier properties was mainly attributed to the hydrophobicity
of lauric acid and optimum chitosan or starch content. AM starch
based film also showed excellent oxygen barrier. Obtaining films
with good oxygen permeability would be an indication of the
potential use of these antimicrobial packaging as a natural packaging
and an alternative packaging to the synthetic polymer to protect food
from oxidation reactions
Abstract: In this work we will present a new approach for shot transition auto-detection. Our approach is based on the analysis of Spatio-Temporal Video Slice (STVS) edges extracted from videos. The proposed approach is capable to efficiently detect both abrupt shot transitions 'cuts' and gradual ones such as fade-in, fade-out and dissolve. Compared to other techniques, our method is distinguished by its high level of precision and speed. Those performances are obtained due to minimizing the problem of the boundary shot detection to a simple 2D image partitioning problem.
Abstract: We study the dynamic response of a wind turbine
structure subjected to theoretical seismic motions, taking into account
the rotational component of ground shaking. Models are generated
for a shallow moderate crustal earthquake in the Madrid Region
(Spain). Synthetic translational and rotational time histories are
computed using the Discrete Wavenumber Method, assuming a point
source and a horizontal layered earth structure. These are used to
analyze the dynamic response of a wind turbine, represented by a
simple finite element model. Von Mises stress values at different
heights of the tower are used to study the dynamical structural
response to a set of synthetic ground motion time histories
Abstract: In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.
Abstract: Interactive installations for public spaces are a
particular kind of interactive systems, the design of which has been
the subject of several research studies. Sensor-based applications are
becoming increasingly popular, but the human-computer interaction
community is still far from reaching sound, effective large-scale
interactive installations for public spaces. The 6DSpaces project is
described in this paper as a research approach based on studying the
role of multisensory interactivity and how it can be effectively used
to approach people to digital, scientific contents. The design of an
entire scientific exhibition is described and the result was evaluated
in the real world context of a Science Centre. Conclusions bring
insight into how the human-computer interaction should be designed
in order to maximize the overall experience.
Abstract: To calculate the temperature distribution of the slab in
a hot rolled reheating furnace a mathematical model has been
developed by considering the thermal radiation in the furnace and
transient conduction in the slab. The furnace is modeled as radiating
medium with spatially varying temperature. Radiative heat flux within
the furnace including the effect of furnace walls, combustion gases,
skid beams and buttons is calculated using the FVM and is applied as
the boundary condition of the transient conduction equation of the
slab. After determining the slab emissivity by comparison between
simulation and experimental work, variation of heating characteristics
in the slab is investigated in the case of changing furnace temperature
with various time and the slab residence time is optimized with this
evaluation.
Abstract: Evolution of one-dimensional electron system under
high-energy-density (HED) conditions is investigated, using the
principle of least-action and variational method. In a single-mode
modulation model, the amplitude and spatial wavelength of the
modulation are chosen to be general coordinates. Equations of motion
are derived by considering energy conservation and force balance.
Numerical results show that under HED conditions, electron density
modulation could exist. Time dependences of amplitude and
wavelength are both positively related to the rate of energy input.
Besides, initial loading speed has a significant effect on modulation
amplitude, while wavelength relies more on loading duration.
Abstract: Metal matrix composites have been increasingly used
as materials for components in automotive and aerospace industries
because of their improved properties compared with non-reinforced
alloys. During machining the selection of appropriate machining
parameters to produce job for desired surface roughness is of great
concern considering the economy of manufacturing process. In this
study, a surface roughness prediction model using fuzzy logic is
developed for end milling of Al-SiCp metal matrix composite
component using carbide end mill cutter. The surface roughness is
modeled as a function of spindle speed (N), feed rate (f), depth of cut
(d) and the SiCp percentage (S). The predicted values surface
roughness is compared with experimental result. The model predicts
average percentage error as 4.56% and mean square error as 0.0729.
It is observed that surface roughness is most influenced by feed rate,
spindle speed and SiC percentage. Depth of cut has least influence.
Abstract: This paper presents a new methodology to study power and energy consumption in mechatronic systems early in the development process. This new approach makes use of two modeling languages to represent and simulate embedded control software and electromechanical subsystems in the discrete event and continuous time domain respectively within a single co-model. This co-model enables an accurate representation of power and energy consumption and facilitates the analysis and development of both software and electro-mechanical subsystems in parallel. This makes the engineers aware of energy-wise implications of different design alternatives and enables early trade-off analysis from the beginning of the analysis and design activities.
Abstract: In this paper performance of Puma 560
manipulator is being compared for hybrid gradient descent
and least square method learning based ANFIS controller with
hybrid Genetic Algorithm and Generalized Pattern Search
tuned radial basis function based Neuro-Fuzzy controller.
ANFIS which is based on Takagi Sugeno type Fuzzy
controller needs prior knowledge of rule base while in radial
basis function based Neuro-Fuzzy rule base knowledge is not
required. Hybrid Genetic Algorithm with generalized Pattern
Search is used for tuning weights of radial basis function
based Neuro- fuzzy controller. All the controllers are checked
for butterfly trajectory tracking and results in the form of
Cartesian and joint space errors are being compared. ANFIS
based controller is showing better performance compared to
Radial Basis Function based Neuro-Fuzzy Controller but rule
base independency of RBF based Neuro-Fuzzy gives it an
edge over ANFIS
Abstract: Given a large sparse signal, great wishes are to
reconstruct the signal precisely and accurately from lease number of
measurements as possible as it could. Although this seems possible
by theory, the difficulty is in built an algorithm to perform the
accuracy and efficiency of reconstructing. This paper proposes a new
proved method to reconstruct sparse signal depend on using new
method called Least Support Matching Pursuit (LS-OMP) merge it
with the theory of Partial Knowing Support (PSK) given new method
called Partially Knowing of Least Support Orthogonal Matching
Pursuit (PKLS-OMP).
The new methods depend on the greedy algorithm to compute the
support which depends on the number of iterations. So to make it
faster, the PKLS-OMP adds the idea of partial knowing support of its
algorithm. It shows the efficiency, simplicity, and accuracy to get
back the original signal if the sampling matrix satisfies the Restricted
Isometry Property (RIP).
Simulation results also show that it outperforms many algorithms
especially for compressible signals.
Abstract: A first intermediate roll of Sendzirmir mills was failure
by surface spalling during operation. After analyzing by visual, stereo
microscope, optical microscope, scanning electron microscope,
glow-discharged spectrometer and hardness test, respectively, the
results show that some voids and cracks existed on the contact surface
as well as subsurface. Further examination verified inadequate
hardness and inclusions were responsible for the failure of surface
spalling.
Abstract: Application of flexible structures has been
significantly, increased in industry and aerospace missions due to
their contributions and unique advantages over the rigid counterparts.
In this paper, vibration analysis of a flexible structure i.e., automobile
wiper blade is investigated and controlled. The wiper generates
unwanted noise and vibration during the wiping the rain and other
particles on windshield which may cause annoying noise in different
ranges of frequency. A two dimensional analytical modeled wiper
blade whose model accuracy is verified by numerical studies in
literature is considered in this study. Particle swarm optimization
(PSO) is employed in alliance with input shaping (IS) technique in
order to control or to attenuate the amplitude level of unwanted
noise/vibration of the wiper blade.
Abstract: Imitation learning is considered to be an effective way of teaching humanoid robots and action recognition is the key step to imitation learning. In this paper an online algorithm to recognize
parametric actions with object context is presented. Objects are key instruments in understanding an action when there is uncertainty.
Ambiguities arising in similar actions can be resolved with objectn context. We classify actions according to the changes they make to
the object space. Actions that produce the same state change in the object movement space are classified to belong to the same class. This allow us to define several classes of actions where members of
each class are connected with a semantic interpretation.
Abstract: Investigation of soil properties like Cation Exchange
Capacity (CEC) plays important roles in study of environmental
reaserches as the spatial and temporal variability of this property
have been led to development of indirect methods in estimation of
this soil characteristic. Pedotransfer functions (PTFs) provide an
alternative by estimating soil parameters from more readily available
soil data. 70 soil samples were collected from different horizons of
15 soil profiles located in the Ziaran region, Qazvin province, Iran.
Then, multivariate regression and neural network model (feedforward
back propagation network) were employed to develop a
pedotransfer function for predicting soil parameter using easily
measurable characteristics of clay and organic carbon. The
performance of the multivariate regression and neural network model
was evaluated using a test data set. In order to evaluate the models,
root mean square error (RMSE) was used. The value of RMSE and
R2 derived by ANN model for CEC were 0.47 and 0.94 respectively,
while these parameters for multivariate regression model were 0.65
and 0.88 respectively. Results showed that artificial neural network
with seven neurons in hidden layer had better performance in
predicting soil cation exchange capacity than multivariate regression.
Abstract: This paper explores the importance of privacy in a
contemporary online world. Crucial to the discussion is the idea of
the Lacanian postmodern fragmented self and the problem of how to
ensure that we have room to fully explore various aspects of our
personalities in an environment which is–or at least feels--safe and
free from observation by others. The paper begins with an
exploration of the idea of the self with particular regard to the ways
in which contemporary life and technology seems to have multiplied
the various faces or masks which we present in different contexts. A
brief history of privacy and surveillance follows. Finally, the paper
ends with an affirmation of the importance of private space as an
essential component of our spiritual and emotional well-being in
today-s wired world.
Abstract: Even though so many efforts have been taken to
renovate and renew the architecture of Miyaneh villages in cold and
dry regions of Iran-s northwest, these efforts failed due to lack of
significant study and ignoring the past and sustainable history of
those villages. Considering the overpopulation of Iran-s villages as
well as the importance in preventing their immigration to cities,
recognizing village architecture and its construction technology is of
great significance to attain sustainable residence in villages. As the
only vertical surface in the space, wall possesses its unique special
characteristics, and it is also a very important architectural element
able to provide the immunity and comfort space for the residents.
This article analyzes the characteristics of this vertical element, main
types of adobe and stone walls, locally constructed technologies,
implementation, the elements forming the walls in the frame of
village house typology of Miyaneh, which has the most villages in
East Azerbaijan, based on sustainable architectural construction
materials of walls.
Abstract: This paper presents a study of laminar to turbulent transition on a profile specifically designed for wind turbine blades, the DU91-W2-250, which belongs to a class of wind turbine dedicated airfoils, developed by Delft University of Technology. A comparison between the experimental behavior of the airfoil studied at Delft wind tunnel and the numerical predictions of the commercial CFD solver ANSYS FLUENT® has been performed. The prediction capabilities of the Spalart-Allmaras turbulence model and of the γ-θ Transitional model have been tested. A sensitivity analysis of the numerical results to the spatial domain discretization has also been performed using four different computational grids, which have been created using the mesher GAMBIT®. The comparison between experimental measurements and CFD results have allowed to determine the importance of the numerical prediction of the laminar to turbulent transition, in order not to overestimate airfoil friction drag due to a fully turbulent-regime flow computation.
Abstract: In this paper smooth trajectories are computed in the Lie group SO(2, 1) as a motion planning problem by assigning a Frenet frame to the rigid body system to optimize the cost function of the elastic energy which is spent to track a timelike curve in Minkowski space. A method is proposed to solve a motion planning problem that minimizes the integral of the Lorentz inner product of Darboux vector of a timelike curve. This method uses the coordinate free Maximum Principle of Optimal control and results in the theory of integrable Hamiltonian systems. The presence of several conversed quantities inherent in these Hamiltonian systems aids in the explicit computation of the rigid body motions.