Abstract: This paper proposes an innovative methodology for
Acceptance Sampling by Variables, which is a particular category of
Statistical Quality Control dealing with the assurance of products
quality. Our contribution lies in the exploitation of machine learning
techniques to address the complexity and remedy the drawbacks of
existing approaches. More specifically, the proposed methodology
exploits Artificial Neural Networks (ANNs) to aid decision making
about the acceptance or rejection of an inspected sample. For any
type of inspection, ANNs are trained by data from corresponding
tables of a standard-s sampling plan schemes. Once trained, ANNs
can give closed-form solutions for any acceptance quality level and
sample size, thus leading to an automation of the reading of the
sampling plan tables, without any need of compromise with the
values of the specific standard chosen each time. The proposed
methodology provides enough flexibility to quality control engineers
during the inspection of their samples, allowing the consideration of
specific needs, while it also reduces the time and the cost required for
these inspections. Its applicability and advantages are demonstrated
through two numerical examples.
Abstract: This paper deals with the thermo-mechanical deformation behavior of shear deformable functionally graded ceramicmetal (FGM) plates. Theoretical formulations are based on higher order shear deformation theory with a considerable amendment in the transverse displacement using finite element method (FEM). The mechanical properties of the plate are assumed to be temperaturedependent and graded in the thickness direction according to a powerlaw distribution in terms of the volume fractions of the constituents. The temperature field is supposed to be a uniform distribution over the plate surface (XY plane) and varied in the thickness direction only. The fundamental equations for the FGM plates are obtained using variational approach by considering traction free boundary conditions on the top and bottom faces of the plate. A C0 continuous isoparametric Lagrangian finite element with thirteen degrees of freedom per node have been employed to accomplish the results. Convergence and comparison studies have been performed to demonstrate the efficiency of the present model. The numerical results are obtained for different thickness ratios, aspect ratios, volume fraction index and temperature rise with different loading and boundary conditions. Numerical results for the FGM plates are provided in dimensionless tabular and graphical forms. The results proclaim that the temperature field and the gradient in the material properties have significant role on the thermo-mechanical deformation behavior of the FGM plates.
Abstract: The technique of inducing micro ecosystem
restoration is one of aquatic ecology engineering methods used to
retrieve the polluted water. Batch scale study, pilot plant study, and
field study were carried out to observe the eutrophication using the
Inducing Ecology Restorative Symbiosis Agent (IERSA) consisting
mainly degraded products by using lactobacillus, saccharomycete,
and phycomycete. The results obtained from the experiments of the
batch scale and pilot plant study allowed us to development the
parameters for the field study. A pond, 5 m to the outlet of a lake,
with an area of 500 m2 and depth of 0.6-1.2 m containing about 500
tons of water was selected as a model. After the treatment with 10
mg IERSA/L water twice a week for 70 days, the micro restoration
mechanisms consisted of three stages (i.e., restoration, impact
maintenance, and ecology recovery experiment after impact). The
COD, TN, TKN, and chlorophyll a were reduced significantly in the
first week. Although the unexpected heavy rain and contaminate
from sewage system might slow the ecology restoration. However,
the self-cleaning function continued and the chlorophyll a reduced
for 50% in one month. In the 4th week, amoeba, paramecium, rotifer,
and red wriggle worm reappeared, and the number of fish flies
appeared up to1000 fish fries/m3. Those results proved that inducing
restorative mechanism can be applied to improve the eutrophication
and to control the growth of algae in the lakes by gaining the selfcleaning
through inducing and competition of microbes. The
situation for growth of fishes also can reach an excellent result due to
the improvement of water quality.
Abstract: Wireless sensor networks (WSNs) consist of number
of tiny, low cost and low power sensor nodes to monitor some physical phenomenon. The major limitation in these networks is the use of non-rechargeable battery having limited power supply. The
main cause of energy consumption in such networks is
communication subsystem. This paper presents an energy efficient
Cluster Cooperative Caching at Sensor (C3S) based upon grid type clustering. Sensor nodes belonging to the same cluster/grid form a
cooperative cache system for the node since the cost for
communication with them is low both in terms of energy
consumption and message exchanges. The proposed scheme uses
cache admission control and utility based data replacement policy to
ensure that more useful data is retained in the local cache of a node.
Simulation results demonstrate that C3S scheme performs better in
various performance metrics than NICoCa which is existing
cooperative caching protocol for WSNs.
Abstract: Applying corona wind as a novel technique can lead
to a great level of heat and mass transfer augmentation by using very
small amount of energy. Enhancement of forced flow evaporation
rate by applying electric field (corona wind) has been experimentally
evaluated in this study. Corona wind produced by a fine wire
electrode which is charged with positive high DC voltage impinges
to water surface and leads to evaporation enhancement by disturbing
the saturated air layer over water surface. The study was focused on
the effect of corona wind velocity, electrode spacing and air flow
velocity on the level of evaporation enhancement. Two sets of
experiments, i.e. with and without electric field, have been
conducted. Data obtained from the first experiment were used as
reference for evaluation of evaporation enhancement at the presence
of electric field. Applied voltages ranged from corona threshold
voltage to spark over voltage at 1 kV increments. The results showed
that corona wind has great enhancement effect on water evaporation
rate, but its effectiveness gradually diminishes by increasing air flow
velocity. Maximum enhancements were 7.3 and 3.6 for air velocities
of 0.125 and 1.75 m/s, respectively.
Abstract: Recently, as the scale of construction projects has
increases, more ground excavation for foundations is carried out than ever before. Consequently, damage to underground ducts (gas, water/sewage or oil pipelines, communication cables or power cable ducts) or superannuated pipelines frequently cause serious accidents
resulting in damage to life and property. (In Korea, the total length of city water pipelines was approximately 2,000 km as of the end of 2009.) In addition, large amounts of damage caused by fractures, water
and gas leakage caused by superannuation or damage to underground
ducts in construction has been reported. Therefore, a system is required to precisely detect defects and deterioration in underground
pipelines and the locations of such defects, for timely and accurate
maintenance or replacement of the ducts. In this study, a system was
developed which can locate underground structures (gas and water
pipelines, power cable ducts, etc.) in 3D-coordinates and monitor the
degree and position of defects using an Inertial Measurement Unit
(IMU) sensing technique. The system can prevent damage to underground ducts and superannuated pipelines during construction,
and provide reliable data for maintenance. The utility of the IMU sensing technique used in aircraft and ships in civil applications was
verified.
Abstract: The general idea behind the filter is to average a pixel
using other pixel values from its neighborhood, but simultaneously to
take care of important image structures such as edges. The main
concern of the proposed filter is to distinguish between any variations
of the captured digital image due to noise and due to image structure.
The edges give the image the appearance depth and sharpness. A
loss of edges makes the image appear blurred or unfocused.
However, noise smoothing and edge enhancement are traditionally
conflicting tasks. Since most noise filtering behaves like a low pass
filter, the blurring of edges and loss of detail seems a natural
consequence. Techniques to remedy this inherent conflict often
encompass generation of new noise due to enhancement.
In this work a new fuzzy filter is presented for the noise reduction
of images corrupted with additive noise. The filter consists of three
stages. (1) Define fuzzy sets in the input space to computes a fuzzy
derivative for eight different directions (2) construct a set of IFTHEN
rules by to perform fuzzy smoothing according to
contributions of neighboring pixel values and (3) define fuzzy sets in
the output space to get the filtered and edged image.
Experimental results are obtained to show the feasibility of the
proposed approach with two dimensional objects.
Abstract: Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually the effects of blurred edges and jagged artifacts in the image to some extent. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to sharpen edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (“jaggies") along the tangent directions. In order to preserve image features such as edges, corners and textures, the nonlinear diffusion coefficients are locally adjusted according to the directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Abstract: Social resilience has role to govern the local community and coastal fisheries resources toward sustainable fisheries development in tsunami affected area. This paper asses, explore and investigates of indigenous institutions, external and internal facilitators toward strengthening social resilience. Identification of the genuine organizations role had been conducted twice by using Rapid Assessment Appraisal, Focus Group Discussion, and in-depth interview for collecting primary and secondary data. Local wisdom had a contribution and adaptable to rebound social resilience. The Panglima Laot Lhok (sea commander) had determined and adapted role on recovery of the fishing community, particularly facilitated aid delivery to fishermen, as shown in anchovy fisheries relief case in Krueng Raya Bay. Toke Bangku (financial trader) had stimulated for reinforcement of advance payment and market channel. The other institutions supported upon linking and bridging connectivity among stakeholders. Collaborative governance can avoid conflict, reduce donor dependency and strengthen social resilience within fishing community.
Abstract: The purpose of this study is to investigate the
efficiency of a double-layer roof in collecting solar energy as an
application to the areas such as raising high-end temperature of
organic Rankine cycle (ORC). The by-product of the solar roof is to
reduce building air-conditioning loads. The experimental apparatus
are arranged to evaluate the effects of the solar roof in absorbing solar
energy. The flow channel is basically formed by an aluminum plate on
top of a plywood plate. The geometric configurations in which the
effects of absorbing energy is analyzed include: a bare uncovered
aluminum plate, a glass-covered aluminum plate, a
glass-covered/black-painted aluminum plate, a plate with variable
lengths, a flow channel with stuffed material (in an attempt on
enhancement of heat conduction), and a flow channel with variable
slanted angles. The experimental results show that the efficiency of
energy collection varies from 0.6 % to 11 % for the geometric
configurations mentioned above. An additional study is carried out
using CFD simulation to investigate the effects of fins on the
aluminum plate. It shows that due to vastly enhanced heat conduction,
the efficiency can reach ~23 % if 50 fins are installed on the aluminum
plate. The study shows that a double-layer roof can efficiently absorb
solar energy and substantially reduce building air-conditioning
loads. On the high end of an organic Rankine cycle, a solar pond is
used to replace the warm surface water of the sea as OTEC (ocean
thermal energy conversion) is the driving energy for the ORC. The
energy collected from the double-layered solar roof can be pumped
into the pond and raise the pond temperature as the pond surface area is
equivalently increased by nearly one-fourth of the total area of the
double-layer solar roof. The effect of raising solar pond temperature is
especially prominent if the double-layer solar roofs are installed in a
community area.
Abstract: Image enhancement is the most important challenging preprocessing for almost all applications of Image Processing. By now, various methods such as Median filter, α-trimmed mean filter, etc. have been suggested. It was proved that the α-trimmed mean filter is the modification of median and mean filters. On the other hand, ε-filters have shown excellent performance in suppressing noise. In spite of their simplicity, they achieve good results. However, conventional ε-filter is based on moving average. In this paper, we suggested a new ε-filter which utilizes α-trimmed mean. We argue that this new method gives better outcomes compared to previous ones and the experimental results confirmed this claim.
Abstract: Snoring is prevalent and is the most significant feature
of sleep-disordered breathing (SDB). Ignore the therapies of SDB will
lead to serious problems in health. Based on the research of
mechanisms, diagnosis, and treatments of snoring, oral appliances are
ensured in therapeutic effect and compliance, especially the
mandibular advancement devices (MADs). Market survey includes
commercial product reviews and patent analyses. Due to pay more
attention to the sleep medicine, the oral appliances are considered as a
standard treatment of snoring that promoted by American Academy of
Sleep Medicine (AASM). There are more and more adjustable MADs
developed since 1995. According to the patent analyses, there are
many drawbacks existed in the present design, such as uncomfortable,
high cost, bulky volume, and complex adjustment. In this study,
several new designs of the MAD are proposed.
Abstract: Recently electric vehicles are becoming popular as an
alternative of conventional fossil fuel vehicles. Conventional Internal
Combustion Engine (ICE) vehicle uses fossil fuel which contributing
a major part of overall carbon emission in the environment. Carbon
and other green house gas emission are responsible for global
warming and resulting climate change. It becomes vital to evaluate
performance of vehicle based on emission. In this paper an effort has
been made to depict the picture of emission caused by vehicle and
scenario of Australia has taken into account. Effort has been made to
compare the fossil based vehicle with electric vehicle in phases. The
study also evaluates advancement in electric vehicle technology,
required infrastructure for sustainability and future scope of
developments. This paper also includes the evaluation of electric
vehicle concept for pollution control and sustainable transport
systems in future. This study can be a benchmark for development of
electric vehicle as low carbon emission alternative for the cities of
tomorrow.
Abstract: The transient thermoelastic response of thick hollow cylinder made of functionally graded material under thermal loading is studied. The generalized coupled thermoelasticity based on the Green-Lindsay model is used. The thermal and mechanical properties of the functionally graded material are assumed to be varied in the radial direction according to a power law variation as a function of the volume fractions of the constituents. The thermal and elastic governing equations are solved by using Galerkin finite element method. All the finite element calculations were done by using commercial finite element program FlexPDE. The transient temperature, radial displacement, and thermal stresses distribution through the radial direction of the cylinder are plotted.
Abstract: Fluids are used for heat transfer in many engineering
equipments. Water, ethylene glycol and propylene glycol are some
of the common heat transfer fluids. Over the years, in an attempt to
reduce the size of the equipment and/or efficiency of the process,
various techniques have been employed to improve the heat transfer
rate of these fluids. Surface modification, use of inserts and
increased fluid velocity are some examples of heat transfer
enhancement techniques. Addition of milli or micro sized particles
to the heat transfer fluid is another way of improving heat transfer
rate. Though this looks simple, this method has practical problems
such as high pressure loss, clogging and erosion of the material of
construction. These problems can be overcome by using nanofluids,
which is a dispersion of nanosized particles in a base fluid.
Nanoparticles increase the thermal conductivity of the base fluid
manifold which in turn increases the heat transfer rate. In this work,
the heat transfer enhancement using aluminium oxide nanofluid has
been studied by computational fluid dynamic modeling of the
nanofluid flow adopting the single phase approach.
Abstract: Mechanical interaction between endothelial cells (ECs) and the extracellular matrix (or collagen gel) is known to influence the sprouting response of endothelial cells during angiogenesis. This influence is believed to impact on the capability of endothelial cells to sense soluble chemical cues. Quantitative analysis of endothelial-cell-mediated displacement of the collagen gel provides a means to explore this mechanical interaction. Existing analysis in this context is generally limited to 2D settings. In this paper, we investigate the mechanical interaction between endothelial cells and the extracellular matrix in terms of the endothelial-cellmediated displacement of the collagen gel in both 2D and 3D. Digital image correlation and Digital volume correlation are applied on confocal reflectance image stacks to analyze cell-mediated displacement of the gel. The skeleton of the sprout is extracted from phase contrast images and superimposed on the displacement field to further investigate the link between the development of the sprout and the displacement of the gel.
Abstract: Human activity is a major concern in a wide variety of
applications, such as video surveillance, human computer interface
and face image database management. Detecting and recognizing
faces is a crucial step in these applications. Furthermore, major
advancements and initiatives in security applications in the past years
have propelled face recognition technology into the spotlight. The
performance of existing face recognition systems declines significantly
if the resolution of the face image falls below a certain level.
This is especially critical in surveillance imagery where often, due to
many reasons, only low-resolution video of faces is available. If these
low-resolution images are passed to a face recognition system, the
performance is usually unacceptable. Hence, resolution plays a key
role in face recognition systems. In this paper we introduce a new
low resolution face recognition system based on mixture of expert
neural networks. In order to produce the low resolution input images
we down-sampled the 48 × 48 ORL images to 12 × 12 ones using
the nearest neighbor interpolation method and after that applying
the bicubic interpolation method yields enhanced images which is
given to the Principal Component Analysis feature extractor system.
Comparison with some of the most related methods indicates that
the proposed novel model yields excellent recognition rate in low
resolution face recognition that is the recognition rate of 100% for
the training set and 96.5% for the test set.
Abstract: In this paper, the discrete-time fuzzy BAM neural network with delays and impulses is studied. Sufficient conditions are obtained for the existence and global stability of a unique equilibrium of this class of fuzzy BAM neural networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. Some numerical examples are given to demonstrate the effectiveness of the obtained results.
Abstract: How to coordinate the behaviors of the agents through
learning is a challenging problem within multi-agent domains.
Because of its complexity, recent work has focused on how
coordinated strategies can be learned. Here we are interested in using
reinforcement learning techniques to learn the coordinated actions of a
group of agents, without requiring explicit communication among
them. However, traditional reinforcement learning methods are based
on the assumption that the environment can be modeled as Markov
Decision Process, which usually cannot be satisfied when multiple
agents coexist in the same environment. Moreover, to effectively
coordinate each agent-s behavior so as to achieve the goal, it-s
necessary to augment the state of each agent with the information
about other existing agents. Whereas, as the number of agents in a
multiagent environment increases, the state space of each agent grows
exponentially, which will cause the combinational explosion problem.
Profit sharing is one of the reinforcement learning methods that allow
agents to learn effective behaviors from their experiences even within
non-Markovian environments. In this paper, to remedy the drawback
of the original profit sharing approach that needs much memory to
store each state-action pair during the learning process, we firstly
address a kind of on-line rational profit sharing algorithm. Then, we
integrate the advantages of modular learning architecture with on-line
rational profit sharing algorithm, and propose a new modular
reinforcement learning model. The effectiveness of the technique is
demonstrated using the pursuit problem.
Abstract: A numerical method for Riccati equation is presented in this work. The method is based on the replacement of unknown functions through a truncated series of hybrid of block-pulse functions and Chebyshev polynomials. The operational matrices of derivative and product of hybrid functions are presented. These matrices together with the tau method are then utilized to transform the differential equation into a system of algebraic equations. Corresponding numerical examples are presented to demonstrate the accuracy of the proposed method.