Abstract: In this work, we developed the concept of
supercompression, i.e., compression above the compression standard
used. In this context, both compression rates are multiplied. In fact,
supercompression is based on super-resolution. That is to say,
supercompression is a data compression technique that superpose
spatial image compression on top of bit-per-pixel compression to
achieve very high compression ratios. If the compression ratio is very
high, then we use a convolutive mask inside decoder that restores the
edges, eliminating the blur. Finally, both, the encoder and the
complete decoder are implemented on General-Purpose computation
on Graphics Processing Units (GPGPU) cards. Specifically, the
mentio-ned mask is coded inside texture memory of a GPGPU.
Abstract: In this paper a study on the vibration of thin
cylindrical shells with ring supports and made of functionally graded
materials (FGMs) composed of stainless steel and nickel is presented.
Material properties vary along the thickness direction of the shell
according to volume fraction power law. The cylindrical shells have
ring supports which are arbitrarily placed along the shell and impose
zero lateral deflections. The study is carried out based on third order
shear deformation shell theory (T.S.D.T). The analysis is carried out
using Hamilton-s principle. The governing equations of motion of
FGM cylindrical shells are derived based on shear deformation
theory. Results are presented on the frequency characteristics,
influence of ring support position and the influence of boundary
conditions. The present analysis is validated by comparing results
with those available in the literature.
Abstract: Flow movement in unsaturated soil can be expressed
by a partial differential equation, named Richards equation. The
objective of this study is the finding of an appropriate implicit
numerical solution for head based Richards equation. Some of the
well known finite difference schemes (fully implicit, Crank Nicolson
and Runge-Kutta) have been utilized in this study. In addition, the
effects of different approximations of moisture capacity function,
convergence criteria and time stepping methods were evaluated. Two
different infiltration problems were solved to investigate the
performance of different schemes. These problems include of vertical
water flow in a wet and very dry soils. The numerical solutions of
two problems were compared using four evaluation criteria and the
results of comparisons showed that fully implicit scheme is better
than the other schemes. In addition, utilizing of standard chord slope
method for approximation of moisture capacity function, automatic
time stepping method and difference between two successive
iterations as convergence criterion in the fully implicit scheme can
lead to better and more reliable results for simulation of fluid
movement in different unsaturated soils.
Abstract: The competitive learning is an adaptive process in
which the neurons in a neural network gradually become sensitive to
different input pattern clusters. The basic idea behind the Kohonen-s
Self-Organizing Feature Maps (SOFM) is competitive learning.
SOFM can generate mappings from high-dimensional signal spaces
to lower dimensional topological structures. The main features of this
kind of mappings are topology preserving, feature mappings and
probability distribution approximation of input patterns. To overcome
some limitations of SOFM, e.g., a fixed number of neural units and a
topology of fixed dimensionality, Growing Self-Organizing Neural
Network (GSONN) can be used. GSONN can change its topological
structure during learning. It grows by learning and shrinks by
forgetting. To speed up the training and convergence, a new variant
of GSONN, twin growing cell structures (TGCS) is presented here.
This paper first gives an introduction to competitive learning, SOFM
and its variants. Then, we discuss some GSONN with fixed
dimensionality, which include growing cell structures, its variants
and the author-s model: TGCS. It is ended with some testing results
comparison and conclusions.
Abstract: The development of entrepreneurial competences of
farmers has been pointed out as a necessary condition for the
modernization of land in facing the phenomenon of globalization.
However, the educational processes involved in such a development
have been studied little, especially in emerging economies. This
research aims to enlighten some of the critical issues behind the early
stages of the transformation of farmers into entrepreneurs, through in
depth interviews with farmers, entrepreneurial promoters and public
officials participating in a public pilot project in Mexico. Although
major impacts were expected only in the long run, important positive
changes in the mind set of farmers and other participants were found
in early stages of the intervention. Apparently, the farmers started a
process of becoming more conscious about the importance of
preserving the aquiferous resources, as well as more market and
entrepreneurial oriented.
Abstract: Face recognition is a technique to automatically
identify or verify individuals. It receives great attention in
identification, authentication, security and many more applications.
Diverse methods had been proposed for this purpose and also a lot of
comparative studies were performed. However, researchers could not
reach unified conclusion. In this paper, we are reporting an extensive
quantitative accuracy analysis of four most widely used face
recognition algorithms: Principal Component Analysis (PCA),
Independent Component Analysis (ICA), Linear Discriminant
Analysis (LDA) and Support Vector Machine (SVM) using AT&T,
Sheffield and Bangladeshi people face databases under diverse
situations such as illumination, alignment and pose variations.
Abstract: We constructed a method of phase unwrapping for a typical wave-front by utilizing the maximizer of the posterior marginal (MPM) estimate corresponding to equilibrium statistical mechanics of the three-state Ising model on a square lattice on the basis of an analogy between statistical mechanics and Bayesian inference. We investigated the static properties of an MPM estimate from a phase diagram using Monte Carlo simulation for a typical wave-front with synthetic aperture radar (SAR) interferometry. The simulations clarified that the surface-consistency conditions were useful for extending the phase where the MPM estimate was successful in phase unwrapping with a high degree of accuracy and that introducing prior information into the MPM estimate also made it possible to extend the phase under the constraint of the surface-consistency conditions with a high degree of accuracy. We also found that the MPM estimate could be used to reconstruct the original wave-fronts more smoothly, if we appropriately tuned hyper-parameters corresponding to temperature to utilize fluctuations around the MAP solution. Also, from the viewpoint of statistical mechanics of the Q-Ising model, we found that the MPM estimate was regarded as a method for searching the ground state by utilizing thermal fluctuations under the constraint of the surface-consistency condition.
Abstract: Metallic micro parts are playing an important role in micro-fabrication industry. Recently, we have demonstrated a new deformation mechanism for micro-formability of polycrystalline materials. Different depressed micro-features smaller than the grain size have been successfully fabricated on 6061 aluminum alloy (AA6061) substrates with good fidelity. To further verify this proposed deformation mechanism that grain size is not a limiting factor, we demonstrate here that in addition of depressed features, protruded micro-features on a polycrystalline substrate can similarly be fabricated.
Abstract: This paper analysed the food security situation among
Nigerian rural farmers. Data collected on 202 rural farmers from
Benue State were analysed using descriptive and inferential statistics.
The study revealed that majority of the respondents (60.83%) had
medium dietary diversity. Furthermore, household daily calorie
requirement for the food secure households was 10,723 and the
household daily calorie consumption was 12,598, with a surplus
index of 0.04. The food security index was 1.16. The Household
daily per capita calorie consumption was 3,221.2. For the food
insecure households, the household daily calorie requirement was
20,213 and the household daily calorie consumption was 17,393. The
shortfall index was 0.14. The food security index was 0.88. The
Household daily per capita calorie consumption was 2,432.8. The
most commonly used coping strategies during food stress included
intercropping (99.2%), reliance on less preferred food (98.1%),
limiting portion size at meal times (85.8%) and crop diversification
(70.8%).
Abstract: In this work a new method for low complexity
image coding is presented, that permits different settings and great
scalability in the generation of the final bit stream. This coding
presents a continuous-tone still image compression system that
groups loss and lossless compression making use of finite arithmetic
reversible transforms. Both transformation in the space of color and
wavelet transformation are reversible. The transformed coefficients
are coded by means of a coding system in depending on a
subdivision into smaller components (CFDS) similar to the bit
importance codification. The subcomponents so obtained are
reordered by means of a highly configure alignment system
depending on the application that makes possible the re-configure of
the elements of the image and obtaining different importance levels
from which the bit stream will be generated. The subcomponents of
each importance level are coded using a variable length entropy
coding system (VBLm) that permits the generation of an embedded
bit stream. This bit stream supposes itself a bit stream that codes a
compressed still image. However, the use of a packing system on the
bit stream after the VBLm allows the realization of a final highly
scalable bit stream from a basic image level and one or several
improvement levels.
Abstract: The purpose of this study is to analyze Green IT industry in major developed countries and to suggest overall directions for IT-Energy convergence industry. Recently, IT industry is pointed out as a problem such as environmental pollution, energy exhaustion, and high energy consumption. Therefore, Green IT gets focused which concerns as solution of these problems. However, since it is a beginning stage of this convergence area, there are only a few studies of IT-Energy convergence industry. According to this, this study examined the major developed countries in terms of institution arrangements, resources, markets and companies based on Van de Ven(1999)'s social system framework that shows relationship among key components of industrial infrastructure. Subsequently, the direction of the future study of convergence on IT and Energy industry is proposed.
Abstract: The theory of Groebner Bases, which has recently been
honored with the ACM Paris Kanellakis Theory and Practice Award,
has become a crucial building block to computer algebra, and is
widely used in science, engineering, and computer science. It is wellknown
that Groebner bases computation is EXP-SPACE in a general
setting. In this paper, we give an algorithm to show that Groebner
bases computation is P-SPACE in Boolean rings. We also show that
with this discovery, the Groebner bases method can theoretically be
as efficient as other methods for automated verification of hardware
and software. Additionally, many useful and interesting properties of
Groebner bases including the ability to efficiently convert the bases
for different orders of variables making Groebner bases a promising
method in automated verification.
Abstract: Several trillion cigarettes produced worldwide annually lead to many thousands of kilograms of toxic waste. Cigarette butts (CBs) accumulate in the environment due to the poor biodegradability of the cellulose acetate filters. This paper presents some of the results from a continuing study on recycling CBs into fired clay bricks. Physico-mechanical properties of fired clay bricks manufactured with different percentages of CBs are reported and discussed. The results show that the density of fired bricks was reduced by up to 30 %, depending on the percentage of CBs incorporated into the raw materials. Similarly, the compressive strength of bricks tested decreased according to the percentage of CBs included in the mix. The thermal conductivity performance of bricks was improved by 51 and 58 % for 5 and 10 % CBs content respectively. Leaching tests were carried out to investigate the levels of possible leachates of heavy metals from the manufactured clay-CB bricks. The results revealed trace amounts of heavy metals.
Abstract: This paper presents the design and implements the prototype of an intelligent data processing framework in ubiquitous sensor networks. Much focus is put on how to handle the sensor data stream as well as the interoperability between the low-level sensor data and application clients. Our framework first addresses systematic middleware which mitigates the interaction between the application layer and low-level sensors, for the sake of analyzing a great volume of sensor data by filtering and integrating to create value-added context information. Then, an agent-based architecture is proposed for real-time data distribution to efficiently forward a specific event to the appropriate application registered in the directory service via the open interface. The prototype implementation demonstrates that our framework can host a sophisticated application on the ubiquitous sensor network and it can autonomously evolve to new middleware, taking advantages of promising technologies such as software agents, XML, cloud computing, and the like.
Abstract: Intelligent traffic surveillance technology is an issue in
the field of traffic data analysis. Therefore, we need the technology to
detect moving objects in real-time while there are variations in background and natural light. In this paper, we proposed a Weighted-Center Surround Difference
method for object detection in outdoor environments. The proposed system detects objects using the saliency map that is obtained by
analyzing the weight of each layers of Gaussian pyramid. In order to validate the effectiveness of our system, we implemented the proposed
method using a digital signal processor, TMS320DM6437.
Experimental results show that blurred noisy around objects was effectively eliminated and the object detection accuracy is improved.
Abstract: Biomimicry has many potential benefits as many
technologies found in nature are superior to their man-made
counterparts. As technological device components approach the micro
and nanoscale, surface properties such as surface adhesion and friction
may need to be taken into account. Lowering surface adhesion by
manipulating chemistry alone might no longer be sufficient for such
components and thus physical manipulation may be required.
Adhesion reduction is only one of the many surface functions
displayed by micro/nano-structured cuticles of insects. Here, we
present a mini review of our understanding of insect cuticle structures
and the relationship between the structure dimensions and the
corresponding functional mechanisms. It may be possible to introduce
additional properties to material surfaces (indeed multi-functional
properties) based on the design of natural surfaces.
Abstract: The number of cross-border student between Hong
Kong and mainland China is increasing due to an increase of
cross-border marriage between Hong Kong and mainland China. Since
the education system is different to the mainland China, the statue
Since all the children who have the right of abode in Hong Kong
entitle to have free education in Hong Kong, many of the cross-border
family prefer to send the children back to Hong Kong for their
education.
Abstract: We provide a maximum norm analysis of a finite
element Schwarz alternating method for a nonlinear elliptic boundary
value problem of the form -Δu = f(u), on two overlapping sub
domains with non matching grids. We consider a domain which is
the union of two overlapping sub domains where each sub domain
has its own independently generated grid. The two meshes being
mutually independent on the overlap region, a triangle belonging to
one triangulation does not necessarily belong to the other one. Under
a Lipschitz assumption on the nonlinearity, we establish, on each sub
domain, an optimal L∞ error estimate between the discrete Schwarz
sequence and the exact solution of the boundary value problem.
Abstract: This study investigates the electrical performance of a
planar solid oxide fuel cell unit with cross-flow configuration when the fuel utilization gets higher and the fuel inlet flow are non-uniform.
A software package in this study solves two-dimensional,
simultaneous, partial differential equations of mass, energy, and
electro-chemistry, without considering stack direction variation. The
results show that the fuel utilization increases with a decrease in the molar flow rate, and the average current density decreases when the
molar flow rate drops. In addition, non-uniform Pattern A will induce more severe happening of non-reaction area in the corner of the fuel
exit and the air inlet. This non-reaction area deteriorates the average
current density and then deteriorates the electrical performance to –7%.
Abstract: This paper aims to develop a NOx emission model of
an acid gas incinerator using Nelder-Mead least squares support
vector regression (LS-SVR). Malaysia DOE is actively imposing the
Clean Air Regulation to mandate the installation of analytical
instrumentation known as Continuous Emission Monitoring System
(CEMS) to report emission level online to DOE . As a hardware
based analyzer, CEMS is expensive, maintenance intensive and often
unreliable. Therefore, software predictive technique is often
preferred and considered as a feasible alternative to replace the
CEMS for regulatory compliance. The LS-SVR model is built based
on the emissions from an acid gas incinerator that operates in a LNG
Complex. Simulated Annealing (SA) is first used to determine the
initial hyperparameters which are then further optimized based on the
performance of the model using Nelder-Mead simplex algorithm.
The LS-SVR model is shown to outperform a benchmark model
based on backpropagation neural networks (BPNN) in both training
and testing data.