Abstract: This paper presents a novel approach for optimal
reconfiguration of radial distribution systems. Optimal
reconfiguration involves the selection of the best set of branches to
be opened, one each from each loop, such that the resulting radial
distribution system gets the desired performance. In this paper an
algorithm is proposed based on simple heuristic rules and identified
an effective switch status configuration of distribution system for the
minimum loss reduction. This proposed algorithm consists of two
parts; one is to determine the best switching combinations in all loops
with minimum computational effort and the other is simple optimum
power loss calculation of the best switching combination found in
part one by load flows. To demonstrate the validity of the proposed
algorithm, computer simulations are carried out on 33-bus system.
The results show that the performance of the proposed method is
better than that of the other methods.
Abstract: Multimedia distributed systems deal with heterogeneous
data, such as texts, images, graphics, video and audio. The specification
of temporal relations among different data types and distributed
sources is an open research area. This paper proposes a fully
distributed synchronization model to be used in multimedia systems.
One original aspect of the model is that it avoids the use of a common
reference (e.g. wall clock and shared memory). To achieve this, all
possible multimedia temporal relations are specified according to
their causal dependencies.
Abstract: The complexity of lignocellulosic biomass requires
a pretreatment step to improve the yield of fermentable sugars. The
efficient pretreatment of corn cobs using microwave and potassium
hydroxide and enzymatic hydrolysis was investigated. The
objective of this work was to characterize the optimal condition of
pretreatment of corn cobs using microwave and potassium
hydroxide enhance enzymatic hydrolysis. Corn cobs were
submerged in different potassium hydroxide concentration at varies
temperature and resident time. The pretreated corn cobs were
hydrolyzed to produce the reducing sugar for analysis. The
morphology and microstructure of samples were investigated by
Thermal gravimetric analysis (TGA, scanning electron microscope
(SEM), X-ray diffraction (XRD). The results showed that lignin
and hemicellulose were removed by microwave/potassium
hydroxide pretreatment. The crystallinity of the pretreated corn
cobs was higher than the untreated. This method was compared
with autoclave and conventional heating method. The results
indicated that microwave-alkali treatment was an efficient way to
improve the enzymatic hydrolysis rate by increasing its
accessibility hydrolysis enzymes.
Abstract: The IDR(s) method based on an extended IDR theorem was proposed by Sonneveld and van Gijzen. The original IDR(s) method has excellent property compared with the conventional iterative methods in terms of efficiency and small amount of memory. IDR(s) method, however, has unexpected property that relative residual 2-norm stagnates at the level of less than 10-12. In this paper, an effective strategy for stagnation detection, stagnation avoidance using adaptively information of parameter s and improvement of convergence rate itself of IDR(s) method are proposed in order to gain high accuracy of the approximated solution of IDR(s) method. Through numerical experiments, effectiveness of adaptive tuning IDR(s) method is verified and demonstrated.
Abstract: In recent years a number of applications with multirobot
systems (MRS) is growing in various areas. But their design
is in practice often difficult and algorithms are proposed for the
theoretical background and do not consider errors and noise in real
conditions, so they are not usable in real environment. These errors
are visible also in task of target localization enough, when robots
try to find and estimate the position of the target by the sensors.
Localization of target is possible also with one robot but as it was
examined target finding and localization with group of mobile robots
can estimate the target position more accurately and faster. The
accuracy of target position estimation is made by cooperation of
MRS and particle filtering. Advantage of usage the MRS with particle
filtering was tested on task of fixed target localization by group of
mobile robots.
Abstract: In this paper, an inventory model with finite and
constant replenishment rate, price dependant demand rate, time
value of money and inflation, finite time horizon, lead time and
exponential deterioration rate and with the objective of maximizing
the present worth of the total system profit is developed. Using a
dynamic programming based solution algorithm, the optimal
sequence of the cycles can be found and also different optimal
selling prices, optimal order quantities and optimal maximum
inventories can be obtained for the cycles with unequal lengths,
which have never been done before for this model. Also, a
numerical example is used to show accuracy of the solution
procedure.
Abstract: Cryptography, Image watermarking and E-banking are
filled with apparent oxymora and paradoxes. Random sequences are
used as keys to encrypt information to be used as watermark during
embedding the watermark and also to extract the watermark during
detection. Also, the keys are very much utilized for 24x7x365
banking operations. Therefore a deterministic random sequence is
very much useful for online applications. In order to obtain the same
random sequence, we need to supply the same seed to the generator.
Many researchers have used Deterministic Random Number
Generators (DRNGs) for cryptographic applications and Pseudo
Noise Random sequences (PNs) for watermarking. Even though,
there are some weaknesses in PN due to attacks, the research
community used it mostly in digital watermarking. On the other hand,
DRNGs have not been widely used in online watermarking due to its
computational complexity and non-robustness. Therefore, we have
invented a new design of generating DRNG using Pi-series to make it
useful for online Cryptographic, Digital watermarking and Banking
applications.
Abstract: Passive systems were born with the purpose of the
greatest exploitation of solar energy in cold climates and high
altitudes. They spread themselves until the 80-s all over the world
without any attention to the specific climate and the summer
behavior; this caused the deactivation of the systems due to a series
of problems connected to the summer overheating, the complex
management and the rising of the dust.
Until today the European regulation limits only the winter
consumptions without any attention to the summer behavior but, the
recent European EN 15251 underlines the relevance of the indoor
comfort, and the necessity of the analytic studies validation by
monitoring case studies.
In the porpose paper we demonstrate that the solar wall is an
efficient system both from thermal comfort and energy saving point
of view and it is the most suitable for our temperate climates because
it can be used as a passive cooling sistem too. In particular the paper
present an experimental and numerical analisys carried out on a case
study with nine different solar passive systems in Ancona, Italy.
We carried out a detailed study of the lodging provided by the
solar wall by the monitoring and the evaluation of the indoor
conditions.
Analyzing the monitored data, on the base of recognized models
of comfort (ISO, ASHRAE, Givoni-s BBCC), is emerged that the
solar wall has an optimal behavior in the middle seasons. In winter
phase this passive system gives more advantages in terms of energy
consumptions than the other systems, because it gives greater heat
gain and therefore smaller consumptions. In summer, when outside
air temperature return in the mean seasonal value, the indoor comfort
is optimal thanks to an efficient transversal ventilation activated from
the same wall.
Abstract: School homework has been synonymous with students- life in Chinese national type primary schools in Malaysia. Although many reports in the press claimed that students were burdened with too much of it, homework continues to be a common practice in national type schools that is believed to contribute to academic achievement. This study is conducted to identify the relationship between the burden of school homework and academic achievement among pupils in Chinese National Type Primary School in the state of Perak, Malaysia. A total of 284 students (142 from urban and 142 from rural) respectively were chosen as participants in this study. Variables of gender and location (urban/rural areas) has shown significant difference in student academic achievement. Female Chinese student from rural areas showed a higher mean score than males from urban area. Therefore, the Chinese language teachers should give appropriate and relevant homework to primary school students to achieve good academic performance.
Abstract: Before performing polymerase chain reactions (PCR), a feasible primer set is required. Many primer design methods have been proposed for design a feasible primer set. However, the majority of these methods require a relatively long time to obtain an optimal solution since large quantities of template DNA need to be analyzed. Furthermore, the designed primer sets usually do not provide a specific PCR product. In recent years, evolutionary computation has been applied to PCR primer design and yielded promising results. In this paper, a particle swarm optimization (PSO) algorithm is proposed to solve primer design problems associated with providing a specific product for PCR experiments. A test set of the gene CYP1A1, associated with a heightened lung cancer risk was analyzed and the comparison of accuracy and running time with the genetic algorithm (GA) and memetic algorithm (MA) was performed. A comparison of results indicated that the proposed PSO method for primer design finds optimal or near-optimal primer sets and effective PCR products in a relatively short time.
Abstract: This paper deals with a delayed single population model on time scales. With the assistance of coincidence degree theory, sufficient conditions for existence of periodic solutions are obtained. Furthermore, the better estimations for bounds of periodic solutions are established.
Abstract: The paper presents the results of research on trends in shaping of multifamily buildings in Poland on the example of Wrocław, after Polish accession to the European Union. The study is conducted within the research project: “Trends in creating of multifamily housing development since 2004, on the Wrocław study case" supported by Polish Ministry of Science and Higher Education and will be completed in November 2011. The research involves multifamily buildings completed in the last decade, in term of fundamental urbanization factors such as: building-s coefficient area, useable area, green area (biologically active surface), intensity of building development, amount of dwellings, dwelling area, amount of parking places, numbers of floors, etc. The analysis of these indicators was conducted based on the date obtained in the study of approximately one hundred new housing units, completed in Wroclaw. The analysis attempts to formulate the main trends in creating of housing policy in Poland during the last 10 years in reference to local urban policy.
Abstract: This paper presents the use of Legendre pseudospectral
method for the optimization of finite-thrust orbital transfer for
spacecrafts. In order to get an accurate solution, the System-s
dynamics equations were normalized through a dimensionless method.
The Legendre pseudospectral method is based on interpolating
functions on Legendre-Gauss-Lobatto (LGL) quadrature nodes. This
is used to transform the optimal control problem into a constrained
parameter optimization problem. The developed novel optimization
algorithm can be used to solve similar optimization problems of
spacecraft finite-thrust orbital transfer. The results of a numerical
simulation verified the validity of the proposed optimization method.
The simulation results reveal that pseudospectral optimization method
is a promising method for real-time trajectory optimization and
provides good accuracy and fast convergence.
Abstract: In this paper, we propose a robust face relighting
technique by using spherical space properties. The proposed method
is done for reducing the illumination effects on face recognition.
Given a single 2D face image, we relight the face object by
extracting the nine spherical harmonic bases and the face spherical
illumination coefficients. First, an internal training illumination
database is generated by computing face albedo and face normal
from 2D images under different lighting conditions. Based on the
generated database, we analyze the target face pixels and compare
them with the training bootstrap by using pre-generated tiles. In this
work, practical real time processing speed and small image size were
considered when designing the framework. In contrast to other works,
our technique requires no 3D face models for the training process
and takes a single 2D image as an input. Experimental results on
publicly available databases show that the proposed technique works
well under severe lighting conditions with significant improvements
on the face recognition rates.
Abstract: We analyze the effectivity of different pseudo noise (PN) and orthogonal sequences for encrypting speech signals in terms of perceptual intelligence. Speech signal can be viewed as sequence of correlated samples and each sample as sequence of bits. The residual intelligibility of the speech signal can be reduced by removing the correlation among the speech samples. PN sequences have random like properties that help in reducing the correlation among speech samples. The mean square aperiodic auto-correlation (MSAAC) and the mean square aperiodic cross-correlation (MSACC) measures are used to test the randomness of the PN sequences. Results of the investigation show the effectivity of large Kasami sequences for this purpose among many PN sequences.
Abstract: In this paper, we focus on the fusion of images from
different sources using multiresolution wavelet transforms. Based on
reviews of popular image fusion techniques used in data analysis,
different pixel and energy based methods are experimented. A novel
architecture with a hybrid algorithm is proposed which applies pixel
based maximum selection rule to low frequency approximations and
filter mask based fusion to high frequency details of wavelet
decomposition. The key feature of hybrid architecture is the
combination of advantages of pixel and region based fusion in a
single image which can help the development of sophisticated
algorithms enhancing the edges and structural details. A Graphical
User Interface is developed for image fusion to make the research
outcomes available to the end user. To utilize GUI capabilities for
medical, industrial and commercial activities without MATLAB
installation, a standalone executable application is also developed
using Matlab Compiler Runtime.
Abstract: Imprecision is a long-standing problem in CAD design
and high accuracy image-based reconstruction applications. The visual
hull which is the closed silhouette equivalent shape of the objects
of interest is an important concept in image-based reconstruction.
We extend the domain-theoretic framework, which is a robust and
imprecision capturing geometric model, to analyze the imprecision in
the output shape when the input vertices are given with imprecision.
Under this framework, we show an efficient algorithm to generate the
2D partial visual hull which represents the exact information of the
visual hull with only basic imprecision assumptions. We also show
how the visual hull from polyhedra problem can be efficiently solved
in the context of imprecise input.
Abstract: In this paper, our focus is to assure a global frequency synchronization in OFDMA-based wireless mesh networks with local information. To acquire the global synchronization in distributed manner, we propose a novel distributed frequency synchronization (DFS) method. DFS is a method that carrier frequencies of distributed nodes converge to a common value by repetitive estimation and averaging step and sharing step. Experimental results show that DFS achieves noteworthy better synchronization success probability than existing schemes in OFDMA-based mesh networks where the estimation error is presented.
Abstract: This paper argues that increased uncertainty, in certain
situations, may actually encourage investment. Since earlier studies
mostly base their arguments on the assumption of geometric Brownian
motion, the study extends the assumption to alternative stochastic
processes, such as mixed diffusion-jump, mean-reverting process, and
jump amplitude process. A general approach of Monte Carlo
simulation is developed to derive optimal investment trigger for the
situation that the closed-form solution could not be readily obtained
under the assumption of alternative process. The main finding is that
the overall effect of uncertainty on investment is interpreted by the
probability of investing, and the relationship appears to be an invested
U-shaped curve between uncertainty and investment. The implication
is that uncertainty does not always discourage investment even under
several sources of uncertainty. Furthermore, high-risk projects are not
always dominated by low-risk projects because the high-risk projects
may have a positive realization effect on encouraging investment.
Abstract: On-line (near infrared) spectroscopy is widely used to support the operation of complex process systems. Information extracted from spectral database can be used to estimate unmeasured product properties and monitor the operation of the process. These techniques are based on looking for similar spectra by nearest neighborhood algorithms and distance based searching methods. Search for nearest neighbors in the spectral space is an NP-hard problem, the computational complexity increases by the number of points in the discrete spectrum and the number of samples in the database. To reduce the calculation time some kind of indexing could be used. The main idea presented in this paper is to combine indexing and visualization techniques to reduce the computational requirement of estimation algorithms by providing a two dimensional indexing that can also be used to visualize the structure of the spectral database. This 2D visualization of spectral database does not only support application of distance and similarity based techniques but enables the utilization of advanced clustering and prediction algorithms based on the Delaunay tessellation of the mapped spectral space. This means the prediction has not to use the high dimension space but can be based on the mapped space too. The results illustrate that the proposed method is able to segment (cluster) spectral databases and detect outliers that are not suitable for instance based learning algorithms.