Abstract: In this paper, we propose a supervised method for
color image classification based on a multilevel sigmoidal neural
network (MSNN) model. In this method, images are classified into
five categories, i.e., “Car", “Building", “Mountain", “Farm" and
“Coast". This classification is performed without any segmentation
processes. To verify the learning capabilities of the proposed method,
we compare our MSNN model with the traditional Sigmoidal Neural
Network (SNN) model. Results of comparison have shown that the
MSNN model performs better than the traditional SNN model in the
context of training run time and classification rate. Both color
moments and multi-level wavelets decomposition technique are used
to extract features from images. The proposed method has been
tested on a variety of real and synthetic images.
Abstract: Virtual environment induces simulator sickness effect
for some users. The purpose of this research is to compare the
simulation sickness relative with parallax affect in one-screen and
three-screen HoloStageTM system, measured by Simulation Sickness
Questionnaire (SSQ). The results show the subjects tested in
three-screen has less sickness than one-screen and effect from the
Oculomotor (O) more than from the Disorientation (D) and more than
from the Nausea (N) or represented in O>D>N.
Abstract: In this paper a new embedded Singly Diagonally
Implicit Runge-Kutta Nystrom fourth order in fifth order method for
solving special second order initial value problems is derived. A
standard set of test problems are tested upon and comparisons on the
numerical results are made when the same set of test problems are
reduced to first order systems and solved using the existing
embedded diagonally implicit Runge-Kutta method. The results
suggests the superiority of the new method.
Abstract: In this paper, estimation of the linear regression
model is made by ordinary least squares method and the
partially linear regression model is estimated by penalized
least squares method using smoothing spline. Then, it is
investigated that differences and similarity in the sum of
squares related for linear regression and partial linear
regression models (semi-parametric regression models). It is
denoted that the sum of squares in linear regression is reduced
to sum of squares in partial linear regression models.
Furthermore, we indicated that various sums of squares in the
linear regression are similar to different deviance statements in
partial linear regression. In addition to, coefficient of the
determination derived in linear regression model is easily
generalized to coefficient of the determination of the partial
linear regression model. For this aim, it is made two different
applications. A simulated and a real data set are considered to
prove the claim mentioned here. In this way, this study is
supported with a simulation and a real data example.
Abstract: MultiProtocol Label Switching (MPLS) is an
emerging technology that aims to address many of the existing issues
associated with packet forwarding in today-s Internetworking
environment. It provides a method of forwarding packets at a high
rate of speed by combining the speed and performance of Layer 2
with the scalability and IP intelligence of Layer 3. In a traditional IP
(Internet Protocol) routing network, a router analyzes the destination
IP address contained in the packet header. The router independently
determines the next hop for the packet using the destination IP
address and the interior gateway protocol. This process is repeated at
each hop to deliver the packet to its final destination. In contrast, in
the MPLS forwarding paradigm routers on the edge of the network
(label edge routers) attach labels to packets based on the forwarding
Equivalence class (FEC). Packets are then forwarded through the
MPLS domain, based on their associated FECs , through swapping
the labels by routers in the core of the network called label switch
routers. The act of simply swapping the label instead of referencing
the IP header of the packet in the routing table at each hop provides
a more efficient manner of forwarding packets, which in turn allows
the opportunity for traffic to be forwarded at tremendous speeds and
to have granular control over the path taken by a packet. This paper
deals with the process of MPLS forwarding mechanism,
implementation of MPLS datapath , and test results showing the
performance comparison of MPLS and IP routing. The discussion
will focus primarily on MPLS IP packet networks – by far the
most common application of MPLS today.
Abstract: Image coding based on clustering provides immediate
access to targeted features of interest in a high quality decoded
image. This approach is useful for intelligent devices, as well as for
multimedia content-based description standards. The result of image
clustering cannot be precise in some positions especially on pixels
with edge information which produce ambiguity among the clusters.
Even with a good enhancement operator based on PDE, the quality of
the decoded image will highly depend on the clustering process. In
this paper, we introduce an ambiguity cluster in image coding to
represent pixels with vagueness properties. The presence of such
cluster allows preserving some details inherent to edges as well for
uncertain pixels. It will also be very useful during the decoding phase
in which an anisotropic diffusion operator, such as Perona-Malik,
enhances the quality of the restored image. This work also offers a
comparative study to demonstrate the effectiveness of a fuzzy
clustering technique in detecting the ambiguity cluster without losing
lot of the essential image information. Several experiments have been
carried out to demonstrate the usefulness of ambiguity concept in
image compression. The coding results and the performance of the
proposed algorithms are discussed in terms of the peak signal-tonoise
ratio and the quantity of ambiguous pixels.
Abstract: Wireless Sensor Networks (WSN) are emerging
because of the developments in wireless communication technology and miniaturization of the hardware. WSN consists of a large number of low-cost, low-power, multifunctional sensor nodes to monitor physical conditions, such as temperature, sound, vibration, pressure,
motion, etc. The MAC protocol to be used in the sensor networks must be energy efficient and this should aim at conserving the energy during its operation. In this paper, with the focus of analyzing the
MAC protocols used in wireless Adhoc networks to WSN, simulation
experiments were conducted in Global Mobile Simulator
(GloMoSim) software. Number of packets sent by regular nodes, and received by sink node in different deployment strategies, total energy
spent, and the network life time have been chosen as the metric for comparison. From the results of simulation, it is evident that the IEEE 802.11 protocol performs better compared to CSMA and MACA protocols.
Abstract: Throughout this paper, a relatively new technique, the Tabu search variable selection model, is elaborated showing how it can be efficiently applied within the financial world whenever researchers come across the selection of a subset of variables from a whole set of descriptive variables under analysis. In the field of financial prediction, researchers often have to select a subset of variables from a larger set to solve different type of problems such as corporate bankruptcy prediction, personal bankruptcy prediction, mortgage, credit scoring and the Arbitrage Pricing Model (APM). Consequently, to demonstrate how the method operates and to illustrate its usefulness as well as its superiority compared to other commonly used methods, the Tabu search algorithm for variable selection is compared to two main alternative search procedures namely, the stepwise regression and the maximum R 2 improvement method. The Tabu search is then implemented in finance; where it attempts to predict corporate bankruptcy by selecting the most appropriate financial ratios and thus creating its own prediction score equation. In comparison to other methods, mostly the Altman Z-Score model, the Tabu search model produces a higher success rate in predicting correctly the failure of firms or the continuous running of existing entities.
Abstract: Tomato powder has good potential as substitute of tomato paste and other tomato products. In order to protect physicochemical properties and nutritional quality of tomato during dehydration process, investigation was carried out using different drying methods and pretreatments. Solar drier and continuous conveyor (tunnel) drier were used for dehydration where as calcium chloride (CaCl2), potassium metabisulphite (KMS), calcium chloride and potassium metabisulphite (CaCl2 +KMS), and sodium chloride (NaCl) selected for treatment.. lycopene content, dehydration ratio, rehydration ratio and non-enzymatic browning in addition to moisture, sugar and titrable acidity were studied. Results show that pre-treatment with CaCl2 and NaCl increased water removal and moisture mobility in tomato slices during drying of tomatoes. Where CaCl2 used along with KMS the NEB was recorded the least compared to other treatments and the best results were obtained while using the two chemicals in combination form. Storage studies in LDPE polymeric and metalized polyesters films showed less changes in the products packed in metallized polyester pouches and even after 6 months lycopene content did not decrease more than 20% as compared to the control sample and provide extension of shelf life in acceptable condition for 6 months. In most of the quality characteristics tunnel drier samples presented better values in comparison to solar drier.
Abstract: Modeling product configurations needs large amounts of knowledge about technical and marketing restrictions on the product. Previous attempts to automate product configurations concentrate on representations and management of the knowledge for specific domains in fixed and isolated computing environments. Since the knowledge about product configurations is subject to continuous change and hard to express, these attempts often failed to efficiently manage and exchange the knowledge in collaborative product development. In this paper, XML Topic Map (XTM) is introduced to represent and exchange the knowledge about product configurations in collaborative product development. A product configuration model based on XTM along with its merger and inference facilities enables configuration engineers in collaborative product development to manage and exchange their knowledge efficiently. A prototype implementation is also presented to demonstrate the proposed model can be applied to engineering information systems to exchange the product configuration knowledge.
Abstract: Liver segmentation is the first significant process for
liver diagnosis of the Computed Tomography. It segments the liver
structure from other abdominal organs. Sophisticated filtering techniques
are indispensable for a proper segmentation. In this paper, we
employ a 3D anisotropic diffusion as a preprocessing step. While
removing image noise, this technique preserve the significant parts
of the image, typically edges, lines or other details that are important
for the interpretation of the image. The segmentation task is done
by using thresholding with automatic threshold values selection and
finally the false liver region is eliminated using 3D connected component.
The result shows that by employing the 3D anisotropic filtering,
better liver segmentation results could be achieved eventhough simple
segmentation technique is used.
Abstract: Accurate timing alignment and stability is important
to maximize the true counts and minimize the random counts in
positron emission tomography So signals output from detectors must
be centering with the two isotopes to pre-operation and fed signals
into four units of pulse-processing units, each unit can accept up to
eight inputs. The dual source computed tomography consist two units
on the left for 15 detector signals of Cs-137 isotope and two units on
the right are for 15 detectors signals of Co-60 isotope. The gamma
spectrum consisting of either single or multiple photo peaks. This
allows for the use of energy discrimination electronic hardware
associated with the data acquisition system to acquire photon counts
data with a specific energy, even if poor energy resolution detectors
are used. This also helps to avoid counting of the Compton scatter
counts especially if a single discrete gamma photo peak is emitted by
the source as in the case of Cs-137. In this study the polyenergetic
version of the alternating minimization algorithm is applied to the
dual energy gamma computed tomography problem.
Abstract: Raisin Concentrate (RC) are the most important
products obtained in the raisin processing industries. These RC
products are now used to make the syrups, drinks and confectionery
productions and introduced as natural substitute for sugar in food
applications. Iran is a one of the biggest raisin exporter in the world
but unfortunately despite a good raw material, no serious effort to
extract the RC has been taken in Iran. Therefore, in this paper, we
determined and analyzed affected parameters on extracting RC
process and then optimizing these parameters for design the
extracting RC process in two types of raisin (round and long)
produced in Khorasan region. Two levels of solvent (1:1 and 2:1),
three levels of extraction temperature (60°C, 70°C and 80°C), and
three levels of concentration temperature (50°C, 60°C and 70°C)
were the treatments. Finally physicochemical characteristics of the
obtained concentrate such as color, viscosity, percentage of reduction
sugar, acidity and the microbial tests (mould and yeast) were
counted. The analysis was performed on the basis of factorial in the
form of completely randomized design (CRD) and Duncan's multiple
range test (DMRT) was used for the comparison of the means.
Statistical analysis of results showed that optimal conditions for
production of concentrate is round raisins when the solvent ratio was
2:1 with extraction temperature of 60°C and then concentration
temperature of 50°C. Round raisin is cheaper than the long one, and
it is more economical to concentrate production. Furthermore, round
raisin has more aromas and the less color degree with increasing the
temperature of concentration and extraction. Finally, according to
mentioned factors the concentrate of round raisin is recommended.
Abstract: Postmenopausal osteoporosis is a disorder
characterized by the progressive bone loss induced by estrogen
deficiency in postmenopausal women. This imbalance affects
calcium–phosphate metabolism and results in secondary
hyperparathyroidism. Purariae Radix (PR), the root of P. lobata
(Wild.) Ohwi, is one of the earliest medicinal herbs employed in
ancient China. PR contains a high quantity of isoflavones and their
glycosides, which are regarded as phytoestrogen. Few investigations
of PR are related to its osteoprotective effects. The present study is
designed to administer PR water extract to ovariectomized (OVX)
female rats, for the investigation of its possibly protective actions on
bone and to delineate the potential mechanisms involved. Our results
demonstrated that long-term treatment of PR could not significantly
improve bone properties, whereas it greatly ameliorated the condition
of secondary hyperparathyroidism induced by ovariectomy in those
animals. PR might be useful as alternative regimen for protecting
against postmenopausal bone loss.
Abstract: This is a genetic comparison study of Arabian Oryx
(Oryx leucoryx) population at two different locations (A &B) based
on nuclear microsatellite DNA markers. Arabian Oryx is listed as
vulnerable and endanger by the World Conservation Union (IUCN).
Thirty microsatellite markers from bovine family were applied to
investigate the genetic diversity of the Arabian Oryx and to set up a
molecular inventory. Among 30 microsatellite markers used, 13
markers were moderately polymorphic. Arabian Oryx at location A
has shown better gene diversity over location B. However, mean
number of alleles were less than location B. Data of within
population inbreeding coefficient indicates inbreeding at both
locations (A&B). Based on the analysis of polymorphic microsatellite
markers, the study revealed that Arabian Oryx need a genetically
designed breeding program.
Abstract: Truss spars are used for oil exploitation in deep and ultra-deep water if storage crude oil is not needed. The linear hydrodynamic analysis of truss spar in random sea wave load is necessary for determining the behaviour of truss spar. This understanding is not only important for design of the mooring lines, but also for optimising the truss spar design. In this paper linear hydrodynamic analysis of truss spar is carried out in frequency domain. The hydrodynamic forces are calculated using the modified Morison equation and diffraction theory. Added mass and drag coefficients of truss section computed by transmission matrix and normal acceleration and velocity component acting on each element and for hull section computed by strip theory. The stiffness properties of the truss spar can be separated into two components; hydrostatic stiffness and mooring line stiffness. Then, platform response amplitudes obtained by solved the equation of motion. This equation is non-linear due to viscous damping term therefore linearised by iteration method [1]. Finally computed RAOs and significant response amplitude and results are compared with experimental data.
Abstract: A biophysically based multilayer continuum model of the facial soft tissue composite has been developed for simulating wrinkle formation. The deformed state of the soft tissue block was determined by solving large deformation mechanics equations using the Galerkin finite element method. The proposed soft tissue model is composed of four layers with distinct mechanical properties. These include stratum corneum, epidermal-dermal layer (living epidermis and dermis), subcutaneous tissue and the underlying muscle. All the layers were treated as non-linear, isotropic Mooney Rivlin materials. Contraction of muscle fibres was approximated using a steady-state relationship between the fibre extension ratio, intracellular calcium concentration and active stress in the fibre direction. Several variations of the model parameters (stiffness and thickness of epidermal-dermal layer, thickness of subcutaneous tissue layer) have been considered.
Abstract: Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.
Abstract: Although many researchers have studied the flow
hydraulics in compound channels, there are still many complicated problems in determination of their flow rating curves. Many different
methods have been presented for these channels but extending them
for all types of compound channels with different geometrical and
hydraulic conditions is certainly difficult. In this study, by aid of nearly 400 laboratory and field data sets of geometry and flow rating
curves from 30 different straight compound sections and using artificial neural networks (ANNs), flow discharge in compound channels was estimated. 13 dimensionless input variables including relative depth, relative roughness, relative width, aspect ratio, bed
slope, main channel side slopes, flood plains side slopes and berm
inclination and one output variable (flow discharge), have been used
in ANNs. Comparison of ANNs model and traditional method
(divided channel method-DCM) shows high accuracy of ANNs model results. The results of Sensitivity analysis showed that the relative depth with 47.6 percent contribution, is the most effective input parameter for flow discharge prediction. Relative width and
relative roughness have 19.3 and 12.2 percent of importance, respectively. On the other hand, shape parameter, main channel and
flood plains side slopes with 2.1, 3.8 and 3.8 percent of contribution, have the least importance.
Abstract: Bandung city center can be deemed as economic, social and cultural center. However the city center suffers from deterioration. The retail activities tend to shift outward the city center. Numerous idyllic residences changed into business premises in two villages situated in the north part of the city during 1990s, especially after a new highway and flyover opened. According to space syntax theory, the pattern of spatial integration in the urban grid is a prime determinant of movement patterns in the system. The syntactic analysis results show the flyover has insignificant influence on street network in the city center. However the flyover has been generating a major difference in the new commercial area since it has become relatively as strategic as the city center. Besides street network, local government policy, rapid private motorization and particular condition of each site also played important roles in encouraging the current commercial areas to flourish.