Abstract: The kinematics of manipulators is a central problem in the automatic control of robot manipulators. Theoretical background for the analysis of the 5 Dof Lynx-6 educational Robot Arm kinematics is presented in this paper. The kinematics problem is defined as the transformation from the Cartesian space to the joint space and vice versa. The Denavit-Harbenterg (D-H) model of representation is used to model robot links and joints in this study. Both forward and inverse kinematics solutions for this educational manipulator are presented, An effective method is suggested to decrease multiple solutions in inverse kinematics. A visual software package, named MSG, is also developed for testing Motional Characteristics of the Lynx-6 Robot arm. The kinematics solutions of the software package were found to be identical with the robot arm-s physical motional behaviors.
Abstract: Full adders are important components in applications
such as digital signal processors (DSP) architectures and
microprocessors. In addition to its main task, which is adding two
numbers, it participates in many other useful operations such as
subtraction, multiplication, division,, address calculation,..etc. In
most of these systems the adder lies in the critical path that
determines the overall speed of the system. So enhancing the
performance of the 1-bit full adder cell (the building block of the
adder) is a significant goal.Demands for the low power VLSI have
been pushing the development of aggressive design methodologies to
reduce the power consumption drastically. To meet the growing
demand, we propose a new low power adder cell by sacrificing the
MOS Transistor count that reduces the serious threshold loss
problem, considerably increases the speed and decreases the power
when compared to the static energy recovery full (SERF) adder. So a
new improved 14T CMOS l-bit full adder cell is presented in this
paper. Results show 50% improvement in threshold loss problem,
45% improvement in speed and considerable power consumption
over the SERF adder and other different types of adders with
comparable performance.
Abstract: In this work, a radial basis function (RBF) neural network is developed for the identification of hyperbolic distributed parameter systems (DPSs). This empirical model is based only on process input-output data and used for the estimation of the controlled variables at specific locations, without the need of online solution of partial differential equations (PDEs). The nonlinear model that is obtained is suitably transformed to a nonlinear state space formulation that also takes into account the model mismatch. A stable robust control law is implemented for the attenuation of external disturbances. The proposed identification and control methodology is applied on a long duct, a common component of thermal systems, for a flow based control of temperature distribution. The closed loop performance is significantly improved in comparison to existing control methodologies.
Abstract: Repeated observation of a given area over time yields
potential for many forms of change detection analysis. These
repeated observations are confounded in terms of radiometric
consistency due to changes in sensor calibration over time,
differences in illumination, observation angles and variation in
atmospheric effects.
This paper demonstrates applicability of an empirical relative
radiometric normalization method to a set of multitemporal cloudy
images acquired by Resourcesat1 LISS III sensor. Objective of this
study is to detect and remove cloud cover and normalize an image
radiometrically. Cloud detection is achieved by using Average
Brightness Threshold (ABT) algorithm. The detected cloud is
removed and replaced with data from another images of the same
area. After cloud removal, the proposed normalization method is
applied to reduce the radiometric influence caused by non surface
factors. This process identifies landscape elements whose reflectance
values are nearly constant over time, i.e. the subset of non-changing
pixels are identified using frequency based correlation technique. The
quality of radiometric normalization is statistically assessed by R2
value and mean square error (MSE) between each pair of analogous
band.
Abstract: In this paper, by using Mawhin-s continuation theorem of coincidence degree and a method based on delay differential inequality, some sufficient conditions are obtained for the existence and global exponential stability of periodic solutions of cellular neural networks with distributed delays and impulses on time scales. The results of this paper generalized previously known results.
Abstract: The aim of this study was to assess the effect of LAB
isolated from Iranian native olives on the opportunistic skin
pathogens, Pseudomonas aeruginosa and Staphylococcus aureus.
Lactic Acid Bacteria were isolated from the brine of each sample in
the prior of time. The samples were spread on MRS agar for isolation
of lactobacillus and for lactococcus. 28 strains of labs were isolated.
The labs were centrifuged, the supernatant was strewed and pellet
was used to inoculation in wells or at blank disks. 20μl of each pellet
was inoculated to blank disks and 40μl of each pellet was inoculated
to each well. The result of disk and well diffusion agar against these
pathogens were confirmed each other. The size of inhibition zone
was different according to the type of bacteria, the method and the
concentrations of labs.
Abstract: There are reports of gas and oil wells fire due to different accidents. Many different methods are used for fire fighting in gas and oil industry. Traditional fire extinguishing techniques are mostly faced with many problems and are usually time consuming and needs lots of equipments. Besides, they cause damages to facilities, and create health and environmental problems. This article proposes innovative approach in fire extinguishing techniques in oil and gas industry, especially applicable for burning oil wells located offshore. Fire extinguishment employing a turbojet is a novel approach which can help to extinguishment the fire in short period of time. Divergent and convergent turbojets modeled in laboratory scale along with a high pressure flame were used. Different experiments were conducted to determine the relationship between output discharges of trumpet and oil wells. The results were corrected and the relationship between dimensionless parameters of flame and fire extinguishment distances and also the output discharge of turbojet and oil wells in specified distances are demonstrated by specific curves.
Abstract: This paper proposes a method that discovers sequential patterns corresponding to user-s interests from sequential data. This method expresses the interests as constraint patterns. The constraint patterns can define relationships among attributes of the items composing the data. The method recursively decomposes the constraint patterns into constraint subpatterns. The method evaluates the constraint subpatterns in order to efficiently discover sequential patterns satisfying the constraint patterns. Also, this paper applies the method to the sequential data composed of stock price indexes and verifies its effectiveness through comparing it with a method without using the constraint patterns.
Abstract: The modeling of water transfer in the unsaturated zone
uses techniques and methods of the soil physics to solve the
Richards-s equation. However, there is a disaccord between the size
of the measurements provided by the soil physics and the size of the
fields of hydrological modeling problem, to which is added the
strong spatial variability of soil hydraulic properties. The objective of
this work was to develop a methodology to estimate the
hydrodynamic parameters for modeling water transfers at different
hydrological scales in the soil-plant atmosphere systems.
Abstract: This paper presents an automatic feature recognition
method based on center-surround difference detecting and fuzzy logic
that can be applied in ground-penetrating radar (GPR) image
processing. Adopted center-surround difference method, the salient
local image regions are extracted from the GPR images as features of
detected objects. And fuzzy logic strategy is used to match the
detected features and features in template database. This way, the
problem of objects detecting, which is the key problem in GPR image
processing, can be converted into two steps, feature extracting and
matching. The contributions of these skills make the system have the
ability to deal with changes in scale, antenna and noises. The results of
experiments also prove that the system has higher ratio of features
sensing in using GPR to image the subsurface structures.
Abstract: Supplier selection, in real situation, is affected by
several qualitative and quantitative factors and is one of the most
important activities of purchasing department. Since at the time of
evaluating suppliers against the criteria or factors, decision makers
(DMS) do not have precise, exact and complete information, supplier
selection becomes more difficult. In this case, Grey theory helps us
to deal with this problem of uncertainty. Here, we apply Technique
for Order Preference by Similarity to Ideal Solution (TOPSIS)
method to evaluate and select the best supplier by using interval
fuzzy numbers. Through this article, we compare TOPSIS with some
other approaches and afterward demonstrate that the concept of
TOPSIS is very important for ranking and selecting right supplier.
Abstract: Single nucleotide polymorphisms (SNPs) hold much promise as a basis for disease-gene association. However, research is limited by the cost of genotyping the tremendous number of SNPs. Therefore, it is important to identify a small subset of informative SNPs, the so-called tag SNPs. This subset consists of selected SNPs of the genotypes, and accurately represents the rest of the SNPs. Furthermore, an effective evaluation method is needed to evaluate prediction accuracy of a set of tag SNPs. In this paper, a genetic algorithm (GA) is applied to tag SNP problems, and the K-nearest neighbor (K-NN) serves as a prediction method of tag SNP selection. The experimental data used was taken from the HapMap project; it consists of genotype data rather than haplotype data. The proposed method consistently identified tag SNPs with considerably better prediction accuracy than methods from the literature. At the same time, the number of tag SNPs identified was smaller than the number of tag SNPs in the other methods. The run time of the proposed method was much shorter than the run time of the SVM/STSA method when the same accuracy was reached.
Abstract: The electrolyte stirring method of anodization etching
process for manufacturing porous silicon (PS) is reported in this work.
Two experimental setups of nature air stirring (PS-ASM) and
electrolyte stirring (PS-ESM) are employed to clarify the influence of
stirring mechanisms on electrochemical etching process. Compared to
traditional fabrication without any stirring apparatus (PS-TM), a large
plateau region of PS surface structure is obtained from samples with
both stirring methods by the 3D-profiler measurement. Moreover, the
light emission response is also improved by both proposed electrolyte
stirring methods due to the cycling force in electrolyte could
effectively enhance etch-carrier distribution while the electrochemical
etching process is made. According to the analysis of statistical
calculation of photoluminescence (PL) intensity, lower standard
deviations are obtained from PS-samples with studied stirring methods,
i.e. the uniformity of PL-intensity is effectively improved. The
calculated deviations of PL-intensity are 93.2, 74.5 and 64,
respectively, for PS-TM, PS-ASM and PS-ESM.
Abstract: The potential of economically cheaper cellulose
containing natural materials like rice husk was assessed for nickel
adsorption from aqueous solutions. The effects of pH, contact time,
sorbent dose, initial metal ion concentration and temperature on the
uptake of nickel were studied in batch process. The removal of nickel
was dependent on the physico-chemical characteristics of the
adsorbent, adsorbate concentration and other studied process
parameters. The sorption data has been correlated with Langmuir,
Freundlich and Dubinin-Radush kevich (D-R) adsorption models. It
was found that Freundlich and Langmuir isotherms fitted well to the
data. Maximum nickel removal was observed at pH 6.0. The
efficiency of rice husk for nickel removal was 51.8% for dilute
solutions at 20 g L-1 adsorbent dose. FTIR, SEM and EDAX were
recorded before and after adsorption to explore the number and
position of the functional groups available for nickel binding on to
the studied adsorbent and changes in surface morphology and
elemental constitution of the adsorbent. Pseudo-second order model
explains the nickel kinetics more effectively. Reusability of the
adsorbent was examined by desorption in which HCl eluted 78.93%
nickel. The results revealed that nickel is considerably adsorbed on
rice husk and it could be and economic method for the removal of
nickel from aqueous solutions.
Abstract: In this paper, a novel deinterlacing algorithm is
proposed. The proposed algorithm approximates the distribution of the
luminance into a polynomial function. Instead of using one
polynomial function for all pixels, different polynomial functions are
used for the uniform, texture, and directional edge regions. The
function coefficients for each region are computed by matrix
multiplications. Experimental results demonstrate that the proposed
method performs better than the conventional algorithms.
Abstract: We address the problem of joint beamforming and multipath channel parameters estimation in Wideband Code Division Multiple Access (WCDMA) communication systems that employ Multiple-Access Interference (MAI) suppression techniques in the uplink (from mobile to base station). Most of the existing schemes rely on time multiplex a training sequence with the user data. In WCDMA, the channel parameters can also be estimated from a code multiplexed common pilot channel (CPICH) that could be corrupted by strong interference resulting in a bad estimate. In this paper, we present new methods to combine interference suppression together with channel estimation when using multiple receiving antennas by using adaptive signal processing techniques. Computer simulation is used to compare between the proposed methods and the existing conventional estimation techniques.
Abstract: Serial Analysis of Gene Expression is a powerful
quantification technique for generating cell or tissue gene expression
data. The profile of the gene expression of cell or tissue in several
different states is difficult for biologists to analyze because of the large
number of genes typically involved. However, feature selection in
machine learning can successfully reduce this problem. The method
allows reducing the features (genes) in specific SAGE data, and
determines only relevant genes. In this study, we used a genetic
algorithm to implement feature selection, and evaluate the
classification accuracy of the selected features with the K-nearest
neighbor method. In order to validate the proposed method, we used
two SAGE data sets for testing. The results of this study conclusively
prove that the number of features of the original SAGE data set can be
significantly reduced and higher classification accuracy can be
achieved.
Abstract: The launching nose plays an important role in the
incremental launching construction. The parameters of the launching
nose essentially affect the internal forces of the girder during the
construction. The appropriate parameters can decrease the internal
forces in the girder and save the material and reduce the cost. The
simplified structural model, which is made with displacement method
according to the characteristic of incremental launching construction
and the variation rule of the internal forces, calculates and analyzes the
effect of the length, the rigidity and weight of launch nose on the
internal forces of girder during the incremental launching
construction. The method, which can calculate the launching nose
parameters for the optimum incremental launching construction, is
achieved. This method is simple, reliable and easy for practical use.
Abstract: Group contribution based models are widely used in
industrial applications for its convenience and flexibility. Although a
number of group contribution models have been proposed, there were
certain limitations inherent to those models. Models based on group
contribution excess Gibbs free energy are limited to low pressures and
models based on equation of state (EOS) cannot properly describe
highly nonideal mixtures including acids without introducing
additional modification such as chemical theory. In the present study
new a new approach derived from quantum chemistry have been used
to calculate necessary EOS group interaction parameters. The
COSMO-RS method, based on quantum mechanics, provides a
reliable tool for fluid phase thermodynamics. Benefits of the group
contribution EOS are the consistent extension to hydrogen-bonded
mixtures and the capability to predict polymer-solvent equilibria up to
high pressures. The authors are confident that with a sufficient
parameter matrix the performance of the lattice EOS can be improved
significantly.
Abstract: Wavelet transforms are multiresolution
decompositions that can be used to analyze signals and images.
Image compression is one of major applications of wavelet
transforms in image processing. It is considered as one of the most
powerful methods that provides a high compression ratio. However,
its implementation is very time-consuming. At the other hand,
parallel computing technologies are an efficient method for image
compression using wavelets. In this paper, we propose a parallel
wavelet compression algorithm based on quadtrees. We implement
the algorithm using MatlabMPI (a parallel, message passing version
of Matlab), and compute its isoefficiency function, and show that it is
scalable. Our experimental results confirm the efficiency of the
algorithm also.