Abstract: In this paper we use the property of co-occurrence
matrix in finding parallel lines in binary pictures for fingerprint
identification. In our proposed algorithm, we reduce the noise by
filtering the fingerprint images and then transfer the fingerprint
images to binary images using a proper threshold. Next, we divide
the binary images into some regions having parallel lines in the same
direction. The lines in each region have a specific angle that can be
used for comparison. This method is simple, performs the
comparison step quickly and has a good resistance in the presence of
the noise.
Abstract: The paper suggests for the first time the use of dynamic programming techniques for optimal risk reduction in the railway industry. It is shown that by using the concept ‘amount of removed risk by a risk reduction option’, the problem related to optimal allocation of a fixed budget to achieve a maximum risk reduction in the railway industry can be reduced to an optimisation problem from dynamic programming. For n risk reduction options and size of the available risk reduction budget B (expressed as integer number), the worst-case running time of the proposed algorithm is O (n x (B+1)), which makes the proposed method a very efficient tool
for solving the optimal risk reduction problem in the railway industry.
Abstract: The Ramon preparation is received from a plant; it is destined for external treatment of inflammations in post-surgery period. The Ramon is a biogenic immune stimulator accelerating metabolism, contributing to improvement of blood indexes, having general tonic, anti-inflammatory and bactericidal effect.
Abstract: Efficient luminescence is reported for the first time in Eu2+ activated double Chlorides A2BCl4 (A=Alkali metal, B=Alkaline earth element). A simple wet-chemical preparation is described. Emission intensities are comparable to that of the commercial phosphor. Excitation covers near UV region. These phosphors may be useful for applications like solid state lighting, scintillation detectors and X-ray storage using photo-stimulable phosphors.
Abstract: Calcium [Ca2+] is an important second messenger
which plays an important role in signal transduction. There are
several parameters that affect its concentration profile like buffer
source etc. The effect of stationary immobile buffer on Ca2+
concentration has been incorporated which is a very important
parameter needed to be taken into account in order to make the
model more realistic. Interdependence of all the important parameters
like diffusion coefficient and influx over [Ca2+] profile has been
studied. Model is developed in the form of advection diffusion
equation together with buffer concentration. A program has been
developed using finite volume method for the entire problem and
simulated on an AMD-Turion 32-bit machine to compute the
numerical results.
Abstract: User satisfaction is one of the most used success
indicators in the research of information system (IS). Literature
shows user expectations have great influence on user satisfaction.
Both expectation and satisfaction of users are important for Hospital
Information Systems (HIS). Education, IS experience, age, attitude
towards change, business title, sex and working unit of the hospital,
are examined as the potential determinant of the medical users’
expectations. Data about medical user expectations are collected by
the “Expectation Questionnaire” developed for this study.
Expectation data are used for calculating the Expectation Meeting
Ratio (EMR) with the evaluation framework also developed for this
study. The internal consistencies of the answers to the questionnaire
are measured by Cronbach´s Alpha coefficient. The multivariate
analysis of medical user’s EMRs of HIS is performed by forward
stepwise binary logistic regression analysis. Education and business
title is appeared to be the determinants of expectations from HIS.
Abstract: Saturated hydraulic conductivity is one of the soil
hydraulic properties which is widely used in environmental studies
especially subsurface ground water. Since, its direct measurement is
time consuming and therefore costly, indirect methods such as
pedotransfer functions have been developed based on multiple linear
regression equations and neural networks model in order to estimate
saturated hydraulic conductivity from readily available soil
properties e.g. sand, silt, and clay contents, bulk density, and organic
matter. The objective of this study was to develop neural networks
(NNs) model to estimate saturated hydraulic conductivity from
available parameters such as sand and clay contents, bulk density,
van Genuchten retention model parameters (i.e. r
θ , α , and n) as well
as effective porosity. We used two methods to calculate effective
porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s
θ is
saturated water content, FC θ is water content retained at -33 kPa
matric potential, and inf θ is water content at the inflection point.
Total of 311 soil samples from the UNSODA database was divided
into three groups as 187 for the training, 62 for the validation (to
avoid over training), and 62 for the test of NNs model. A commercial
neural network toolbox of MATLAB software with a multi-layer
perceptron model and back propagation algorithm were used for the
training procedure. The statistical parameters such as correlation
coefficient (R2), and mean square error (MSE) were also used to
evaluate the developed NNs model. The best number of neurons in
the middle layer of NNs model for methods (1) and (2) were
calculated 44 and 6, respectively. The R2 and MSE values of the test
phase were determined for method (1), 0.94 and 0.0016, and for
method (2), 0.98 and 0.00065, respectively, which shows that method
(2) estimates saturated hydraulic conductivity better than method (1).
Abstract: Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.
Abstract: This study presents a simulation model for converting coal to methanol, based on gasification technology with the commercial chemical process simulator, Pro/II® V8.1.1. The methanol plant consists of air separation unit (ASU), gasification unit, gas clean-up unit, and methanol synthetic unit. The clean syngas is produced with the first three operating units, and the model has been verified with the reference data from United States Environment Protection Agency. The liquid phase methanol (LPMEOHTM) process is adopted in the methanol synthetic unit. Clean syngas goes through gas handing section to reach the reaction requirement, reactor loop/catalyst to generate methanol, and methanol distillation to get desired purity over 99.9 wt%. The ratio of the total energy combined with methanol and dimethyl ether to that of feed coal is 78.5% (gross efficiency). The net efficiency is 64.2% with the internal power consumption taken into account, based on the assumption that the efficiency of electricity generation is 40%.
Abstract: In this study, we sought to investigate the mercury
removal efficiency of manganese oxides from natural gas. The
fundamental studies on mercury removal with manganese oxides
sorbents were carried out in a laboratory scale fixed bed reactor at 30
°C with a mixture of methane (20%) and nitrogen gas laden with 4.8
ppb of elemental mercury. Manganese oxides with varying surface
area and crystalline phase were prepared by conventional precipitation
method in this study. The effects of surface area, crystallinity and
other metal oxides on mercury removal efficiency were investigated.
Effect of Ag impregnation on mercury removal efficiency was also
investigated. Ag supported on metal oxide such titania and zirconia as
reference materials were also used in this study for comparison. The
characteristics of mercury removal reaction with manganese oxide
was investigated using a temperature programmed desorption (TPD)
technique.
Manganese oxides showed very high Hg removal activity (about
73-93% Hg removal) for first time use. Surface area of the manganese
oxide samples decreased after heat-treatment and resulted in complete
loss of Hg removal ability for repeated use after Hg desorption in the
case of amorphous MnO2, and 75% loss of the initial Hg removal
activity for the crystalline MnO2. Mercury desorption efficiency of
crystalline MnO2 was very low (37%) for first time use and high (98%)
after second time use. Residual potassium content in MnO2 may have
some effect on the thermal stability of the adsorbed Hg species.
Desorption of Hg from manganese oxides occurs at much higher
temperatures (with a peak at 400 °C) than Ag/TiO2 or Ag/ZrO2.
Mercury may be captured on manganese oxides in the form of mercury
manganese oxide.
Abstract: In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.
Abstract: Many multimedia communication applications require a
source to transmit messages to multiple destinations subject to quality
of service (QoS) delay constraint. To support delay constrained
multicast communications, computer networks need to guarantee an
upper bound end-to-end delay from the source node to each of
the destination nodes. This is known as multicast delay problem.
On the other hand, if the same message fails to arrive at each
destination node at the same time, there may arise inconsistency and
unfairness problem among users. This is related to multicast delayvariation
problem. The problem to find a minimum cost multicast
tree with delay and delay-variation constraints has been proven to
be NP-Complete. In this paper, we propose an efficient heuristic
algorithm, namely, Economic Delay and Delay-Variation Bounded
Multicast (EDVBM) algorithm, based on a novel heuristic function,
to construct an economic delay and delay-variation bounded multicast
tree. A noteworthy feature of this algorithm is that it has very high
probability of finding the optimal solution in polynomial time with
low computational complexity.
Abstract: Markov games can be effectively used to design
controllers for nonlinear systems. The paper presents two novel
controller design algorithms by incorporating ideas from gametheory
literature that address safety and consistency issues of the
'learned' control strategy. A more widely used approach for
controller design is the H∞ optimal control, which suffers from high
computational demand and at times, may be infeasible. We generate
an optimal control policy for the agent (controller) via a simple
Linear Program enabling the controller to learn about the unknown
environment. The controller is facing an unknown environment and
in our formulation this environment corresponds to the behavior rules
of the noise modeled as the opponent. Proposed approaches aim to
achieve 'safe-consistent' and 'safe-universally consistent' controller
behavior by hybridizing 'min-max', 'fictitious play' and 'cautious
fictitious play' approaches drawn from game theory. We empirically
evaluate the approaches on a simulated Inverted Pendulum swing-up
task and compare its performance against standard Q learning.
Abstract: Waste problem is becoming a future problem all over the world. Magnesium wastes which can be used in recycling processes are produced by many industrial activities. Magnesium borates which have useful properties such as; high heat resistance, corrosion resistance, supermechanical strength, superinsulation, light weight, high coefficient of elasticity and so on. Addition, magnesium borates have great potential in the development of ceramic and detergents industry, whisker-reinforced composites, antiwear, and reducing friction additives.
In this study, using the starting materials of waste magnesium and H3BO3 the hydrothermal method was applied at a moderate temperature of 70oC with different reaction times. Several reaction times of waste magnesium to H3BO3 were selected as; 30, 60, 120, 240 minutes. After the synthesis, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) techniques were applied to products. As a result, the forms of Admontite [MgO(B2O3)3.7(H2O)] and Mcallisterite [Mg2(B6O7(OH)6)2.9(H2O)] were synthesized.
Abstract: Variational methods for optical flow estimation are
known for their excellent performance. The method proposed by Brox
et al. [5] exemplifies the strength of that framework. It combines
several concepts into single energy functional that is then minimized
according to clear numerical procedure. In this paper we propose
a modification of that algorithm starting from the spatiotemporal
gradient constancy assumption. The numerical scheme allows to
establish the connection between our model and the CLG(H) method
introduced in [18]. Experimental evaluation carried out on synthetic
sequences shows the significant superiority of the spatial variant of
the proposed method. The comparison between methods for the realworld
sequence is also enclosed.
Abstract: This work presents a methodology for the design and
manufacture of propellers oriented to the experimental verification of
theoretical results based on the combined model. The design process
begins by using algorithms in Matlab which output data contain the
coordinates of the points that define the blade airfoils, in this case the
NACA 6512 airfoil was used. The modeling for the propeller blade
was made in NX7, through the imported files in Matlab and with the
help of surfaces. Later, the hub and the clamps were also modeled.
Finally, NX 7 also made possible to create post-processed files to the
required machine. It is possible to find the block of numbers with G
& M codes about the type of driver on the machine. The file
extension is .ptp. These files made possible to manufacture the blade,
and the hub of the propeller.
Abstract: A strip domain decomposition parallel algorithm for fast direct Poisson solver is presented on a 3D Cartesian staggered grid. The parallel algorithm follows the principles of sequential algorithm for fast direct Poisson solver. Both Dirichlet and Neumann boundary conditions are addressed. Several test cases are likewise addressed in order to shed light on accuracy and efficiency in the strip domain parallelization algorithm. Actually the current implementation shows a very high efficiency when dealing with a large grid mesh up to 3.6 * 109 under massive parallel approach, which explicitly demonstrates that the proposed algorithm is ready for massive parallel computing.
Abstract: Earthquakes are natural phenomena that occur with influence of a lot of parameters such as seismic activity, changing in the ground waters' motion, changing in the water-s temperature, etc. On the other hand, the radon gas concentrations in soil vary as nonlinear generally with earthquakes. Continuous measurement of the soil radon gas is very important for determination of characteristic of the seismic activity. The radon gas changes as continuous with strain occurring within the Earth-s surface during an earthquake and effects from the physical and the chemical processes such as soil structure, soil permeability, soil temperature, the barometric pressure, etc. Therefore, at the modeling researches are notsufficient to knowthe concentration ofradon gas. In this research, we determined relationships between radon emissions based on the environmental parameters and earthquakes occurring along the East Anatolian Fault Zone (EAFZ), Turkiye and predicted magnitudes of some earthquakes with the artificial neural network (ANN) model.
Abstract: The general purpose processors that are used in
embedded systems must support constraints like execution time,
power consumption, code size and so on. On the other hand an
Application Specific Instruction-set Processor (ASIP) has advantages
in terms of power consumption, performance and flexibility. In this
paper, a 16-bit Application Specific Instruction-set processor for the
sensor data transfer is proposed. The designed processor architecture
consists of on-chip transmitter and receiver modules along with the
processing and controlling units to enable the data transmission and
reception on a single die. The data transfer is accomplished with less
number of instructions as compared with the general purpose
processor. The ASIP core operates at a maximum clock frequency of
1.132GHz with a delay of 0.883ns and consumes 569.63mW power
at an operating voltage of 1.2V. The ASIP is implemented in Verilog
HDL using the Xilinx platform on Virtex4.
Abstract: Medicinal plants are most suitable crops for ecological production systems because of their role in human health and the aim of sustainable agriculture to improve ecosystem efficiency and its products quality. Calculations include energy output (contents of energy in seed) and energy inputs (consumption of fertilizers, pesticides, labor, machines, fuel and electricity). The ratio of output of the production to inputs is called the energy outputs / inputs ratio or energy efficiency. One way to quantify essential parts of agricultural development is the energy flow method. The output / input energy ratio is proposed as the most comprehensive single factor in pursuing the objective of sustainability. Sylibum marianum L. is one of the most important medicinal plants in Iran and has effective role on health of growing population in Iran. The objective of this investigation was to find out energy efficiency in conventional and low input production system of Milk thistle. This investigation was carried out in the spring of 2005 – 2007 in the Research Station of Rangelands in Hamand - Damavand region of IRAN. This experiment was done in split-split plot based on randomized complete block design with 3 replications. Treatments were 2 production systems (Conventional and Low input system) in the main plots, 3 planting time (25 of March, 4 and 14 of April) in the sub plots and 2 seed types (Improved and Native of Khoozestan) in the sub-sub plots. Results showed that in conventional production system energy efficiency, because of higher inputs and less seed yield, was less than low input production system. Seed yield was 1199.5 and 1888 kg/ha in conventional and low input systems, respectively. Total energy inputs and out puts for conventional system was 10068544.5 and 7060515.9 kcal. These amounts for low input system were 9533885.6 and 11113191.8 kcal. Results showed that energy efficiency for seed production in conventional and low input system was 0.7 and 1.16, respectively. So, milk thistle seed production in low input system has 39.6 percent higher energy efficiency than conventional production system. Also, higher energy efficiency were found in sooner planting time (25 of March) and native seed of Khoozestan.