Abstract: Atlantic herring (Clupea harengus) is an important
commercial fish and shows to be more and more demanded for
human consumption. Therefore, it is very important to find good
methods for monitoring the freshness of the fish in order to keep it in
the best quality for human consumption. In this study, the fish was
stored in ice up to 2 weeks. Quality changes during storage were
assessed by the Quality Index Method (QIM), quantitative
descriptive analysis (QDA) and Torry scheme, by texture
measurements: puncture tests and Texture Profile Analysis (TPA)
tests on texture analyzer TA.XT2i, and by electronic nose (e-nose)
measurements using FreshSense instrument. Storage time of herring
in ice could be estimated by QIM with ± 2 days using 5 herring per
lot. No correlation between instrumental texture parameters and
storage time or between sensory and instrumental texture variables
was found. E-nose measurements could be use to detect the onset of
spoilage.
Abstract: The aim of the study was to evaluate the effect of
texturizers on the rheological properties of the apple mass and
desserts made from various raw materials. The apple varieties -
‘Antonovka’, ‘Baltais Dzidrais’, and ‘Zarja Alatau’ harvested in
Latvia, were used for the experiment. The apples were processed in a
blender unpeeled for obtaining a homogenous mass. The apple mass
was analyzed fresh and after storage at –18ºC. Both fresh and thawed
apple mass samples with added gelatin, xantan gum, and sodium
carboxymethylcellulose were whisked obtaining dessert. Pectin, pH
and soluble dry matter of the product were determined. Apparent
viscosity was measured using a rotational viscometer DV–III Ultra.
Pectin content in frozen apple mass decreased significantly (p
Abstract: Vacuum membrane distillation (VMD) process can be
used for water purification or the desalination of salt water. The
process simply consists of a flat sheet hydrophobic micro porous
PTFE membrane and diaphragm vacuum pump without a condenser
for the water recovery or trap. The feed was used aqueous NaCl
solution. The VMD experiments were performed to evaluate the heat
and mass transfer coefficient of the boundary layer in a membrane
module. The only operating parameters are feed inlet temperature,
and feed flow rate were investigated. The permeate flux was strongly
affected by the feed inlet temperature, feed flow rate, and boundary
layer heat transfer coefficient. Since lowering the temperature
polarization coefficient is essential enhance the process performance
considerable and maximizing the heat transfer coefficient for
maximizes the mass flux of distillate water. In this paper, the results
of VMD experiments are used to measure the boundary layer heat
transfer coefficient, and the experimental results are used to reevaluate
the empirical constants in the Dittus- Boelter equation.
Abstract: The value of overall oxygen transfer Coefficient
(KLa), which is the best measure of oxygen transfer in water through
aeration, is obtained by a simple approach, which sufficiently
explains the utility of the method to eliminate the discrepancies due
to inaccurate assumption of saturation dissolved oxygen
concentration. The rate of oxygen transfer depends on number of
factors like intensity of turbulence, which in turns depends on the
speed of rotation, size, and number of blades, diameter and
immersion depth of the rotor, and size and shape of aeration tank, as
well as on physical, chemical, and biological characteristic of water.
An attempt is made in this paper to correlate the overall oxygen
transfer Coefficient (KLa), as an independent parameter with other
influencing parameters mentioned above. It has been estimated that
the simulation equation developed predicts the values of KLa and
power with an average standard error of estimation of 0.0164 and
7.66 respectively and with R2 values of 0.979 and 0.989 respectively,
when compared with experimentally determined values. The
comparison of this model is done with the model generated using
Computational fluid dynamics (CFD) and both the models were
found to be in good agreement with each other.
Abstract: For most image fusion algorithms separate
relationship by pixels in the image and treat them more or less
independently. In addition, they have to be adjusted different
parameters in different time or weather. In this paper, we propose a
region–based image fusion which combines aspects of feature and
pixel-level fusion method to replace only by pixel. The basic idea is
to segment far infrared image only and to add information of each
region from segmented image to visual image respectively. Then we
determine different fused parameters according different region. At
last, we adopt artificial neural network to deal with the problems of
different time or weather, because the relationship between fused
parameters and image features are nonlinear. It render the fused
parameters can be produce automatically according different states.
The experimental results present the method we proposed indeed
have good adaptive capacity with automatic determined fused
parameters. And the architecture can be used for lots of applications.
Abstract: The Beshar River is one aquatic ecosystem, which is
located next to the city of Yasuj in southern Iran. The Beshar river
has been contaminated by industrial factories such as effluent of
sugar factory, agricultural and other activities in this region such as,
Imam Sajjad hospital, drainage from agricultural farms, Yasuj urban
surface runoff and effluent of wastewater treatment plants ,specially
Yasuj waste water treatment plant. In order to evaluate the effects of
these pollutants on the quality of the Beshar river, five monitoring
stations were selected along its course. The first station is located
upstream of Yasuj near the Dehnow village; stations 2 to 4 are
located east, south and west of city; and the 5th station is located
downstream of Yasuj. Several water quality parameters were
sampled. These include pH, dissolved oxygen, biological oxygen
demand (BOD), temperature, conductivity, turbidity, total dissolved
solids and discharge or flow measurements. Water samples from the
five stations were collected and analyzed to determine the following
physicochemical parameters: EC, pH, T.D.S, T.H, No2, DO, BOD5,
COD during 2008 to 2010. The study shows that the BOD5 value of
station 1 is at a minimum (1.7 ppm) and increases downstream from
stations 2 to 4 to a maximum (11.6 ppm), and then decreases at
station 5. The DO values of station 1 is a maximum (8.45 ppm),
decreases downstream to stations 2 - 4 which are at a minimum (3.1
ppm), before increasing at station 5. The amount of BOD and TDS
are highest at the 4th station and the amount of DO is lowest at this
station, marking the 4th station as more highly polluted than the
other stations .This study shows average amount of the water quality
parameters in first year of sampling (2008) have had a better quality
relation to third year in 2010 because of recent drought in this region
and pollutant increasing .As the Beshar river path after 5th station
goes through the mountain area with more slope and flow velocity
,so the physicochemical parameters improve at the 5th station due to
pollutant degradation and dilution. Finally the point and nonpoint
pollutant sources of Beshar river were determined and compared to
the monitoring results.
Abstract: We analyze hand dexterity in Parkinson-s disease patients (PD) and control subjects using a natural manual transport task (moving an object from one place to another). Eight PD patients and ten control subjects performed the task repeatedly at maximum speed both in OFF and ON medicated status. The movement parameters and the grip and load forces were recorded by a single optoelectronic camera and force transducers built in the especially designed object. Using the force and velocity signals, ten subsequent phases of the transport movement were defined and their durations were measured. The outline of 3D optical measurement is presented to obtain more precise movement trajectory.
Abstract: Throughput is an important measure of performance of production system. Analyzing and modeling of production throughput is complex in today-s dynamic production systems due to uncertainties of production system. The main reasons are that uncertainties are materialized when the production line faces changes in setup time, machinery break down, lead time of manufacturing, and scraps. Besides, demand changes are fluctuating from time to time for each product type. These uncertainties affect the production performance. This paper proposes Bayesian inference for throughput modeling under five production uncertainties. Bayesian model utilized prior distributions related to previous information about the uncertainties where likelihood distributions are associated to the observed data. Gibbs sampling algorithm as the robust procedure of Monte Carlo Markov chain was employed for sampling unknown parameters and estimating the posterior mean of uncertainties. The Bayesian model was validated with respect to convergence and efficiency of its outputs. The results presented that the proposed Bayesian models were capable to predict the production throughput with accuracy of 98.3%.
Abstract: The charge-exchange xenon (CEX) ion generated by ion thruster can backflow to the surface of spacecraft and threaten to the safety of spacecraft operation. In order to evaluate the effects of the induced plasma environment in backflow regions on the spacecraft, we designed a spherical single Langmuir probe of 5.8cm in diameter for measuring low-density plasma parameters in backflow region of ion thruster. In practice, the tests are performed in a two-dimensional array (40cm×60cm) composed of 20 sites. The experiment results illustrate that the electron temperature ranges from 3.71eV to 3.96eV, with the mean value of 3.82eV and the standard deviation of 0.064eV. The electron density ranges from 8.30×1012/m3 to 1.66×1013/m3, with the mean value of 1.30×1013/m3 and the standard deviation of 2.15×1012/m3. All data is analyzed according to the “ideal" plasma conditions of Maxwellian distributions.
Abstract: This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.
Abstract: This paper proposes a new parameter identification
method based on Linear Fractional Transformation (LFT). It is
assumed that the target linear system includes unknown parameters.
The parameter deviations are separated from a nominal system via
LFT, and identified by organizing I/O signals around the separated
deviations of the real system. The purpose of this paper is to apply LFT
to simultaneously identify the parameter deviations in systems with
fewer outputs than unknown parameters. As a fundamental example,
this method is implemented to one degree of freedom vibratory system.
Via LFT, all physical parameters were simultaneously identified in this
system. Then, numerical simulations were conducted for this system to
verify the results. This study shows that all the physical parameters of a
system with fewer outputs than unknown parameters can be effectively
identified simultaneously using LFT.
Abstract: Timetabling problems are often hard and timeconsuming
to solve. Most of the methods of solving them concern
only one problem instance or class. This paper describes a universal
method for solving large, highly constrained timetabling problems
from different domains. The solution is based on evolutionary
algorithm-s framework and operates on two levels – first-level
evolutionary algorithm tries to find a solution basing on given set of
operating parameters, second-level algorithm is used to establish
those parameters. Tabu search is employed to speed up the solution
finding process on first level. The method has been used to solve
three different timetabling problems with promising results.
Abstract: This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.
Abstract: Hepatitis C is an infectious disease transmitted by
blood and due to hepatitis C virus (HCV), which attacks the liver.
The infection is characterized by liver inflammation (hepatitis) that is
often asymptomatic but can progress to chronic hepatitis and later
cirrhosis and liver cancer. Our problem tends to highlight on the one
hand the prevalence of infectious disease in the population of the
region of Batna and on other hand the biological characteristics of
this disease by a screening and a specific diagnosis based on
serological tests, liver checkup (measurement of haematological and
biochemical parameters).
The results showed:
The serology of hepatitis C establishes the diagnosis of infection
with hepatitis C. In this study and with the serological test, 24 cases
of the disease of hepatitis C were found in 1000 suspected cases (7
cases with normal transaminases and 17 cases with elevated
transaminases). The prevalence of this disease in this study
population was 2.4%.
The presence of hepatitis C disrupts liver function including the
onset of cytolysis, cholestasis, jaundice, thrombocytopenia, and
coagulation disorders.
Abstract: This paper deals with the tuning of parameters for Automatic Generation Control (AGC). A two area interconnected hydrothermal system with PI controller is considered. Genetic Algorithm (GA) and Particle Swarm optimization (PSO) algorithms have been applied to optimize the controller parameters. Two objective functions namely Integral Square Error (ISE) and Integral of Time-multiplied Absolute value of the Error (ITAE) are considered for optimization. The effectiveness of an objective function is considered based on the variation in tie line power and change in frequency in both the areas. MATLAB/SIMULINK was used as a simulation tool. Simulation results reveal that ITAE is a better objective function than ISE. Performances of optimization algorithms are also compared and it was found that genetic algorithm gives better results than particle swarm optimization algorithm for the problems of AGC.
Abstract: In this article a modification of the algorithm of the fuzzy ART network, aiming at returning it supervised is carried out. It consists of the search for the comparison, training and vigilance parameters giving the minimum quadratic distances between the output of the training base and those obtained by the network. The same process is applied for the determination of the parameters of the fuzzy ARTMAP giving the most powerful network. The modification consist in making learn the fuzzy ARTMAP a base of examples not only once as it is of use, but as many time as its architecture is in evolution or than the objective error is not reached . In this way, we don-t worry about the values to impose on the eight (08) parameters of the network. To evaluate each one of these three networks modified, a comparison of their performances is carried out. As application we carried out a classification of the image of Algiers-s bay taken by SPOT XS. We use as criterion of evaluation the training duration, the mean square error (MSE) in step control and the rate of good classification per class. The results of this study presented as curves, tables and images show that modified fuzzy ARTMAP presents the best compromise quality/computing time.
Abstract: This paper concerns about the experimental and
numerical investigations of energy absorption and axial tearing
behaviour of aluminium 6060 circular thin walled tubes under static
axial compression. The tubes are received in T66 heat treatment
condition with fixed outer diameter of 42mm, thickness of 1.5mm
and length of 120mm. The primary variables are the conical die
angles (15°, 20° and 25°). Numerical simulations are carried on
ANSYS/LS-DYNA software tool, for investigating the effect of
friction between the tube and the die.
Abstract: A dent is a gross distortion of the pipe cross-section.
Dent depth is defined as the maximum reduction in the diameter of
the pipe compared to the original diameter. Pipeline dent finite
element (FE) simulation and theoretical analysis are conducted in this
paper to develop an understanding of the geometric characteristics
and strain distribution in the pressurized dented pipe. Based on the
results, the magnitude of the denting force increases significantly
with increasing the internal pressure, and the maximum
circumferential and longitudinal strains increase by increasing the
internal pressure and the dent depth. The results can be used for
characterizing dents and ranking their risks to the integrity of a
pipeline.
Abstract: The resistive-inductive-capacitive behavior of long
interconnects which are driven by CMOS gates are presented in this
paper. The analysis is based on the ¤Ç-model of a RLC load and is
developed for submicron devices. Accurate and analytical
expressions for the output load voltage, the propagation delay and the
short circuit power dissipation have been proposed after solving a
system of differential equations which accurately describe the
behavior of the circuit. The effect of coupling capacitance between
input and output and the short circuit current on these performance
parameters are also incorporated in the proposed model. The
estimated proposed delay and short circuit power dissipation are in
very good agreement with the SPICE simulation with average
relative error less than 6%.
Abstract: Prediction of viscosity of natural gas is an important parameter in the energy industries such as natural gas storage and transportation. In this study viscosity of different compositions of natural gas is modeled by using an artificial neural network (ANN) based on back-propagation method. A reliable database including more than 3841 experimental data of viscosity for testing and training of ANN is used. The designed neural network can predict the natural gas viscosity using pseudo-reduced pressure and pseudo-reduced temperature with AARD% of 0.221. The accuracy of designed ANN has been compared to other published empirical models. The comparison indicates that the proposed method can provide accurate results.