Abstract: Oxyleotris marmorata is considered as
undomesticated fish, and its culture occasionally faces a problem of
food deprivation. The present study aims to evaluate alteration of
hematological indices, blood chemical associated with liver function
during 4 weeks of fasting. A non-linear relationships between fasting
days and hematological parameters (red blood cell number; y = -
0.002x2 + 0.041x + 1.249; R2=0.915, P0.05), mean corpuscular
volume; y = -0.180x2 + 2.183x + 149.61; R2=0.732, P>0.05, mean
corpuscular hemoglobin; y = -0.041x2 + 0.862x + 29.864; R2=0.818,
P>0.05 and mean corpuscular hemoglobin concentration; y = -
0.044x2 + 0.711x + 21.580; R2=0.730, P>0.05) were demonstrated.
Significant change in hematocrit (Ht) during fasting period was
observed. Ht elevated sharply increase at the first weeks of fasting
period. Higher Ht also was detected during week 2-4 of fasting time.
The significant reduction of hepatosomatic index was observed (y = -
0.007x2 - 0.096x + 1.414; R2=0.968, P0.05, serum glutamic oxaloacetic transaminase;
y = 0.005x2 – 0.201x2 + 1.297x + 33.256; R2=1, P0.05). Taken together, prolonged fasting has
deleterious effects on hematological indices, liver mass and enzyme
associated in liver function. The marked adverse effects occurred
after the first week of fasting state.
Abstract: This paper presents the study of hardness profile of spur gear heated by induction heating process in function of the machine parameters, such as the power (kW), the heating time (s) and the generator frequency (kHz). The global work is realized by 3D finite-element simulation applied to the process by coupling and resolving the electromagnetic field and the heat transfer problems, and it was performed in three distinguished steps. First, a Comsol 3D model was built using an adequate formulation and taking into account the material properties and the machine parameters. Second, the convergence study was conducted to optimize the mesh. Then, the surface temperatures and the case depths were deeply analyzed in function of the initial current density and the heating time in medium frequency (MF) and high frequency (HF) heating modes and the edge effect were studied. Finally, the simulations results are validated using experimental tests.
Abstract: One of the processes of slope that occurs every year in Iran and some parts of world and cause a lot of criminal and financial harms is called landslide. They are plenty of method to stability landslide in soil and rock slides. The use of the best method with the least cost and in the shortest time is important for researchers. In this research, determining the best method of stability is investigated by using of Decision Support systems. DSS is made for this purpose and was used (for Hasan Salaran area in Kurdistan). Field study data from topography, slope, geology, geometry of landslide and the related features was used. The related data entered decision making managements programs (DSS) (ALES).Analysis of mass stability indicated the instability potential at present. Research results show that surface and sub surface drainage the best method of stabilizing. Analysis of stability shows that acceptable increase in security coefficient is a consequence of drainage.
Abstract: The soil moisture content is an important property of
the soil. The results of mean weekly gravimetric soil moisture
content, measured for the three soil layers within the A horizon,
showed that it was higher for the top 5 cm over the whole period of
monitoring (15/7/2004 up to 10/11/05) with the variation becoming
greater during winter time. This reflects the pattern of rainfall in
Ireland which is spread over the whole year and shows that light
rainfall events during summer time were compensated by loss
through evapotranspiration, but only in the top 5 cm of soil. This
layer had the highest porosity and highest moisture holding capacity
due to the high content of organic matter. The gravimetric soil
moisture contents of the top 5 cm and the underlying 5-15 and 15-25
cm layers show that bottom site of the Hill Field had higher soil
moisture content than the middle and top sites during the whole
period of monitoring.
Abstract: The objective of this paper is to study the electrical
resistivity complexity between field and laboratory measurement, in
order to improve the effectiveness of data interpretation for
geophysical ground resistivity survey. The geological outcrop in
Penang, Malaysia with an obvious layering contact was chosen as the
study site. Two dimensional geoelectrical resistivity imaging were
used in this study to maps the resistivity distribution of subsurface,
whereas few subsurface sample were obtained for laboratory
advance. In this study, resistivity of samples in original conditions is
measured in laboratory by using time domain low-voltage technique,
particularly for granite core sample and soil resistivity measuring set
for soil sample. The experimentation results from both schemes are
studied, analyzed, calibrated and verified, including basis and
correlation, degree of tolerance and characteristics of substance.
Consequently, the significant different between both schemes is
explained comprehensively within this paper.
Abstract: In this paper, transversal vibration of buried pipelines
during loading induced by underground explosions is analyzed. The
pipeline is modeled as an infinite beam on an elastic foundation, so
that soil-structure interaction is considered by means of transverse
linear springs along the pipeline. The pipeline behavior is assumed to
be ideal elasto-plastic which an ultimate strain value limits the plastic
behavior. The blast loading is considered as a point load, considering
the affected length at some point of the pipeline, in which the
magnitude decreases exponentially with time. A closed-form solution
for the quasi-static problem is carried out for both elastic and elasticperfect
plastic behaviors of pipe materials. At the end, a comparative
study on steel and polyethylene pipes with different sizes buried in
various soil conditions, affected by a predefined underground
explosion is conducted, in which effect of each parameter is
discussed.
Abstract: The aluminum bronze matrix alumina composites using hot press and resin infiltration were investigated to study their porosities, hardness, bending strengths, and microstructures. The experiment results show that the hardness of the sintered composites with the decrease of porosity increases. The composites without and with resin infiltration have about HRF 42-61 of about 34-40% of porosity and about HRF 62-83 of about 30-36% of porosity, respectively. Besides, the alumina composites contain a more amount of iron and nickel powders would cause a lower bending strength due to forming some weaker bonding among the iron, nickel, copper, aluminum under this hot pressing of shorter time.
Abstract: Blood pulse is an important human physiological signal commonly used for the understanding of the individual physical health. Current methods of non-invasive blood pulse sensing require direct contact or access to the human skin. As such, the performances of these devices tend to vary with time and are subjective to human body fluids (e.g. blood, perspiration and skin-oil) and environmental contaminants (e.g. mud, water, etc). This paper proposes a simulation model for the novel method of non-invasive acquisition of blood pulse using the disturbance created by blood flowing through a localized magnetic field. The simulation model geometry represents a blood vessel, a permanent magnet, a magnetic sensor, surrounding tissues and air in 2-dimensional. In this model, the velocity and pressure fields in the blood stream are described based on Navier-Stroke equations and the walls of the blood vessel are assumed to have no-slip condition. The blood assumes a parabolic profile considering a laminar flow for blood in major artery near the skin. And the inlet velocity follows a sinusoidal equation. This will allow the computational software to compute the interactions between the magnetic vector potential generated by the permanent magnet and the magnetic nanoparticles in the blood. These interactions are simulated based on Maxwell equations at the location where the magnetic sensor is placed. The simulated magnetic field at the sensor location is found to assume similar sinusoidal waveform characteristics as the inlet velocity of the blood. The amplitude of the simulated waveforms at the sensor location are compared with physical measurements on human subjects and found to be highly correlated.
Abstract: The objective of this paper is to estimate realistic
principal extrusion process parameters by means of artificial neural
network. Conventionally, finite element analysis is used to derive
process parameters. However, the finite element analysis of the
extrusion model does not consider the manufacturing process
constraints in its modeling. Therefore, the process parameters
obtained through such an analysis remains highly theoretical.
Alternatively, process development in industrial extrusion is to a
great extent based on trial and error and often involves full-size
experiments, which are both expensive and time-consuming. The
artificial neural network-based estimation of the extrusion process
parameters prior to plant execution helps to make the actual extrusion
operation more efficient because more realistic parameters may be
obtained. And so, it bridges the gap between simulation and real
manufacturing execution system. In this work, a suitable neural
network is designed which is trained using an appropriate learning
algorithm. The network so trained is used to predict the
manufacturing process parameters.
Abstract: This paper reports a case study on how a conceptual
and analytical thinking approach was used in Art and Design Department at Multimedia University (Malaysia) in addressing the
issues of one nation and its impact in the society through artworks. The art project was designed for students to increase the know-how
and develop creative thinking in design and communication. Goals of the design project were: (1) to develop creative thinking in design
and communication, (2) to increase student understanding on the
process of problem solving for design work, and (3) to use design
elements and principles to generate interest, attention and emotional responses. An exhibition entitled "One Nation" was showcased to
local and international viewers consisting of the general public, professionals, academics, artists and students. Findings indicate that the project supported several visual art standards, as well as
generated awareness in the society. This project may be of interest to
current and future art educators and others interested in the potential
of utilizing global issues as content for art, community and environment studies for the purpose of educational art.
Abstract: This paper introduces a temporal epistemic logic
CBCTL that updates agent-s belief states through communications
in them, based on computational tree logic (CTL). In practical
environments, communication channels between agents may not be
secure, and in bad cases agents might suffer blackouts. In this study,
we provide inform* protocol based on ACL of FIPA, and declare the
presence of secure channels between two agents, dependent on time.
Thus, the belief state of each agent is updated along with the progress
of time. We show a prover, that is a reasoning system for a given
formula in a given a situation of an agent ; if it is directly provable
or if it could be validated through the chains of communications, the
system returns the proof.
Abstract: The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations.
As a results of this, Computational Fluid Dynamic (CFD) solvers are
widely used in the aeronautical field. These solvers require the correct
selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on
the proper choice of these parameters.
In this paper we create an expert system capable of making an
accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver.
Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time
required for the convergence of a CFD solver.
Abstract: Software estimation accuracy is among the greatest
challenges for software developers. This study aimed at building and
evaluating a neuro-fuzzy model to estimate software projects
development time. The forty-one modules developed from ten
programs were used as dataset. Our proposed approach is compared
with fuzzy logic and neural network model and Results show that the
value of MMRE (Mean of Magnitude of Relative Error) applying
neuro-fuzzy was substantially lower than MMRE applying fuzzy
logic and neural network.
Abstract: Conventionally the selection of parameters depends
intensely on the operator-s experience or conservative technological
data provided by the EDM equipment manufacturers that assign
inconsistent machining performance. The parameter settings given by
the manufacturers are only relevant with common steel grades. A
single parameter change influences the process in a complex way.
Hence, the present research proposes artificial neural network (ANN)
models for the prediction of surface roughness on first commenced
Ti-15-3 alloy in electrical discharge machining (EDM) process. The
proposed models use peak current, pulse on time, pulse off time and
servo voltage as input parameters. Multilayer perceptron (MLP) with
three hidden layer feedforward networks are applied. An assessment
is carried out with the models of distinct hidden layer. Training of the
models is performed with data from an extensive series of
experiments utilizing copper electrode as positive polarity. The
predictions based on the above developed models have been verified
with another set of experiments and are found to be in good
agreement with the experimental results. Beside this they can be
exercised as precious tools for the process planning for EDM.
Abstract: In this paper we compare the response of linear and
nonlinear neural network-based prediction schemes in prediction of
received Signal-to-Interference Power Ratio (SIR) in Direct
Sequence Code Division Multiple Access (DS/CDMA) systems. The
nonlinear predictor is Multilayer Perceptron MLP and the linear
predictor is an Adaptive Linear (Adaline) predictor. We solve the
problem of complexity by using the Minimum Mean Squared Error
(MMSE) principle to select the optimal predictors. The optimized
Adaline predictor is compared to optimized MLP by employing
noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an
urban environment. The results show that the Adaline predictor can
estimates SIR with the same error as MLP when the user has the
velocity of 5 km/h and 60 km/h but by increasing the velocity up-to
120 km/h the mean squared error of MLP is two times more than
Adaline predictor. This makes the Adaline predictor (with lower
complexity) more suitable than MLP for closed-loop power control
where efficient and accurate identification of the time-varying
inverse dynamics of the multi path fading channel is required.
Abstract: Supplier selection is a multi criteria decision-making process that comprises tangible and intangible factors. The majority of previous supplier selection techniques do not consider strategic perspective. Besides, uncertainty is one of the most important obstacles in supplier selection. For the first, time in this paper, the idea of the algorithm " Knapsack " is used to select suppliers Moreover, an attempt has to be made to take the advantage of a simple numerical method for solving model .This is an innovation to resolve any ambiguity in choosing suppliers. This model has been tried in the suppliers selected in a competitive environment and according to all desired standards of quality and quantity to show the efficiency of the model, an industry sample has been uses.
Abstract: Through the time, the higher education has changed
the learning system since mother tongue to bilingual, and in this new
century has been coming develop a multilingual education. All as
part of globalization process of the countries and the education.
Nevertheless, this change only has been effectively in countries of the
first world, the rest have been lagging. Therefore, these countries
require strengthen their higher education systems through models that
give way to multilingual and bilingual education. In this way, shows
a new model adapted from a systemic form to allow a higher
bilingual and multilingual education in Latin America. This
systematization aims to increase the skills and competencies
student’s, decrease the time learning of a second tongue, add to
multilingualism in the American Latin Universities, also, contribute
to position the region´s countries in a better global status, and
stimulate the development of new research in this area.
Abstract: Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.
Abstract: The inherent iterative nature of product design and development poses significant challenge to reduce the product design and development time (PD). In order to shorten the time to market, organizations have adopted concurrent development where multiple specialized tasks and design activities are carried out in parallel. Iterative nature of work coupled with the overlap of activities can result in unpredictable time to completion and significant rework. Many of the products have missed the time to market window due to unanticipated or rather unplanned iteration and rework. The iterative and often overlapped processes introduce greater amounts of ambiguity in design and development, where the traditional methods and tools of project management provide less value. In this context, identifying critical metrics to understand the iteration probability is an open research area where significant contribution can be made given that iteration has been the key driver of cost and schedule risk in PD projects. Two important questions that the proposed study attempts to address are: Can we predict and identify the number of iterations in a product development flow? Can we provide managerial insights for a better control over iteration? The proposal introduces the concept of decision points and using this concept intends to develop metrics that can provide managerial insights into iteration predictability. By characterizing the product development flow as a network of decision points, the proposed research intends to delve further into iteration probability and attempts to provide more clarity.
Abstract: research goal was to determine the expression levels cDNA of brain embrio at gestation days 10 (GD-10). The Electroforesis DNA results showed that GAPDH, Fibronectin1, Ncam1, Tenascin, Vimentin, Neurofilament heavy, Neurofilament medium and Neurofilament low were 447 bp, 462 bp, 293 bp. 416 bp, 327 bp, 301 bp, 398 bp and 289 bp. Result of real-time RT-PCR on brain Embryo at gestation days 10 showed that the expression of copy gen Fibronectin 36 copies, Ncam 21,708 copies; Tenascin 24,505 copies; Vimentin 538,554 copies; Neurofilament heavy 2,419 copies; Neurofilament medium 92,928 copies; Neurofilament low 125,809 copies. Vimentin expressed gene copies is very high compared with other gene copies. This condition are caused by Vimentin, that contribute to proliferate of brain development. The vimentin role to cell proliferation of brain.