Abstract: Ultrasound is useful in demonstrating bone mineral
density of regenerating osseous tissue as well as structural alterations.
A proposed ultrasound method, which included ultrasonography and
acoustic parameters measurement, was employed to evaluate its
efficacy in monitoring the bone callus changes in a rabbit tibial
distraction osteogenesis (DO) model.
The findings demonstrated that ultrasonographic images depicted
characteristic changes of the bone callus, typical of histology findings,
during the distraction phase. Follow-up acoustic parameters
measurement of the bone callus, including speed of sound, reflection
and attenuation, showed significant linear changes over time during
the distraction phase. The acoustic parameters obtained during the
distraction phase also showed moderate to strong correlation with
consolidated bone callus density and micro-architecture measured by
micro-computed tomography at the end of the consolidation phase.
The results support the preferred use of ultrasound imaging in the
early monitoring of bone callus changes during DO treatment.
Abstract: Command and Control (C2) system and its interfacethe
Common Operational Picture (COP) are main means that
supports commander in its decision making process. COP contains
information about friendly and enemy unit positions. The friendly
position is gathered via tactical network. In the case of tactical
network failure the information about units are not available. The
tactical simulator can be used as a tool that is capable to predict
movements of units in respect of terrain features. Article deals with
an experiment that was based on Czech C2 system that is in the case
of connectivity lost fed by VR Forces simulator. Article analyzes
maximum time interval in which the position created by simulator is
still usable and truthful for commander in real time.
Abstract: To simulate expected climate change, we implemented a two-factor (temperature and soil moisture) field design in a forest in Ontario, Canada. To manipulate moisture input, we erected rain-exclusion structures. Under each structure, plots were watered with one of three treatments and thermally controlled with three heat treatments to simulate changes in air temperature and rainfall based on the climate model (GCM) predictions for the study area. Environmental conditions (including untreated controls) were monitored tracking air temperature, soil temperature, soil moisture, and photosynthetically active radiation. We measured rainfall and relative humidity at the site outside the rain-exclusion structures. Analyses of environmental conditions demonstrates that the temperature manipulation was most effective at maintaining target temperature during the early part of the growing season, but it was more difficult to keep the warmest treatment at 5º C above ambient by late summer. Target moisture regimes were generally achieved however incoming solar radiation was slightly attenuated by the structures.
Abstract: Response surface methodology was used for
quantitative investigation of water and solids transfer during osmotic
dehydration of beetroot in aqueous solution of salt. Effects of
temperature (25 – 45oC), processing time (30–150 min), salt
concentration (5–25%, w/w) and solution to sample ratio (5:1 – 25:1)
on osmotic dehydration of beetroot were estimated. Quadratic
regression equations describing the effects of these factors on the
water loss and solids gain were developed. It was found that effects
of temperature and salt concentrations were more significant on the
water loss than the effects of processing time and solution to sample
ratio. As for solids gain processing time and salt concentration were
the most significant factors. The osmotic dehydration process was
optimized for water loss, solute gain, and weight reduction. The
optimum conditions were found to be: temperature – 35oC,
processing time – 90 min, salt concentration – 14.31% and solution
to sample ratio 8.5:1. At these optimum values, water loss, solid gain
and weight reduction were found to be 30.86 (g/100 g initial sample),
9.43 (g/100 g initial sample) and 21.43 (g/100 g initial sample)
respectively.
Abstract: For many chemical and biological processes, the understanding of the mixing phenomenon and flow behavior in a stirred tank is of major importance. A three-dimensional numerical study was performed using the software Fluent, to study the flow field in a stirred tank with a Rushton turbine. In this work, we first studied the flow generated in the tank with a Rushton turbine. Then, we studied the effect of the variation of turbine’s submergence on the thermodynamic quantities defining the flow field. For that, four submergences were considered, while maintaining the same rotational speed (N =250rpm). This work intends to optimize the aeration performances of a Rushton turbine in a stirred tank.
Abstract: The exhaustive quality control is becoming more and
more important when commercializing competitive products in the
world's globalized market. Taken this affirmation as an undeniable
truth, it becomes critical in certain sector markets that need to offer
the highest restrictions in quality terms. One of these examples is the
percussion cap mass production, a critical element assembled in
firearm ammunition. These elements, built in great quantities at a
very high speed, must achieve a minimum tolerance deviation in
their fabrication, due to their vital importance in firing the piece of
ammunition where they are built in. This paper outlines a machine
vision development for the 100% inspection of percussion caps
obtaining data from 2D and 3D simultaneous images. The acquisition
speed and precision of these images from a metallic reflective piece
as a percussion cap, the accuracy of the measures taken from these
images and the multiple fabrication errors detected make the main
findings of this work.
Abstract: Three dimensional simulations in tube in tube heat
exchangers are investigated numerically in this study. In these
simulations forced convective heat transfer and laminar flow of
single-phase water are considered. In order to measure heat transfer
parameters in these heat exchangers, FLUENT CFD Solver is used in
this numerical method. For the purpose of creating geometry and
exert boundary and initial conditions in the present model, finite
volume method in Computational Fluid Dynamics is used in this
study. In the present study, at each Z-location, variation of local
temperatures, heat flux and Nusselt number at the whole tube is
investigated in detail. Thereafter, averaged computational Nusselt
number in this model is calculated. In addition, conceivable pressure
drops have been obtained at each Z-location in this model. Then,
pressure drop values in the present model are explored. Finally, all
the numerical results for this kind of heat exchanger will be discussed
precisely.
Abstract: This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on backgrounddifferenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of nonuniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.
Abstract: Wavelets have provided the researchers with
significant positive results, by entering the texture defect detection domain. The weak point of wavelets is that they are one-dimensional
by nature so they are not efficient enough to describe and analyze two-dimensional functions. In this paper we present a new method to
detect the defect of texture images by using curvelet transform.
Simulation results of the proposed method on a set of standard
texture images confirm its correctness. Comparing the obtained results indicates the ability of curvelet transform in describing
discontinuity in two-dimensional functions compared to wavelet
transform
Abstract: The urban centers within northeastern Brazil are
mainly influenced by the intense rainfalls, which can occur after long
periods of drought, when flood events can be observed during such
events. Thus, this paper aims to study the rainfall frequencies in such
region through the wavelet transform. An application of wavelet
analysis is done with long time series of the total monthly rainfall
amount at the capital cities of northeastern Brazil. The main
frequency components in the time series are studied by the global
wavelet spectrum and the modulation in separated periodicity bands
were done in order to extract additional information, e.g., the 8 and
16 months band was examined by an average of all scales, giving a
measure of the average annual variance versus time, where the
periods with low or high variance could be identified. The important
increases were identified in the average variance for some periods,
e.g. 1947 to 1952 at Teresina city, which can be considered as high
wet periods. Although, the precipitation in those sites showed similar
global wavelet spectra, the wavelet spectra revealed particular
features. This study can be considered an important tool for time
series analysis, which can help the studies concerning flood control,
mainly when they are applied together with rainfall-runoff
simulations.
Abstract: The purpose of this study is to investigate the influence of breaststroke swimming exercise to improving the peak expiratory flow. Methode: This study used 17 students of men aged 19-21 years, APE values measured before and after the study. Style swimming workout done in accordance with a program that has been made. Result: Value of peak expiratory flow in male students obtained on average before exercise (530 ± 15 811) liters / min and after doing the exercises (540.59 ± 17 092) liters / minute. Paired ttest showed t = -6.446 and p = 0.000, which means there are differences in peak expiratory flow values before and after exercise swimming breaststroke. Conclusion: The conclusion is the breaststroke swimming exercise can be improving of peak expiratory flow.
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: Transliteration is frequently used especially in writing geographic denominations, personal names (onyms) etc. Proper names (onyms) of all languages must sound similarly in translated works as well as in scientific projects and works written in mother tongue, because we can get introduced with the nation, its history, culture, traditions and other spiritual values through the onyms of that nation. Therefore it is necessary to systematize the different transliterations of onyms of foreign languages. This paper is dedicated to the problem of making the project of transliterating Kazakh onyms into Arabic. In order to achieve this goal we use scientific or practical types of transliteration. Because in this type of transliteration provides easy reading writing source language's texts in the target language without any diacritical symbols, it is limited by the target language's alphabetic system.
Abstract: Cutting fluids, usually in the form of a liquid, are
applied to the chip formation zone in order to improve the cutting
conditions. Cutting fluid can be expensive and represents a biological
and environmental hazard that requires proper recycling and
disposal, thus adding to the cost of the machining operation. For
these reasons dry cutting or dry machining has become an
increasingly important approach; in dry machining no coolant or
lubricant is used. This paper discussed the effect of the dry cutting on
cutting force and tool life when machining aerospace materials
(Haynes 242) with using two different coated carbide cutting tools
(TiAlN and TiN/MT-TiCN/TiN). Response surface method (RSM)
was used to minimize the number of experiments. ParTiAlN Swarm
Optimisation (PSO) models were developed to optimize the
machining parameters (cutting speed, federate and axial depth) and
obtain the optimum cutting force and tool life. It observed that
carbide cutting tool coated with TiAlN performed better in dry
cutting compared with TiN/MT-TiCN/TiN. On other hand, TiAlN
performed more superior with using of 100 % water soluble coolant.
Due to the high temperature produced by aerospace materials, the
cutting tool still required lubricant to sustain the heat transfer from
the workpiece.
Abstract: Movable power sources of proton exchange
membrane fuel cells (PEMFC) are the important research done in the
current fuel cells (FC) field. The PEMFC system control influences
the cell performance greatly and it is a control system for industrial
complex problems, due to the imprecision, uncertainty and partial
truth and intrinsic nonlinear characteristics of PEMFCs. In this paper
an adaptive PI control strategy using neural network adaptive Morlet
wavelet for control is proposed. It is based on a single layer feed
forward neural networks with hidden nodes of adaptive morlet
wavelet functions controller and an infinite impulse response (IIR)
recurrent structure. The IIR is combined by cascading to the network
to provide double local structure resulting in improving speed of
learning. The proposed method is applied to a typical 1 KW PEMFC
system and the results show the proposed method has more accuracy
against to MLP (Multi Layer Perceptron) method.
Abstract: RoboCup Rescue simulation as a large-scale Multi
agent system (MAS) is one of the challenging environments for
keeping coordination between agents to achieve the objectives
despite sensing and communication limitations. The dynamicity of
the environment and intensive dependency between actions of
different kinds of agents make the problem more complex. This point
encouraged us to use learning-based methods to adapt our decision
making to different situations. Our approach is utilizing
reinforcement leaning. Using learning in rescue simulation is one of
the current ways which has been the subject of several researches in
recent years. In this paper we present an innovative learning method
implemented for Police Force (PF) Agent. This method can cope
with the main difficulties that exist in other learning approaches.
Different methods used in the literature have been examined. Their
drawbacks and possible improvements have led us to the method
proposed in this paper which is fast and accurate. The Brain
Emotional Learning Based Intelligent Controller (BELBIC) is our
solution for learning in this environment. BELBIC is a
physiologically motivated approach based on a computational model
of amygdale and limbic system. The paper presents the results
obtained by the proposed approach, showing the power of BELBIC
as a decision making tool in complex and dynamic situation.
Abstract: One of the most basic functions of control engineers is
tuning of controllers. There are always several process loops in the
plant necessitate of tuning. The auto tuned Proportional Integral
Derivative (PID) Controllers are designed for applications where
large load changes are expected or the need for extreme accuracy and
fast response time exists. The algorithm presented in this paper is
used for the tuning PID controller to obtain its parameters with a
minimum computing complexity. It requires continuous analysis of
variation in few parameters, and let the program to do the plant test
and calculate the controller parameters to adjust and optimize the
variables for the best performance. The algorithm developed needs
less time as compared to a normal step response test for continuous
tuning of the PID through gain scheduling.
Abstract: The analysis is mainly concentrating on the knowledge
management literatures productivity trend which subjects as
“knowledge management" in SSCI database. The purpose what the
analysis will propose is to summarize the trend information for
knowledge management researchers since core knowledge will be
concentrated in core categories. The result indicated that the literature
productivity which topic as “knowledge management" is still
increasing extremely and will demonstrate the trend by different
categories including author, country/territory, institution name,
document type, language, publication year, and subject area. Focus on
the right categories, you will catch the core research information. This
implies that the phenomenon "success breeds success" is more
common in higher quality publications.
Abstract: LabVIEW and SIMULINK are two most widely used
graphical programming environments for designing digital signal
processing and control systems. Unlike conventional text-based
programming languages such as C, Cµ and MATLAB, graphical
programming involves block-based code developments, allowing a
more efficient mechanism to build and analyze control systems. In
this paper a LabVIEW environment has been employed as a
graphical user interface for monitoring the operation of a controlled
distillation column, by visualizing both the closed loop performance
and the user selected control conditions, while the column dynamics
has been modeled under the SIMULINK environment. This tool has
been applied to the PID based decoupled control of a binary
distillation column. By means of such integrated environments the
control designer is able to monitor and control the plant behavior and
optimize the response when both, the quality improvement of
distillation products and the operation efficiency tasks, are
considered.
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.