Abstract: Thermal conductivity is an important characteristic of
a nanofluid in laminar flow heat transfer. This paper presents an
improved model for the prediction of the effective thermal
conductivity of nanofluids based on dimensionless groups. The
model expresses the thermal conductivity of a nanofluid as a function
of the thermal conductivity of the solid and liquid, their volume
fractions and particle size. The proposed model includes a parameter
which accounts for the interfacial shell, brownian motion, and
aggregation of particle. The validation of the model is verified by
applying the results obtained by the experiments of Tio2-water and
Al2o3-water nanofluids.
Abstract: This paper describes about dynamic reconfiguration to
miniaturize arithmetic circuits in general-purpose processor. Dynamic
reconfiguration is a technique to realize required functions by
changing hardware construction during operation. The proposed
arithmetic circuit performs floating-point arithmetic which is
frequently used in science and technology. The data format is
floating-point based on IEEE754. The proposed circuit is designed
using VHDL, and verified the correct operation by simulations and
experiments.
Abstract: In this research, a systematic investigation was carried out to determine the optimum conditions of HDS reactor. Moreover, a suitable model was developed for a rigorous RTO (real time optimization) loop of HDS (Hydro desulfurization) process. A systematic experimental series was designed based on CCD (Central Composite design) and carried out in the related pilot plant to tune the develop model. The designed variables in the experiments were Temperature, LHSV and pressure. However, the hydrogen over fresh feed ratio was remained constant. The ranges of these variables were respectively equal to 320-380ºC, 1- 21/hr and 50-55 bar. a power law kinetic model was also developed for our further research in the future .The rate order and activation energy , power of reactant concentration and frequency factor of this model was respectively equal to 1.4, 92.66 kJ/mol and k0=2.7*109 .
Abstract: This paper presents a model for an unreliable
production line, which is operated according to demand with constant
work-in-process (CONWIP). A simulation model is developed based
on the discrete model and several case problems are analyzed using
the model. The model is utilized to optimize storage space capacities
at intermediate stages and the number of kanbans at the last stage,
which is used to trigger the production at the first stage. Furthermore,
effects of several line parameters on production rate are analyzed
using design of experiments.
Abstract: Topological changes in mobile ad hoc networks
frequently render routing paths unusable. Such recurrent path failures
have detrimental effects on quality of service. A suitable technique
for eliminating this problem is to use multiple backup paths between
the source and the destination in the network. This paper proposes an
effective and efficient protocol for backup and disjoint path set in ad
hoc wireless network. This protocol converges to a highly reliable
path set very fast with no message exchange overhead. The paths
selection according to this algorithm is beneficial for mobile ad hoc
networks, since it produce a set of backup paths with more high
reliability. Simulation experiments are conducted to evaluate the
performance of our algorithm in terms of route numbers in the path
set and its reliability. In order to acquire link reliability estimates, we
use link expiration time (LET) between two nodes.
Abstract: This paper summarizes the results of some experiments for finding the effective features for disambiguation of Turkish verbs. Word sense disambiguation is a current area of investigation in which verbs have the dominant role. Generally verbs have more senses than the other types of words in the average and detecting these features for verbs may lead to some improvements for other word types. In this paper we have considered only the syntactical features that can be obtained from the corpus and tested by using some famous machine learning algorithms.
Abstract: In order to avoid the potentially devastating
consequences of global warming and climate change, the carbon
dioxide “CO2" emissions caused due to anthropogenic activities must
be reduced considerably. This paper presents the first study
examining the feasibility of carbon sequestration in construction and
demolition “C&D" waste. Experiments were carried out in a self
fabricated Batch Reactor at 40ºC, relative humidity of 50-70%, and
flow rate of CO2 at 10L/min for 1 hour for water-to-solids ratio of 0.2
to 1.2. The effect of surface area was found by comparing the
theoretical extent of carbonation of two different sieve sizes (0.3mm
and 2.36mm) of C&D waste. A 38.44% of the theoretical extent of
carbonation equating to 4% CO2 sequestration extent was obtained
for C&D waste sample for 0.3mm sieve size. Qualitative,
quantitative and morphological analyses were done to validate
carbonate formation using X-ray diffraction “X.R.D.," thermal
gravimetric analysis “T.G.A., “X-Ray Fluorescence Spectroscopy
“X.R.F.," and scanning electron microscopy “S.E.M".
Abstract: In recent years, real estate prediction or valuation has
been a topic of discussion in many developed countries. Improper
hype created by investors leads to fluctuating prices of real estate,
affecting many consumers to purchase their own homes. Therefore,
scholars from various countries have conducted research in real estate
valuation and prediction. With the back-propagation neural network
that has been popular in recent years and the orthogonal array in the
Taguchi method, this study aimed to find the optimal parameter
combination at different levels of orthogonal array after the system
presented different parameter combinations, so that the artificial
neural network obtained the most accurate results. The experimental
results also demonstrated that the method presented in the study had a
better result than traditional machine learning. Finally, it also showed
that the model proposed in this study had the optimal predictive effect,
and could significantly reduce the cost of time in simulation operation.
The best predictive results could be found with a fewer number of
experiments more efficiently. Thus users could predict a real estate
transaction price that is not far from the current actual prices.
Abstract: Process planning and production scheduling play
important roles in manufacturing systems. In this paper a multiobjective
mixed integer linear programming model is presented for
the integrated planning and scheduling of multi-product. The aim is
to find a set of high-quality trade-off solutions. This is a
combinatorial optimization problem with substantially large solution
space, suggesting that it is highly difficult to find the best solutions
with the exact search method. To account for it, a PSO-based
algorithm is proposed by fully utilizing the capability of the
exploration search and fast convergence. To fit the continuous PSO
in the discrete modeled problem, a solution representation is used in
the algorithm. The numerical experiments have been performed to
demonstrate the effectiveness of the proposed algorithm.
Abstract: Electric impedance imaging is a method of
reconstructing spatial distribution of electrical conductivity inside a
subject. In this paper, a new method of electrical impedance imaging
using eddy current is proposed. The eddy current distribution in the
body depends on the conductivity distribution and the magnetic field
pattern. By changing the position of magnetic core, a set of voltage
differences is measured with a pair of electrodes. This set of voltage
differences is used in image reconstruction of conductivity
distribution. The least square error minimization method is used as a
reconstruction algorithm. The back projection algorithm is used to
get two dimensional images. Based on this principle, a measurement
system is developed and some model experiments were performed
with a saline filled phantom. The shape of each model in the
reconstructed image is similar to the corresponding model,
respectively. From the results of these experiments, it is confirmed
that the proposed method is applicable in the realization of electrical
imaging.
Abstract: In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.
Abstract: A combined three-microphone voice activity detector (VAD) and noise-canceling system is studied to enhance speech recognition in an automobile environment. A previous experiment clearly shows the ability of the composite system to cancel a single noise source outside of a defined zone. This paper investigates the performance of the composite system when there are frequently moving noise sources (noise sources are coming from different locations but are not always presented at the same time) e.g. there is other passenger speech or speech from a radio when a desired speech is presented. To work in a frequently moving noise sources environment, whilst a three-microphone voice activity detector (VAD) detects voice from a “VAD valid zone", the 3-microphone noise canceller uses a “noise canceller valid zone" defined in freespace around the users head. Therefore, a desired voice should be in the intersection of the noise canceller valid zone and VAD valid zone. Thus all noise is suppressed outside this intersection of area. Experiments are shown for a real environment e.g. all results were recorded in a car by omni-directional electret condenser microphones.
Abstract: For identifying the discriminative sequence features between exons and introns, a new paradigm, rescaled-range frameshift analysis (RRFA), was proposed. By RRFA, two new
sequence features, the frameshift sensitivity (FS) and the accumulative
penta-mer complexity (APC), were discovered which
were further integrated into a new feature of larger scale, the persistency in anti-mutation (PAM). The feature-validation experiments
were performed on six model organisms to test the power
of discrimination. All the experimental results highly support that FS, APC and PAM were all distinguishing features between exons
and introns. These identified new sequence features provide new insights into the sequence composition of genes and they have
great potentials of forming a new basis for recognizing the exonintron boundaries in gene sequences.
Abstract: In this paper we consider a nonlinear control design for
nonlinear systems by using two-stage formal linearization and twotype
LQ controls. The ordinary LQ control is designed on almost
linear region around the steady state point. On the other region,
another control is derived as follows. This derivation is based on
coordinate transformation twice with respect to linearization functions
which are defined by polynomials. The linearized systems can be
made up by using Taylor expansion considered up to the higher order.
To the resulting formal linear system, the LQ control theory is applied
to obtain another LQ control. Finally these two-type LQ controls
are smoothly united to form a single nonlinear control. Numerical
experiments indicate that this control show remarkable performances
for a nonlinear system.
Abstract: Monitored 3-Dimensional (3D) video experience can be utilized as “feedback information” to fine tune the service parameters for providing a better service to the demanding 3D service customers. The 3D video experience which includes both video quality and depth perception is influenced by several contextual and content related factors (e.g., ambient illumination condition, content characteristics, etc) due to the complex nature of the 3D video. Therefore, effective factors on this experience should be utilized while assessing it. In this paper, structural information of the depth map sequences of the 3D video is considered as content related factor effective on the depth perception assessment. Cartoon-like filter is utilized to abstract the significant depth levels in the depth map sequences to determine the structural information. Moreover, subjective experiments are conducted using 3D videos associated with cartoon-like depth map sequences to investigate the effectiveness of ambient illumination condition, which is a contextual factor, on depth perception. Using the knowledge gained through this study, 3D video experience metrics can be developed to deliver better service to the 3D video service users.
Abstract: Microarrays technique allows the simultaneous measurements of the expression levels of thousands of mRNAs. By mining this data one can identify the dynamics of the gene expression time series. By recourse of principal component analysis, we uncover the circadian rhythmic patterns underlying the gene expression profiles from Cyanobacterium Synechocystis. We applied PCA to reduce the dimensionality of the data set. Examination of the components also provides insight into the underlying factors measured in the experiments. Our results suggest that all rhythmic content of data can be reduced to three main components.
Abstract: In this research, the flow pattern influence on
performance of a micro PEMFC was investigated
experimentally. The investigation focused on the impacts of
bend angels and rib/channel dimensions of serpentine flow
channel pattern on the performance and investigated how they
improve the performance. The fuel cell employed for these
experiments was a micro single PEMFC with a membrane of
1.44 cm2 Nafion NRE-212. The results show that 60° and 120°
bend angles can provide the better performances at 20 and 40
sccm inlet flow rates comparing to that the conventional design.
Additionally, wider channel with narrower rib spacing gives
better performance. These results may be applied to develop
universal heuristics for the design of flow pattern of micro
PEMFC.
Abstract: The rate of nitrate adsorption by a nitrate selective ion
exchange resin was investigated in a well-stirred batch experiments.
The kinetic experimental data were simulated with diffusion models including external mass transfer, particle diffusion and chemical
adsorption. Particle pore volume diffusion and particle surface diffusion were taken into consideration separately and simultaneously
in the modeling. The model equations were solved numerically using the Crank-Nicholson scheme. An optimization technique was
employed to optimize the model parameters. All nitrate concentration
decay data were well described with the all diffusion models. The
results indicated that the kinetic process is initially controlled by external mass transfer and then by particle diffusion. The external
mass transfer coefficient and the coefficients of pore volume diffusion and surface diffusion in all experiments were close to each
other with the average value of 8.3×10-3 cm/S for external mass
transfer coefficient. In addition, the models are more sensitive to the
mass transfer coefficient in comparison with particle diffusion. Moreover, it seems that surface diffusion is the dominant particle
diffusion in comparison with pore volume diffusion.
Abstract: In this paper, we propose a new seed projection method for solving shifted systems with multiple right-hand sides. This seed projection method uses a seed selection strategy. Numerical experiments are presented to show the efficiency of the newly method.
Abstract: The particular interests of this paper is to explore if the simple Genetic Algorithms (GA) starts with population of only two individuals and applying different crossover technique over these parents to produced 104 children, each one has different attributes inherited from their parents; is better than starting with population of 100 individuals; and using only one type crossover (order crossover OX). For this reason we implement GA with 52 different crossover techniques; each one produce two children; which means 104 different children will be produced and this may discover more search space, also we implement classic GA with order crossover and many experiments were done over 3 Travel Salesman Problem (TSP) to find out which method is better, and according to the results we can say that GA with Multi-crossovers is much better.