Abstract: In the present work we model a Multiquantum Well
structure Separate Absorption and Charge Multiplication Avalanche
Photodiode (MQW-SACM-APD), while the Absorption region
coincide with the MQW. We consider the nonuniformity of electric
field using split-step method in active region. This model is based on
the carrier rate equations in the different regions of the device. Using
the model we obtain the photocurrent, and dark current. As an
example, InGaAs/InP SACM-APD and MQW-SACM-APD are
simulated. There is a good agreement between the simulation and
experimental results.
Abstract: The hydrolysis kinetics of polycrystalline lithium hydride (LiH) in argon at various low humidities was measured by gravimetry and Raman spectroscopy with ambient water concentration ranging from 200 to 1200 ppm. The results showed that LiH hydrolysis curve revealed a paralinear shape, which was attributed to two different reaction stages that forming different products as explained by the 'Layer Diffusion Control' model. Based on the model, a novel two-stage rate equation for LiH hydrolysis reactions was developed and used to fit the experimental data for determination of Li2O steady thickness Hs and the ultimate hydrolysis rate vs. The fitted data presented a rise of Hs as ambient water concentration cw increased. However, in spite of the negative effect imposed by Hs increasing, the upward trend of vs remained, which implied that water concentration, rather than Li2O thickness, played a predominant role in LiH hydrolysis kinetics. In addition, the proportional relationship between vsHs and cw predicted by rate equation and confirmed by gravimetric data validated the model in such conditions.
Abstract: Most CT reconstruction system x-ray computed
tomography (CT) is a well established visualization technique in
medicine and nondestructive testing. However, since CT scanning
requires sampling of radiographic projections from different viewing
angles, common CT systems with mechanically moving parts are too
slow for dynamic imaging, for instance of multiphase flows or live
animals. A large number of X-ray projections are needed to
reconstruct CT images, so the collection and calculation of the
projection data consume too much time and harmful for patient. For
the purpose of solving the problem, in this study, we proposed a
method for tomographic reconstruction of a sample from a limited
number of x-ray projections by using linear interpolation method. In
simulation, we presented reconstruction from an experimental x-ray
CT scan of a Aluminum phantom that follows to two steps: X-ray
projections will be interpolated using linear interpolation method and
using it for CT reconstruction based upon Ordered Subsets
Expectation Maximization (OSEM) method.
Abstract: The transformation of vocal characteristics aims at
modifying voice such that the intelligibility of aphonic voice is
increased or the voice characteristics of a speaker (source speaker) to
be perceived as if another speaker (target speaker) had uttered it. In
this paper, the current state-of-the-art voice characteristics
transformation methodology is reviewed. Special emphasis is placed
on voice transformation methodology and issues for improving the
transformed speech quality in intelligibility and naturalness are
discussed. In particular, it is suggested to use the modulation theory
of speech as a base for research on high quality voice transformation.
This approach allows one to separate linguistic, expressive, organic
and perspective information of speech, based on an analysis of how
they are fused when speech is produced. Therefore, this theory
provides the fundamentals not only for manipulating non-linguistic,
extra-/paralinguistic and intra-linguistic variables for voice
transformation, but also for paving the way for easily transposing the
existing voice transformation methods to emotion-related voice
quality transformation and speaking style transformation. From the
perspectives of human speech production and perception, the popular
voice transformation techniques are described and classified them
based on the underlying principles either from the speech production
or perception mechanisms or from both. In addition, the advantages
and limitations of voice transformation techniques and the
experimental manipulation of vocal cues are discussed through
examples from past and present research. Finally, a conclusion and
road map are pointed out for more natural voice transformation
algorithms in the future.
Abstract: This study deals with Computational Fluid Dynamics
(CFD) studies of the interactions between the air flow and louvered
fins which equipped the automotive heat exchangers. 3D numerical
simulation results are obtained by using the ANSYS Fluent 13.0 code
and compared to experimental data. The paper studies the effect of
louver angle and louver pitch geometrical parameters, on overall
thermal hydraulic performances of louvered fins.
The comparison between CFD simulations and experimental data
show that established 3-D CFD model gives a good agreement. The
validation agrees, with about 7% of deviation respectively of friction
and Colburn factors to experimental results. As first, it is found that
the louver angle has a strong influence on the heat transfer rate. Then,
louver angle and louver pitch variation of the louvers and their effects
on thermal hydraulic performances are studied. In addition to this
study, it is shown that the second half of the fin takes has a
significant contribution on pressure drop increase without any
increase in heat transfer.
Abstract: Many experimental results suggest that more precise
spike timing is significant in neural information processing. We
construct a self-organization model using the spatiotemporal patterns,
where Spike-Timing Dependent Plasticity (STDP) tunes the
conduction delays between neurons. We show that the fluctuation of
conduction delays causes globally continuous and locally distributed
firing patterns through the self-organization.
Abstract: In this paper, we present a new and effective image indexing technique that extracts features directly from DCT domain. Our proposed approach is an object-based image indexing. For each block of size 8*8 in DCT domain a feature vector is extracted. Then, feature vectors of all blocks of image using a k-means algorithm is clustered into groups. Each cluster represents a special object of the image. Then we select some clusters that have largest members after clustering. The centroids of the selected clusters are taken as image feature vectors and indexed into the database. Also, we propose an approach for using of proposed image indexing method in automatic image classification. Experimental results on a database of 800 images from 8 semantic groups in automatic image classification are reported.
Abstract: A 3D industrial computed tomography (CT)
manufactured based on a first generation CT systems, single-source
– single-detector, was evaluated. Operation accuracy assessment of
the manufactured system was achieved using simulation in
comparison with experimental tests. 137Cs and 60Co were used as a gamma source. Simulations were achieved using MCNP4C code.
Experimental tests of 137Cs were in good agreement with the simulations
Abstract: This paper describes a novel projection algorithm, the Projection Onto Span Algorithm (POSA) for wavelet-based superresolution and removing speckle (in wavelet domain) of unknown variance from Synthetic Aperture Radar (SAR) images. Although the POSA is good as a new superresolution algorithm for image enhancement, image metrology and biometric identification, here one will use it like a tool of despeckling, being the first time that an algorithm of super-resolution is used for despeckling of SAR images. Specifically, the speckled SAR image is decomposed into wavelet subbands; POSA is applied to the high subbands, and reconstruct a SAR image from the modified detail coefficients. Experimental results demonstrate that the new method compares favorably to several other despeckling methods on test SAR images.
Abstract: This work presents a new phonetic transcription system based on a tree of hierarchical pronunciation rules expressed as context-specific grapheme-phoneme correspondences. The tree is automatically inferred from a phonetic dictionary by incrementally analyzing deeper context levels, eventually representing a minimum set of exhaustive rules that pronounce without errors all the words in the training dictionary and that can be applied to out-of-vocabulary words. The proposed approach improves upon existing rule-tree-based techniques in that it makes use of graphemes, rather than letters, as elementary orthographic units. A new linear algorithm for the segmentation of a word in graphemes is introduced to enable outof- vocabulary grapheme-based phonetic transcription. Exhaustive rule trees provide a canonical representation of the pronunciation rules of a language that can be used not only to pronounce out-of-vocabulary words, but also to analyze and compare the pronunciation rules inferred from different dictionaries. The proposed approach has been implemented in C and tested on Oxford British English and Basic English. Experimental results show that grapheme-based rule trees represent phonetically sound rules and provide better performance than letter-based rule trees.
Abstract: This paper explores university course timetabling
problem. There are several characteristics that make scheduling and
timetabling problems particularly difficult to solve: they have huge
search spaces, they are often highly constrained, they require
sophisticated solution representation schemes, and they usually
require very time-consuming fitness evaluation routines. Thus
standard evolutionary algorithms lack of efficiency to deal with
them. In this paper we have proposed a memetic algorithm that
incorporates the problem specific knowledge such that most of
chromosomes generated are decoded into feasible solutions.
Generating vast amount of feasible chromosomes makes the progress
of search process possible in a time efficient manner. Experimental
results exhibit the advantages of the developed Hybrid Genetic
Algorithm than the standard Genetic Algorithm.
Abstract: An experimental campaign of measurements for a
Darrieus vertical-axis wind turbine (VAWT) is presented for open
field conditions. The turbine is characterized by a twisted bladed
design, each blade being placed at a fixed distance from the rotational
shaft. The experimental setup to perform the acquisitions is described.
The results are lower than expected, due to the high influence of the
wind shear.
Abstract: Decrease in hardware costs and advances in computer
networking technologies have led to increased interest in the use of
large-scale parallel and distributed computing systems. One of the
biggest issues in such systems is the development of effective
techniques/algorithms for the distribution of the processes/load of a
parallel program on multiple hosts to achieve goal(s) such as
minimizing execution time, minimizing communication delays,
maximizing resource utilization and maximizing throughput.
Substantive research using queuing analysis and assuming job
arrivals following a Poisson pattern, have shown that in a multi-host
system the probability of one of the hosts being idle while other host
has multiple jobs queued up can be very high. Such imbalances in
system load suggest that performance can be improved by either
transferring jobs from the currently heavily loaded hosts to the lightly
loaded ones or distributing load evenly/fairly among the hosts .The
algorithms known as load balancing algorithms, helps to achieve the
above said goal(s). These algorithms come into two basic categories -
static and dynamic. Whereas static load balancing algorithms (SLB)
take decisions regarding assignment of tasks to processors based on
the average estimated values of process execution times and
communication delays at compile time, Dynamic load balancing
algorithms (DLB) are adaptive to changing situations and take
decisions at run time.
The objective of this paper work is to identify qualitative
parameters for the comparison of above said algorithms. In future this
work can be extended to develop an experimental environment to
study these Load balancing algorithms based on comparative
parameters quantitatively.
Abstract: Support Vector Domain Description (SVDD) is one of the best-known one-class support vector learning methods, in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. As all kernel-based learning algorithms its performance depends heavily on the proper choice of the kernel parameter. This paper proposes a new approach to select kernel's parameter based on maximizing the distance between both gravity centers of normal and abnormal classes, and at the same time minimizing the variance within each class. The performance of the proposed algorithm is evaluated on several benchmarks. The experimental results demonstrate the feasibility and the effectiveness of the presented method.
Abstract: The atmospheric pressure plasma torch with a direct
current arc discharge stabilized by water vapor vortex was
experimentally investigated. Overheated up to 450K water vapor was
used as plasma forming gas. Plasma torch design is one of the most
important factors leading to a stable operation of the device. The
electrical and thermal characteristics of the plasma torch were
determined during the experimental investigations. The design and
the basic characteristics of the water vapor plasma torch are presented
in the paper.
Plasma torches with the electric arc stabilized by water vapor
vortex provide special performance characteristics in some plasma
processing applications such as thermal plasma neutralization and
destruction of organic wastes enabling to extract high caloric value
synthesis gas as by-product of the process. Syngas could be used as a
surrogate fuel partly replacing the dependence on the fossil fuels or
used as a feedstock for hydrogen, methanol production.
Abstract: Cooktop burners are widely used nowadays. In
cooktop burner design, nozzle efficiency and greenhouse
gas(GHG) emissions mainly depend on heat transfer from the
premixed flame to the impinging surface. This is a complicated
issue depending on the individual and combined effects of various
input combustion variables. Optimal operating conditions for
sustainable burner design were rarely addressed, especially in the
case of multiple slot-jet burners. Through evaluating the optimal
combination of combustion conditions for a premixed slot-jet
array, this paper develops a practical approach for the sustainable
design of gas cooktop burners. Efficiency, CO and NOx emissions
in respect of an array of slot jets using premixed flames were
analysed. Response surface experimental design were applied to
three controllable factors of the combustion process, viz.
Reynolds number, equivalence ratio and jet-to-vessel distance.
Desirability Function Approach(DFA) is the analytic technique
used for the simultaneous optimization of the efficiency and
emission responses.
Abstract: In this study the behavior of interlaminar fracture of
carbon-epoxy thermoplastic laminated composite is investigated
numerically and experimentally. Tests are performed with Arcan
specimens. Testing with Arcan specimen gives the opportunity of
utilizing just one kind of specimen for extracting fracture properties
for mode I, mode II and different mixed mode ratios of materials with
exerting load via different loading angles. Variation of loading angles
in range of 0-90° made possible to achieve different mixed mode
ratios. Correction factors for various conditions are obtained from
ABAQUS 2D finite element models which demonstrate the finite
shape of Arcan specimens used in this study. Finally, applying the
correction factors to critical loads obtained experimentally, critical
interlaminar fracture toughness of this type of carbon- epoxy
composite has been attained.
Abstract: This paper proposed a nonlinear model predictive
control (MPC) method for the control of gantry crane. One of the main
motivations to apply MPC to control gantry crane is based on its
ability to handle control constraints for multivariable systems. A
pre-compensator is constructed to compensate the input nonlinearity
(nonsymmetric dead zone with saturation) by using its inverse
function. By well tuning the weighting function matrices, the control
system can properly compromise the control between crane position
and swing angle. The proposed control algorithm was implemented for
the control of gantry crane system in System Control Lab of University
of Technology, Sydney (UTS), and achieved desired experimental
results.
Abstract: Science and technology of ultrasonic is widely used in
recent years for industrial and medicinal application. The acoustical
properties of 2-mercapto substituted pyrimidines viz.,2- Mercapto-4-
(2’,4’ –dichloro phenyl) – 6-(2’ – hydroxyl -4’ –methyl-5’ –
chlorophenyl) pyrimidine and 2 –Mercapto – 4-(4’ –chloro phenyl) –
6-(2’ – hydroxyl -4’ –methyl-5’ –chlorophenyl) pyrimidine have been
investigated from the ultrasonic velocity and density measurements at
different concentration and different % in dioxane-water mixture at
305K. The adiabatic compressibility (βs), acoustic impedance (Z),
intermolecular free length (Lf), apparent molar volume(ϕv) and
relative association (RA) values have been calculated from the
experimental data of velocity and density measurement at
concentration range of 0.01- 0.000625 mol/lit and 70%,75% and 80%
dioxane water mixture. These above parameters are used to discuss
the structural and molecular interactions.
Abstract: In two studies we tested the hypothesis that the
appropriate linguistic formulation of a deontic rule – i.e. the
formulation which clarifies the monadic nature of deontic operators
- should produce more correct responses than the conditional
formulation in Wason selection task. We tested this assumption by
presenting a prescription rule and a prohibition rule in conditional
vs. proper deontic formulation. We contrasted this hypothesis with
two other hypotheses derived from social contract theory and
relevance theory. According to the first theory, a deontic rule
expressed in terms of cost-benefit should elicit a cheater detection
module, sensible to mental states attributions and thus able to
discriminate intentional rule violations from accidental rule
violations. We tested this prevision by distinguishing the two types
of violations. According to relevance theory, performance in
selection task should improve by increasing cognitive effect and
decreasing cognitive effort. We tested this prevision by focusing
experimental instructions on the rule vs. the action covered by the
rule. In study 1, in which 480 undergraduates participated, we
tested these predictions through a 2 x 2 x 2 x 2 (type of the rule x
rule formulation x type of violation x experimental instructions)
between-subjects design. In study 2 – carried out by means of a 2 x
2 (rule formulation x type of violation) between-subjects design -
we retested the hypothesis of rule formulation vs. the cheaterdetection
hypothesis through a new version of selection task in
which intentional vs. accidental rule violations were better
discriminated. 240 undergraduates participated in this study.
Results corroborate our hypothesis and challenge the contrasting
assumptions. However, they show that the conditional formulation
of deontic rules produces a lower performance than what is
reported in literature.