Abstract: An adaptive Chinese hand-talking system is presented
in this paper. By analyzing the 3 data collecting strategies for new
users, the adaptation framework including supervised and unsupervised
adaptation methods is proposed. For supervised adaptation,
affinity propagation (AP) is used to extract exemplar subsets, and enhanced
maximum a posteriori / vector field smoothing (eMAP/VFS)
is proposed to pool the adaptation data among different models. For
unsupervised adaptation, polynomial segment models (PSMs) are
used to help hidden Markov models (HMMs) to accurately label
the unlabeled data, then the "labeled" data together with signerindependent
models are inputted to MAP algorithm to generate
signer-adapted models. Experimental results show that the proposed
framework can execute both supervised adaptation with small amount
of labeled data and unsupervised adaptation with large amount
of unlabeled data to tailor the original models, and both achieve
improvements on the performance of recognition rate.
Abstract: The porous silicon (PS), formed from the anodization
of a p+ type substrate silicon, consists of a network organized in a
pseudo-column as structure of multiple side ramifications. Structural
micro-topology can be interpreted as the fraction of the interconnected
solid phase contributing to thermal transport. The
reduction of dimensions of silicon of each nanocristallite during the
oxidation induced a reduction in thermal conductivity. Integration of
thermal sensors in the Microsystems silicon requires an effective
insulation of the sensor element. Indeed, the low thermal conductivity
of PS consists in a very promising way in the fabrication of integrated
thermal Microsystems.In this work we are interesting in the
measurements of thermal conductivity (on the surface and in depth)
of PS by the micro-Raman spectroscopy. The thermal conductivity is
studied according to the parameters of anodization (initial doping and
current density. We also, determine porosity of samples by
spectroellipsometry.
Abstract: This paper presents a new Quality-Controlled, wavelet based, compression method for electrocardiogram (ECG) signals. Initially, an ECG signal is decomposed using the wavelet transform. Then, the resulting coefficients are iteratively thresholded to guarantee that a predefined goal percent root mean square difference (GPRD) is matched within tolerable boundaries. The quantization strategy of extracted non-zero wavelet coefficients (NZWC), according to the combination of RLE, HUFFMAN and arithmetic encoding of the NZWC and a resulting look up table, allow the accomplishment of high compression ratios with good quality reconstructed signals.
Abstract: In this paper, we investigated the characteristic of a
clinical dataseton the feature selection and classification
measurements which deal with missing values problem.And also
posed the appropriated techniques to achieve the aim of the activity;
in this research aims to find features that have high effect to mortality
and mortality time frame. We quantify the complexity of a clinical
dataset. According to the complexity of the dataset, we proposed the
data mining processto cope their complexity; missing values, high
dimensionality, and the prediction problem by using the methods of
missing value replacement, feature selection, and classification.The
experimental results will extend to develop the prediction model for
cardiology.
Abstract: Experimental investigation of heat transfer and
friction factor characteristics of circular tube fitted with 300 right-left helical screw inserts with 100 mm spacer of different twist ratio has
been presented for laminar and turbulent flow.. The experimental data obtained were compared with those obtained from plain tube
published data. The heat transfer coefficient enhancement for 300 RL
inserts with 100 mm spacer is quite comparable with for 300 R-L
inserts. Performance evaluation analysis has been made and found
that the performance ratio increases with increasing Reynolds number
and decreasing twist ration with the maximum for the twist ratio 2.93.
Also, the performance ratio of more than one indicates that the type
of twist inserts can be used effectively for heat transfer augmentation.
Abstract: In this work, the influence of temperature on the
different parameters of solar cells based on organic semiconductors
are studied. The short circuit current Isc increases so monotonous
with temperature and then saturates to a maximum value before
decreasing at high temperatures. The open circuit voltage Vco
decreases linearly with temperature. The fill factor FF and efficiency,
which are directly related with Isc and Vco follow the variations of
the letters. The phenomena are explained by the behaviour of the
mobility which is a temperature activated process.
Abstract: Text categorization is the problem of classifying text
documents into a set of predefined classes. After a preprocessing
step, the documents are typically represented as large sparse vectors.
When training classifiers on large collections of documents, both the
time and memory restrictions can be quite prohibitive. This justifies
the application of feature selection methods to reduce the
dimensionality of the document-representation vector. In this paper,
we present three feature selection methods: Information Gain,
Support Vector Machine feature selection called (SVM_FS) and
Genetic Algorithm with SVM (called GA_SVM). We show that the
best results were obtained with GA_SVM method for a relatively
small dimension of the feature vector.
Abstract: Superelastic Shape Memory Alloy (SMA) is accepted
when it used as connection in steel structures. The seismic behaviour
of steel frames with SMA is being assessed in this study. Three eightstorey
steel frames with different SMA systems are suggested, the
first one of which is braced with diagonal bracing system, the second
one is braced with nee bracing system while the last one is which the
SMA is used as connection at the plastic hinge regions of beams.
Nonlinear time history analyses of steel frames with SMA subjected
to two different ground motion records have been performed using
Seismostruct software. To evaluate the efficiency of suggested
systems, the dynamic responses of the frames were compared. From
the comparison results, it can be concluded that using SMA element
is an effective way to improve the dynamic response of structures
subjected to earthquake excitations. Implementing the SMA braces
can lead to a reduction in residual roof displacement. The shape
memory alloy is effective in reducing the maximum displacement at
the frame top and it provides a large elastic deformation range. SMA
connections are very effective in dissipating energy and reducing the
total input energy of the whole frame under severe seismic ground
motion. Using of the SMA connection system is more effective in
controlling the reaction forces at the base frame than other bracing
systems. Using SMA as bracing is more effective in reducing the
displacements. The efficiency of SMA is dependant on the input
wave motions and the construction system as well.
Abstract: This paper deals with the formulation of Maxwell-s equations in a cavity resonator in the presence of the gravitational field produced by a blackhole. The metric of space-time due to the blackhole is the Schwarzchild metric. Conventionally, this is expressed in spherical polar coordinates. In order to adapt this metric to our problem, we have considered this metric in a small region close to the blackhole and expressed this metric in a cartesian system locally.
Abstract: A novel behavioral detection framework is proposed
to detect zero day buffer overflow vulnerabilities (based on network
behavioral signatures) using zero-day exploits, instead of the
signature-based or anomaly-based detection solutions currently
available for IDPS techniques. At first we present the detection
model that uses shadow honeypot. Our system is used for the online
processing of network attacks and generating a behavior detection
profile. The detection profile represents the dataset of 112 types of
metrics describing the exact behavior of malware in the network. In
this paper we present the examples of generating behavioral
signatures for two attacks – a buffer overflow exploit on FTP server
and well known Conficker worm. We demonstrated the visualization
of important aspects by showing the differences between valid
behavior and the attacks. Based on these metrics we can detect
attacks with a very high probability of success, the process of
detection is however very expensive.
Abstract: We evaluate the average energy consumption per bit
in Optical Packet Switches equipped with BENES switching fabric
realized in Semiconductor Optical Amplifier (SOA) technology. We
also study the impact that the Amplifier Spontaneous Emission
(ASE) noise generated by a transmission system has on the power
consumption of the BENES switches due to the gain saturation of the
SOAs used to realize the switching fabric. As a matter of example for
32×32 switches supporting 64 wavelengths and offered traffic equal
to 0,8, the average energy consumption per bit is 2, 34 · 10-1 nJ/bit
and increases if ASE noise introduced by the transmission systems
is increased.
Abstract: In this paper, an automatic system of diagnosis was
developed to detect and locate in real time the defects of the wound
rotor asynchronous machine associated to electronic converter. For
this purpose, we have treated the signals of the measured parameters
(current and speed) to use them firstly, as indicating variables of the
machine defects under study and, secondly, as inputs to the Artificial
Neuron Network (ANN) for their classification in order to detect the
defect type in progress. Once a defect is detected, the interpretation
system of information will give the type of the defect and its place of
appearance.
Abstract: Defect prevention is the most vital but habitually
neglected facet of software quality assurance in any project. If
functional at all stages of software development, it can condense the
time, overheads and wherewithal entailed to engineer a high quality
product. The key challenge of an IT industry is to engineer a
software product with minimum post deployment defects.
This effort is an analysis based on data obtained for five selected
projects from leading software companies of varying software
production competence. The main aim of this paper is to provide
information on various methods and practices supporting defect
detection and prevention leading to thriving software generation. The
defect prevention technique unearths 99% of defects. Inspection is
found to be an essential technique in generating ideal software
generation in factories through enhanced methodologies of abetted
and unaided inspection schedules. On an average 13 % to 15% of
inspection and 25% - 30% of testing out of whole project effort time
is required for 99% - 99.75% of defect elimination.
A comparison of the end results for the five selected projects
between the companies is also brought about throwing light on the
possibility of a particular company to position itself with an
appropriate complementary ratio of inspection testing.
Abstract: In the present study the efficiency of Big Bang-Big
Crunch (BB-BC) algorithm is investigated in discrete structural
design optimization. It is shown that a standard version of the BB-BC
algorithm is sometimes unable to produce reasonable solutions to
problems from discrete structural design optimization. Two
reformulations of the algorithm, which are referred to as modified
BB-BC (MBB-BC) and exponential BB-BC (EBB-BC), are
introduced to enhance the capability of the standard algorithm in
locating good solutions for steel truss and frame type structures,
respectively. The performances of the proposed algorithms are
experimented and compared to its standard version as well as some
other algorithms over several practical design examples. In these
examples, steel structures are sized for minimum weight subject to
stress, stability and displacement limitations according to the
provisions of AISC-ASD.
Abstract: Particle damping is a technique to reduce the
structural vibrations by means of placing small metallic particles
inside a cavity that is attached to the structure at location of high
vibration amplitudes. In this paper, we have presented an analytical
model to simulate the particle damping of two dimensional transient
vibrations in structure operating under high centrifugal loads. The
simulation results show that this technique remains effective as long
as the ratio of the dynamic acceleration of the structure to the applied
centrifugal load is more than 0.1. Particle damping increases with the
increase of particle to structure mass ratio. However, unlike to the
case of particle damping in the absence of centrifugal loads where
the damping efficiency strongly depends upon the size of the cavity,
here this dependence becomes very weak. Despite the simplicity of
the model, the simulation results are considerably in good agreement
with the very scarce experimental data available in the literature for
particle damping under centrifugal loads.
Abstract: This study presents design of a carbon silicon electrode
for iontophorsis treatment towards alopecia. The alopecia is a medical
description means loss of hair from the body. For solving this problem,
the drug need to be delivered into the scalp, therefore, the
iontophoresis was chosen to use in this treatment. However, almost
common electrodes of iontophoresis device are made with metal
material, the electrodes could give patients hurt when they using it, and
it is hard to avoid the hair for attaching the hair. For this reason, an
electrode is made with silicon material to decrease the hurt from the
electrodes, and the carbon material is mixed in it for increasing
conductance. The several cones with stainless material on the
electrode make the electrode is able to void hair to attach the affected
part. According to the results of a vivo-experiment, the carbon silicon
electrode showed a good performance and in treatment comfortably.
Abstract: Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.
Abstract: Calcium oxide (CaO) as carbon dioxide (CO2)
adsorbent at the elevated temperature has been very well-received
thus far. The CaO can be synthesized from natural calcium carbonate
(CaCO3) sources through the reversible calcination-carbonation
process. In the study, cockle shell has been selected as CaO
precursors. The objectives of the study are to investigate the
performance of calcination and carbonation with respect to different
temperature, heating rate, particle size and the duration time. Overall,
better performance is shown at the calcination temperature of 850oC
for 40 minutes, heating rate of 20oC/min, particle size of < 0.125mm
and the carbonation temperature is at 650oC. The synthesized
materials have been characterized by nitrogen physisorption and
surface morphology analysis. The effectiveness of the synthesized
cockle shell in capturing CO2 (0.72 kg CO2/kg adsorbent) which is
comparable to the commercialized adsorbent (0.60 kg CO2/kg
adsorbent) makes them as the most promising materials for CO2
capture.
Abstract: An adaptive dynamic cerebellar model articulation
controller (DCMAC) neural network used for solving the prediction
and identification problem is proposed in this paper. The proposed
DCMAC has superior capability to the conventional cerebellar model
articulation controller (CMAC) neural network in efficient learning
mechanism, guaranteed system stability and dynamic response. The
recurrent network is embedded in the DCMAC by adding feedback
connections in the association memory space so that the DCMAC
captures the dynamic response, where the feedback units act as
memory elements. The dynamic gradient descent method is adopted to
adjust DCMAC parameters on-line. Moreover, the analytical method
based on a Lyapunov function is proposed to determine the
learning-rates of DCMAC so that the variable optimal learning-rates
are derived to achieve most rapid convergence of identifying error.
Finally, the adaptive DCMAC is applied in two computer simulations.
Simulation results show that accurate identifying response and
superior dynamic performance can be obtained because of the
powerful on-line learning capability of the proposed DCMAC.
Abstract: The aim of this research was to calculate the
mechanical properties of Pd3Rh and PdRh3 ordered alloys. The
molecular dynamics (MD) simulation technique was used to obtain
temperature dependence of the energy, the Yong modulus, the shear
modulus, the bulk modulus, Poisson-s ratio and the elastic stiffness
constants at the isobaric-isothermal (NPT) ensemble in the range of
100-325 K. The interatomic potential energy and force on atoms were
calculated by Quantum Sutton-Chen (Q-SC) many body potential.
Our MD simulation results show the effect of temperature on the
cohesive energy and mechanical properties of Pd3Rh as well as
PdRh3 alloys. Our computed results show good agreement with the
experimental results where they have been available.