Abstract: This paper presents the source extraction system which can extract only target signals with constraints on source localization in on-line systems. The proposed system is a kind of methods for enhancing a target signal and suppressing other interference signals. But, the performance of proposed system is superior to any other methods and the extraction of target source is comparatively complete. The method has a beamforming concept and uses an improved time-frequency (TF) mask-based BSS algorithm to separate a target signal from multiple noise sources. The target sources are assumed to be in front and test data was recorded in a reverberant room. The experimental results of the proposed method was evaluated by the PESQ score of real-recording sentences and showed a noticeable speech enhancement.
Abstract: Bone remodeling occurs by the balanced action of
bone resorbing osteoclasts (OC) and bone-building osteoblasts.
Increased bone resorption by excessive OC activity contributes
to malignant and non-malignant diseases including osteoporosis.
To study OC differentiation and function, OC formed in
in vitro cultures are currently counted manually, a tedious
procedure which is prone to inter-observer differences. Aiming
for an automated OC-quantification system, classification of
OC and precursor cells was done on fluorescence microscope
images based on the distinct appearance of fluorescent nuclei.
Following ellipse fitting to nuclei, a combination of eight
features enabled clustering of OC and precursor cell nuclei.
After evaluating different machine-learning techniques, LOGREG
achieved 74% correctly classified OC and precursor cell
nuclei, outperforming human experts (best expert: 55%). In
combination with the automated detection of total cell areas,
this system allows to measure various cell parameters and most
importantly to quantify proteins involved in osteoclastogenesis.
Abstract: A satellite is being integrated and tested by BISEE (Beijing Institute of Spacecraft Environment Engineering). This paper describes the infrared lamp array simulation technology used for satellite thermal balance and thermal vacuum test. These tests were performed in KM6 space environmental simulator in Beijing, China. New software and hardware developed by BISEE, along with enhanced heat flux uniformity, provided for well accomplished thermal balance and thermal vacuum tests. The flux uniformity of lamp array was satisfied with test requirement. Monitored background radiometer offered reliable heat flux measurements with remarkable repeatability. Simulation software supplied accurate thermal flux distribution predictions.
Abstract: Artificial Neural Network (ANN) has been
extensively used for classification of heart sounds for its
discriminative training ability and easy implementation. However, it
suffers from overparameterization if the number of nodes is not
chosen properly. In such cases, when the dataset has redundancy
within it, ANN is trained along with this redundant information that
results in poor validation. Also a larger network means more
computational expense resulting more hardware and time related
cost. Therefore, an optimum design of neural network is needed
towards real-time detection of pathological patterns, if any from heart
sound signal. The aims of this work are to (i) select a set of input
features that are effective for identification of heart sound signals and
(ii) make certain optimum selection of nodes in the hidden layer for a
more effective ANN structure. Here, we present an optimization
technique that involves Singular Value Decomposition (SVD) and
QR factorization with column pivoting (QRcp) methodology to
optimize empirically chosen over-parameterized ANN structure.
Input nodes present in ANN structure is optimized by SVD followed
by QRcp while only SVD is required to prune undesirable hidden
nodes. The result is presented for classifying 12 common
pathological cases and normal heart sound.
Abstract: In this paper a non-parametric statistical pattern recognition algorithm for the problem of credit scoring will be presented. The proposed algorithm is based on a clustering k- means algorithm and allows for the determination of subclasses of homogenous elements in the data. The algorithm will be tested on two benchmark datasets and its performance compared with other well known pattern recognition algorithm for credit scoring.
Abstract: In this paper we present a generic approach for the problem of the blind estimation of the parameters of linear and convolutional error correcting codes. In a non-cooperative context, an adversary has only access to the noised transmission he has intercepted. The intercepter has no knowledge about the parameters used by the legal users. So, before having acess to the information he has first to blindly estimate the parameters of the error correcting code of the communication. The presented approach has the main advantage that the problem of reconstruction of such codes can be expressed in a very simple way. This allows us to evaluate theorical bounds on the complexity of the reconstruction process but also bounds on the estimation rate. We show that some classical reconstruction techniques are optimal and also explain why some of them have theorical complexities greater than these experimentally observed.
Abstract: In this paper we present an efficient system for
independent speaker speech recognition based on neural network
approach. The proposed architecture comprises two phases: a
preprocessing phase which consists in segmental normalization and
features extraction and a classification phase which uses neural
networks based on nonparametric density estimation namely the
general regression neural network (GRNN). The relative
performances of the proposed model are compared to the similar
recognition systems based on the Multilayer Perceptron (MLP), the
Recurrent Neural Network (RNN) and the well known Discrete
Hidden Markov Model (HMM-VQ) that we have achieved also.
Experimental results obtained with Arabic digits have shown that the
use of nonparametric density estimation with an appropriate
smoothing factor (spread) improves the generalization power of the
neural network. The word error rate (WER) is reduced significantly
over the baseline HMM method. GRNN computation is a successful
alternative to the other neural network and DHMM.
Abstract: In this paper, the experimental design of using the
Taguchi method is employed to optimize the processing parameters in
the plasma arc surface hardening process. The processing parameters
evaluated are arc current, scanning velocity and carbon content of
steel. In addition, other significant effects such as the relation between
processing parameters are also investigated. An orthogonal array,
signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are
employed to investigate the effects of these processing parameters.
Through this study, not only the hardened depth increased and surface
roughness improved, but also the parameters that significantly affect
the hardening performance are identified. Experimental results are
provided to verify the effectiveness of this approach.
Abstract: The most Malaria cases are occur along Thai-Mynmar border. Mathematical model for the transmission of Plasmodium falciparum and Plasmodium vivax malaria in a mixed population of Thais and migrant Burmese living along the Thai-Myanmar Border is studied. The population is separated into two groups, Thai and Burmese. Each population is divided into susceptible, infected, dormant and recovered subclasses. The loss of immunity by individuals in the infected class causes them to move back into the susceptible class. The person who is infected with Plasmodium vivax and is a member of the dormant class can relapse back into the infected class. A standard dynamical method is used to analyze the behaviors of the model. Two stable equilibrium states, a disease-free state and an epidemic state, are found to be possible in each population. A disease-free equilibrium state in the Thai population occurs when there are no infected Burmese entering the community. When infected Burmese enter the Thai community, an epidemic state can occur. It is found that the disease-free state is stable when the threshold number is less than one. The epidemic state is stable when a second threshold number is greater than one. Numerical simulations are used to confirm the results of our model.
Abstract: To help the client to select a competent agent
construction enterprise (ACE), this study aims to investigate the
selection standards by using the Fuzzy Analytic Hierarchy Process
(FAHP) and build an evaluation mathematical model with Grey
Relational Analysis (GRA). According to the outputs of literature
review, four orderly levels are established within the model, taking the
consideration of various agent construction models in practice. Then,
the process of applying FAHP and GRA is discussed in detailed.
Finally, through a case study, this paper illustrates how to apply these
methods in getting the weights of each standard and the final
assessment result.
Abstract: Selection of a project among a set of possible
alternatives is a difficult task that the decision maker (DM) has to
face. In this paper, by using a fuzzy TOPSIS technique we propose a
new method for a project selection problem. After reviewing four
common methods of comparing investment alternatives (net present
value, rate of return, benefit cost analysis and payback period) we
use them as criteria in a TOPSIS technique. First we calculate the
weight of each criterion by a pairwise comparison and then we utilize
the improved TOPSIS assessment for the project selection.
Abstract: Fast delay estimation methods, as opposed to
simulation techniques, are needed for incremental performance
driven layout synthesis. On-chip inductive effects are becoming
predominant in deep submicron interconnects due to increasing clock
speed and circuit complexity. Inductance causes noise in signal
waveforms, which can adversely affect the performance of the circuit
and signal integrity. Several approaches have been put forward which
consider the inductance for on-chip interconnect modelling. But for
even much higher frequency, of the order of few GHz, the shunt
dielectric lossy component has become comparable to that of other
electrical parameters for high speed VLSI design. In order to cope up
with this effect, on-chip interconnect has to be modelled as
distributed RLCG line. Elmore delay based methods, although
efficient, cannot accurately estimate the delay for RLCG interconnect
line. In this paper, an accurate analytical delay model has been
derived, based on first and second moments of RLCG
interconnection lines. The proposed model considers both the effect
of inductance and conductance matrices. We have performed the
simulation in 0.18μm technology node and an error of as low as less
as 5% has been achieved with the proposed model when compared to
SPICE. The importance of the conductance matrices in interconnect
modelling has also been discussed and it is shown that if G is
neglected for interconnect line modelling, then it will result an delay
error of as high as 6% when compared to SPICE.
Abstract: The complexity of teaching English in higher
institutions by non-native speakers within a second/foreign language
setting has created continuous discussions and research about
teaching approaches and teaching practises, professional identities
and challenges. In addition, there is a growing awareness that
teaching English within discipline-specific contexts adds up to the
existing complexity. This awareness leads to reassessments,
discussions and suggestions on course design and content and
teaching approaches and techniques. In meeting expectations
teaching at a university specified in a particular discipline such as
engineering, English language educators are not only required to
teach students to be able to communicate in English effectively but
also to teach soft skills such as problem solving skills. This paper is
part of a research conducted to investigate how English language
educators negotiate with the complexities of teaching problem
solving skills through English language teaching at a technical
university. This paper reports the way an English language educator
identified himself and the way he approached his teaching in this
institutional context.