Abstract: In this paper, we propose a new approach to query-by-humming, focusing on MP3 songs database. Since MP3 songs are much more difficult in melody representation than symbolic performance data, we adopt to extract feature descriptors from the vocal sounds part of the songs. Our approach is based on signal filtering, sub-band spectral processing, MDCT coefficients analysis and peak energy detection by ignorance of the background music as much as possible. Finally, we apply dual dynamic programming algorithm for feature similarity matching. Experiments will show us its online performance in precision and efficiency.
Abstract: Dr Eliyahu Goldratt has done the pioneering work in
the development of Theory of Constraints. Since then, many more
researchers around the globe are working to enhance this body of
knowledge. In this paper, an attempt has been made to compile the
salient features of this theory from the work done by Goldratt and
other researchers. This paper will provide a good starting point to the
potential researchers interested to work in Theory of Constraints. The
paper will also help the practicing managers by clarifying their
concepts on the theory and will facilitate its successful
implementation in their working areas.
Abstract: A new digital transceiver circuit for asynchronous frame detection is proposed where both the transmitter and receiver contain all digital components, thereby avoiding possible use of conventional devices like monostable multivibrators with unstable external components such as resistances and capacitances. The proposed receiver circuit, in particular, uses a combinational logic block yielding an output which changes its state as soon as the start bit of a new frame is detected. This, in turn, helps in generating an efficient receiver sampling clock. A data latching circuit is also used in the receiver to latch the recovered data bits in any new frame. The proposed receiver structure is also extended from 4- bit information to any general n data bits within a frame with a common expression for the output of the combinational logic block. Performance of the proposed hardware design is evaluated in terms of time delay, reliability and robustness in comparison with the standard schemes using monostable multivibrators. It is observed from hardware implementation that the proposed circuit achieves almost 33 percent speed up over any conventional circuit.
Abstract: This paper presents a unified approach based graph
theory and system theory postulates for the modeling and analysis
of Simple open cycle Gas turbine system. In the present paper, the
simple open cycle gas turbine system has been modeled up to its subsystem
level and system variables have been identified to develop the
process subgraphs. The theorems and algorithms of the graph theory
have been used to represent behavioural properties of the system like
rate of heat and work transfers rates, pressure drops and temperature
drops in the involved processes of the system. The processes have
been represented as edges of the process subgraphs and their limits
as the vertices of the process subgraphs. The system across variables
and through variables has been used to develop terminal equations of
the process subgraphs of the system. The set of equations developed
for vertices and edges of network graph are used to solve the system
for its process variables.
Abstract: This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compares with earlier methods.
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: A finite element analysis (FEA) computer software HyperWorks is utilized in re-designing an automotive component to reduce its mass. Reduction of components mass contributes towards environmental sustainability by saving world-s valuable metal resources and by reducing carbon emission through improved overall vehicle fuel efficiency. A shape optimization analysis was performed on a rear spindle component. Pre-processing and solving procedures were performed using HyperMesh and RADIOSS respectively. Shape variables were defined using HyperMorph. Then optimization solver OptiStruct was utilized with fatigue life set as a design constraint. Since Stress-Number of Cycle (S-N) theory deals with uni-axial stress, the Signed von Misses stress on the component was used for looking up damage on S-N curve, and Gerber criterion for mean stress corrections. The optimization analysis resulted in mass reduction of 24% of the original mass. The study proved that the adopted approach has high potential use for environmental sustainability.
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: Despite the fact that B2c eCommerce has become
important in numerous economies, its adoption varies from country to
country. This paper aims to identify the factors affecting (enabling or
inhibiting) B2c eCommerce and to determine their quantitative
impact on the diffusion of online sales across countries. A dynamic
panel model analyzing the relationship between 13 factors
(Macroeconomic, Demographic, Socio-Cultural, Infrastructural and
Offer related) stemming from a complete literature analysis and the
B2c eCommerce value in 45 countries over 9 years has been
developed. Having a positive correlation coefficient, GDP, mobile
penetration, Internet user penetration and credit card penetration
resulted as enabling drivers of the B2c eCommerce value across
countries, whereas, having a negative correlation coefficient,equal
distribution of income and the development of traditional retailing
network act as inhibiting factors.
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: This paper studies the cultural creative industry's characteristics between the eastern and western of Zhejiang Province. Through the Comparative analysis, this paper works out that the cultural creative industry in western Zhejiang Province is mainly promoted by the inside force, and its level of development is obviously much lower than the eastern Zhejiang Province whose cultural creative industry is mainly pulled by outside forces. So this paper worked out some strategies for the development of cultural creative industry in western Zhejiang Province, which are based on the economic foundation and the cultural resource endowments. Finally these strategies will help to improve the whole development level of western Zhejiang Province, and contribute to the balance development between the west and east of Zhejiang Province.
Abstract: Time full of changes which is associated with globalization, tougher competition, changes in the structures of markets and economic downturn, that all force companies to think about their competitive advantages. These changes can bring the company a competitive advantage and that can help improve competitive position in the market. Policy of the European Union is focused on the fast growing innovative companies which quickly respond to market demands and consequently increase its competitiveness. To meet those objectives companies need the right conditions and support of their state.
Abstract: In the last few years, three multivariate spectral
analysis techniques namely, Principal Component Analysis (PCA),
Independent Component Analysis (ICA) and Non-negative Matrix
Factorization (NMF) have emerged as effective tools for oscillation
detection and isolation. While the first method is used in determining
the number of oscillatory sources, the latter two methods
are used to identify source signatures by formulating the detection
problem as a source identification problem in the spectral domain.
In this paper, we present a critical drawback of the underlying linear
(mixing) model which strongly limits the ability of the associated
source separation methods to determine the number of sources
and/or identify the physical source signatures. It is shown that the
assumed mixing model is only valid if each unit of the process gives
equal weighting (all-pass filter) to all oscillatory components in its
inputs. This is in contrast to the fact that each unit, in general, acts
as a filter with non-uniform frequency response. Thus, the model
can only facilitate correct identification of a source with a single
frequency component, which is again unrealistic. To overcome
this deficiency, an iterative post-processing algorithm that correctly
identifies the physical source(s) is developed. An additional issue
with the existing methods is that they lack a procedure to pre-screen
non-oscillatory/noisy measurements which obscure the identification
of oscillatory sources. In this regard, a pre-screening procedure
is prescribed based on the notion of sparseness index to eliminate
the noisy and non-oscillatory measurements from the data set used
for analysis.
Abstract: Knowing the geometrical object pose of products in manufacturing line before robot manipulation is required and less time consuming for overall shape measurement. In order to perform it, the information of shape representation and matching of objects is become required. Objects are compared with its descriptor that conceptually subtracted from each other to form scalar metric. When the metric value is smaller, the object is considered closed to each other. Rotating the object from static pose in some direction introduce the change of value in scalar metric value of boundary information after feature extraction of related object. In this paper, a proposal method for indexing technique for retrieval of 3D geometrical models based on similarity between boundaries shapes in order to measure 3D CAD object pose using object shape feature matching for Computer Aided Testing (CAT) system in production line is proposed. In experimental results shows the effectiveness of proposed method.
Abstract: Knowledge of patterns of genetic diversity enhances
the efficiency of germplasm conservation and improvement. In this
study 96 Iranian landraces of Triticum turgidum originating from
different geographical areas of Iran, along with 18 durum cultivars
from ten countries were evaluated for variation in morphological and
high molecular weight glutenin subunit (HMW-GS) composition.
The first two principal components clearly separated the Iranian
landraces from cultivars. Three alleles were present at the Glu-A1
locus and 11 alleles at Glu-B1. In both cultivars and landraces of
durum wheat, the null allele (Glu-A1c) was observed more
frequently than the Glu-A1a and Glu-A1b alleles. Two alleles,
namely Glu-B1a (subunit 7) and Glu-B1e (subunit 20) represented
the more frequent alleles at Glu-B1 locus. The results showed that
the evaluated Iranian landraces formed an interesting source of
favourable glutenin subunits that might be very desirable in breeding
activities for improving pasta-making quality.
Abstract: Cloud Computing (CC) has become one of the most
talked about emerging technologies that provides powerful
computing and large storage environments through the use of the
Internet. Cloud computing provides different dynamically scalable
computing resources as a service. It brings economic benefits to
individuals and businesses that adopt the technology. In theory
adoption of cloud computing reduces capital and operational
expenditure on information technology. For this to be a reality there
is need to solve some challenges and at the same time addressing
concerns that consumers have about cloud computing. This paper
looks at Cloud Computing in general then highlights the challenges
of Cloud Computing and finally suggests solutions to some of the
challenges.
Abstract: Stuck-pipe in drilling operations is one of the most
pressing and expensive problems in the oil industry. This paper
describes a computational simulation and an experimental study of
the hydrodynamic vibrator, which may be used for liquidation of
stuck-pipe problems during well drilling. The work principle of the
vibrator is based upon the known phenomena of Vortex Street of
Karman and the resulting generation of vibrations. We will discuss
the computational simulation and experimental investigations of
vibrations in this device. The frequency of the vibration parameters
has been measured as a function of the wide range Reynolds Number.
The validity of the computational simulation and of the assumptions
on which it is based has been proved experimentally. The
computational simulation of the vibrator work and its effectiveness
was carried out using FLUENT software. The research showed high
degree of congruence with the results of the laboratory tests and
allowed to determine the effect of the granular material features upon
the pipe vibration in the well. This study demonstrates the potential
of using the hydrodynamic vibrator in a well drilling system.
Abstract: The increasing influence of traffic on building
objects and people residing in them should be taken into account in
diagnosis and design. Users of buildings expect that vibrations
occurring in their environment, will not only lead to damage to the
building or its accelerated wear, but neither would affect the required
comfort in rooms designed to accommodate people. This article
describes the methods and principles useful in designing and building
diagnostics located near transportation routes, with particular
emphasis on the impact of traffic vibration on people in buildings. It
also describes the procedures used in obtaining information about the
parameters of vibrations in different cases of diagnostics and design.
A universal algorithm of procedure in diagnostics and design of
buildings taking into account assurance of human vibration comfort
of people residing in the these buildings was presented.
Abstract: In this paper we propose a novel approach for
searching eCommerce products using a mobile phone, illustrated by a
prototype eCoMobile. This approach aims to globalize the mobile
search by integrating the concept of user multilinguism into it. To
show that, we particularly deal with English and Arabic languages.
Indeed the mobile user can formulate his query on a commercial
product in either language (English/Arabic). The description of his
information need on commercial products relies on the ontology that
represents the conceptualization of the product catalogue knowledge
domain defined in both English and Arabic languages. A query
expressed on a mobile device client defines the concept that
corresponds to the name of the product followed by a set of pairs
(property, value) specifying the characteristics of the product. Once a
query is submitted it is then communicated to the server side which
analyses it and in its turn performs an http request to an eCommerce
application server (like Amazon). This latter responds by returning
an XML file representing a set of elements where each element
defines an item of the searched product with its specific
characteristics. The XML file is analyzed on the server side and then
items are displayed on the mobile device client along with its
relevant characteristics in the chosen language.
Abstract: The NGN (Next Generation Network), which can
provide advanced multimedia services over an all-IP based network, has been the subject of much attention for years. While there have
been tremendous efforts to develop its architecture and protocols, especially for IMS, which is a key technology of the NGN, it is far
from being widely deployed. However, efforts to create an advanced
signaling infrastructure realizing many requirements have resulted in a
large number of functional components and interactions between those
components. Thus, the carriers are trying to explore effective ways to
deploy IMS while offering value-added services. As one such
approach, we have proposed a self-organizing IMS. A self-organizing
IMS enables IMS functional components and corresponding physical
nodes to adapt dynamically and automatically based on situation such
as network load and available system resources while continuing IMS
operation. To realize this, service continuity for users is an important
requirement when a reconfiguration occurs during operation. In this
paper, we propose a mechanism that will provide service continuity to
users and focus on the implementation and describe performance
evaluation in terms of number of control signaling and processing time
during reconfiguration