Abstract: Automated operations based on voice commands will become more and more important in many applications, including robotics, maintenance operations, etc. However, voice command recognition rates drop quite a lot under non-stationary and chaotic noise environments. In this paper, we tried to significantly improve the speech recognition rates under non-stationary noise environments. First, 298 Navy acronyms have been selected for automatic speech recognition. Data sets were collected under 4 types of noisy environments: factory, buccaneer jet, babble noise in a canteen, and destroyer. Within each noisy environment, 4 levels (5 dB, 15 dB, 25 dB, and clean) of Signal-to-Noise Ratio (SNR) were introduced to corrupt the speech. Second, a new algorithm to estimate speech or no speech regions has been developed, implemented, and evaluated. Third, extensive simulations were carried out. It was found that the combination of the new algorithm, the proper selection of language model and a customized training of the speech recognizer based on clean speech yielded very high recognition rates, which are between 80% and 90% for the four different noisy conditions. Fourth, extensive comparative studies have also been carried out.
Abstract: This experiment was conducted to investigate the
effect of dietary supplementation of different levels of black seed
(Nigella sativa L.) on the performance and immune response of broiler chicks. A total 240 day-old broiler chicks were used and
randomly allotted equally into six experimental groups designated as 1, 2, 3, 4, 5 and 6 having black seed at the rate of 0, 2, 4, 6, 8 and
10 g /kg diet respectively. The study was lasted for 42 days. Average body weight, weight gain, relative growth rate, feed
conversion, antibody titer against Newcastle disease, phagocytic activity and phagocytic index, some blood parameters(GOT, GPT,
Glucose, Cholesterol, Triglyceride, Total protein, Albumen, WBCs,
RBCs, Hb and PCV), dressing percentage, weight of different body
organs, abdominal fat weight, were determined. It was found that, N. Sativa significantly improved final body weight, total body gain
and feed conversion ratio of groups 2 and 3 when compared with the control group. Higher levels of N. Sativa did not improve
growth performance of the chicks. Non significant differences were
observed for antibody titer against Newcastle virus, WBCs count,
serum GOT, glucose level, dressing %, relative liver, spleen, heart and head percentages. Lymphoid organs (Bursa and Thymus)
improved significantly with increasing N. Sativa level in all supplemented groups. Serum cholesterol, triglyceride and visible fat
% significantly decreased with Nigella sativa supplementation while
serum GPT level significantly increased with nigella sativa
supplementation.
Abstract: Problem solving has traditionally been one of the principal research areas for artificial intelligence. Yet, although artificial intelligence reasoning techniques have been employed in several product support systems, the benefit of integrating product support, knowledge engineering, and problem solving, is still unclear. This paper studies the synergy of these areas and proposes a knowledge engineering framework that integrates product support systems and artificial intelligence techniques. The framework includes four spaces; the data, problem, hypothesis, and solution ones. The data space incorporates the knowledge needed for structured reasoning to take place, the problem space contains representations of problems, and the hypothesis space utilizes a multimodal reasoning approach to produce appropriate solutions in the form of virtual documents. The solution space is used as the gateway between the system and the user. The proposed framework enables the development of product support systems in terms of smaller, more manageable steps while the combination of different reasoning techniques provides a way to overcome the lack of documentation resources.
Abstract: Synthetic juice clarification was done through spiral
wound ultrafiltration (UF) membrane module. Synthetic juice was
clarified at two different operating conditions, such as, with and
without permeates recycle at turbulent flow regime. The performance
of spiral wound ultrafiltration membrane was analyzed during
clarification of synthetic juice. Synthetic juice was the mixture of
deionized water, sucrose and pectin molecule. The operating
conditions are: feed flowrate of 10 lpm, pressure drop of 413.7 kPa
and Reynolds no of 5000. Permeate sample was analyzed in terms of
volume reduction factor (VRF), viscosity (Pa.s), ⁰Brix, TDS (mg/l),
electrical conductivity (μS) and turbidity (NTU). It was observe that
the permeate flux declined with operating time for both conditions of
with and without permeate recycle due to increase of concentration
polarization and increase of gel layer on membrane surface. For
without permeate recycle, the membrane fouling rate was faster
compared to with permeate recycle. For without permeate recycle,
the VRF rose up to 5 and for with recycle permeate the VRF is 1.9.
The VRF is higher due to adsorption of solute (pectin) molecule on
membrane surface and resulting permeateflux declined with VRF.
With permeate recycle, quality was within acceptable limit. Fouled
membrane was cleaned by applying different processes (e.g.,
deionized water, SDS and EDTA solution). Membrane cleaning was
analyzed in terms of permeability recovery.
Abstract: Business Process Modeling (BPM) is the first and
most important step in business process management lifecycle. Graph
based formalism and rule based formalism are the two most
predominant formalisms on which process modeling languages are
developed. BPM technology continues to face challenges in coping
with dynamic business environments where requirements and goals
are constantly changing at the execution time. Graph based
formalisms incur problems to react to dynamic changes in Business
Process (BP) at the runtime instances. In this research, an adaptive
and flexible framework based on the integration between Object
Oriented diagramming technique and Petri Net modeling language is
proposed in order to support change management techniques for
BPM and increase the representation capability for Object Oriented
modeling for the dynamic changes in the runtime instances. The
proposed framework is applied in a higher education environment to
achieve flexible, updatable and dynamic BP.
Abstract: Wavelet neural networks (WNNs) have emerged as a vital alternative to the vastly studied multilayer perceptrons (MLPs) since its first implementation. In this paper, we applied various clustering algorithms, namely, K-means (KM), Fuzzy C-means (FCM), symmetry-based K-means (SBKM), symmetry-based Fuzzy C-means (SBFCM) and modified point symmetry-based K-means (MPKM) clustering algorithms in choosing the translation parameter of a WNN. These modified WNNs are further applied to the heterogeneous cancer classification using benchmark microarray data and were compared against the conventional WNN with random initialization method. Experimental results showed that a WNN classifier with the MPKM algorithm is more precise than the conventional WNN as well as the WNNs with other clustering algorithms.
Abstract: In the present work, we introduce the particle swarm optimization called (PSO in short) to avoid the Runge-s phenomenon occurring in many numerical problems. This new approach is tested with some numerical examples including the generalized integral quadrature method in order to solve the Volterra-s integral equations
Abstract: The Euler-s equation of motion is extended to include
the viscosity stress tensor leading to the formulation of Navier–
Stokes type equation. The latter is linearized and applied to
investigate the rotational motion or vorticity in a viscous fluid.
Relations for the velocity of viscous waves and attenuation parameter
are obtained in terms of viscosity (μ) and the density (¤ü) of the fluid.
μ and ¤ü are measured experimentally as a function of temperature for
two different samples of light and heavy crude oil. These data
facilitated to determine the activation energy, velocity of viscous
wave and the attenuation parameter. Shear wave velocity in heavy oil
is found to be much larger than the light oil, whereas the attenuation
parameter in heavy oil is quite low in comparison to light one. The
activation energy of heavy oil is three times larger than light oil.
Abstract: Smart Grids employ wireless sensor networks for
their control and monitoring. Sensors are characterized by limitations
in the processing power, energy supply and memory spaces, which
require a particular attention on the design of routing and data
management algorithms.
Since most routing algorithms for sensor networks, focus on
finding energy efficient paths to prolong the lifetime of sensor
networks, the power of sensors on efficient paths depletes quickly,
and consequently sensor networks become incapable of monitoring
events from some parts of their target areas. In consequence, the
design of routing protocols should consider not only energy
efficiency paths, but also energy efficient algorithms in general.
In this paper we propose an energy efficient routing protocol for
wireless sensor networks without the support of any location
information system. The reliability and the efficiency of this protocol
have been demonstrated by simulation studies where we compare
them to the legacy protocols. Our simulation results show that these
algorithms scale well with network size and density.
Abstract: Understanding the cell's large-scale organization is an interesting task in computational biology. Thus, protein-protein interactions can reveal important organization and function of the cell. Here, we investigated the correspondence between protein interactions and function for the yeast. We obtained the correlations among the set of proteins. Then these correlations are clustered using both the hierarchical and biclustering methods. The detailed analyses of proteins in each cluster were carried out by making use of their functional annotations. As a result, we found that some functional classes appear together in almost all biclusters. On the other hand, in hierarchical clustering, the dominancy of one functional class is observed. In the light of the clustering data, we have verified some interactions which were not identified as core interactions in DIP and also, we have characterized some functionally unknown proteins according to the interaction data and functional correlation. In brief, from interaction data to function, some correlated results are noticed about the relationship between interaction and function which might give clues about the organization of the proteins, also to predict new interactions and to characterize functions of unknown proteins.
Abstract: This paper reports a new approach on identifying the
individuality of persons by using parametric classification of multiple
mental thoughts. In the approach, electroencephalogram (EEG)
signals were recorded when the subjects were thinking of one or
more (up to five) mental thoughts. Autoregressive features were
computed from these EEG signals and classified by Linear
Discriminant classifier. The results here indicate that near perfect
identification of 400 test EEG patterns from four subjects was
possible, thereby opening up a new avenue in biometrics.
Abstract: The Model for Knowledge Base of Computational Objects
(KBCO model) has been successfully applied to represent the
knowledge of human like Plane Geometry, Physical, Calculus. However,
the original model cannot easyly apply in inorganic chemistry
field because of the knowledge specific problems. So, the aim of
this article is to introduce how we extend the Computional Object
(Com-Object) in KBCO model, kinds of fact, problems model, and
inference algorithms to develop a program for solving problems
in inorganic chemistry. Our purpose is to develop the application
that can help students in their study inorganic chemistry at schools.
This application was built successful by using Maple, C# and WPF
technology. It can solve automatically problems and give human
readable solution agree with those writting by students and teachers.
Abstract: Knowledge of an organization does not merely reside
in structured form of information and data; it is also embedded in
unstructured form. The discovery of such knowledge is particularly
difficult as the characteristic is dynamic, scattered, massive and
multiplying at high speed. Conventional methods of managing
unstructured information are considered too resource demanding and
time consuming to cope with the rapid information growth.
In this paper, a Multi-faceted and Automatic Knowledge
Elicitation System (MAKES) is introduced for the purpose of
discovery and capture of organizational knowledge. A trial
implementation has been conducted in a public organization to
achieve the objective of decision capture and navigation from a
number of meeting minutes which are autonomously organized,
classified and presented in a multi-faceted taxonomy map in both
document and content level. Key concepts such as critical decision
made, key knowledge workers, knowledge flow and the relationship
among them are elicited and displayed in predefined knowledge
model and maps. Hence, the structured knowledge can be retained,
shared and reused.
Conducting Knowledge Management with MAKES reduces work
in searching and retrieving the target decision, saves a great deal of
time and manpower, and also enables an organization to keep pace
with the knowledge life cycle. This is particularly important when
the amount of unstructured information and data grows extremely
quickly. This system approach of knowledge management can
accelerate value extraction and creation cycles of organizations.
Abstract: Symbolic Circuit Analysis (SCA) is a technique used
to generate the symbolic expression of a network. It has become a
well-established technique in circuit analysis and design. The
symbolic expression of networks offers excellent way to perform
frequency response analysis, sensitivity computation, stability
measurements, performance optimization, and fault diagnosis. Many
approaches have been proposed in the area of SCA offering different
features and capabilities. Numerical Interpolation methods are very
common in this context, especially by using the Fast Fourier
Transform (FFT). The aim of this paper is to present a method for
SCA that depends on the use of Wavelet Transform (WT) as a
mathematical tool to generate the symbolic expression for large
circuits with minimizing the analysis time by reducing the number of
computations.
Abstract: This paper considers the control of the longitudinal
flight dynamics of an F-16 aircraft. The primary design objective
is model-following of the pitch rate q, which is the preferred
system for aircraft approach and landing. Regulation of the aircraft
velocity V (or the Mach-hold autopilot) is also considered, but
as a secondary objective. The problem is challenging because the
system is nonlinear, and also non-affine in the input. A sliding
mode controller is designed for the pitch rate, that exploits the
modal decomposition of the linearized dynamics into its short-period
and phugoid approximations. The inherent robustness of the SMC
design provides a convenient way to design controllers without gain
scheduling, with a steady-state response that is comparable to that
of a conventional polynomial based gain-scheduled approach with
integral control, but with improved transient performance. Integral
action is introduced in the sliding mode design using the recently
developed technique of “conditional integrators", and it is shown that
robust regulation is achieved with asymptotically constant exogenous
signals, without degrading the transient response. Through extensive
simulation on the nonlinear multiple-input multiple-output (MIMO)
longitudinal model of the F-16 aircraft, it is shown that the conditional
integrator design outperforms the one based on the conventional linear
control, without requiring any scheduling.
Abstract: This paper is a numerical investigation of a laminar
isothermal plane two dimensional wall jet. Special attention has been
paid to the effect of the inlet conditions at the nozzle exit on the
hydrodynamic and thermal characteristics of the flow. The
behaviour of various fluids evolving in both forced and mixed
convection regimes near a vertical plate plane is carried out. The
system of governing equations is solved with an implicit finite
difference scheme. For numerical stability we use a staggered non
uniform grid. The obtained results show that the effect of the Prandtl
number is significant in the plume region in which the jet flow is
governed by buoyant forces. Further for ascending X values, the
buoyancy forces become dominating, and a certain agreement
between the temperature profiles are observed, which shows that the
velocity profile has no longer influence on the wall temperature
evolution in this region. Fluids with low Prandtl number warm up
more importantly, because for such fluids the effect of heat diffusion
is higher.
Abstract: Missing data is a persistent problem in almost all
areas of empirical research. The missing data must be treated very
carefully, as data plays a fundamental role in every analysis.
Improper treatment can distort the analysis or generate biased results.
In this paper, we compare and contrast various imputation techniques
on missing data sets and make an empirical evaluation of these
methods so as to construct quality software models. Our empirical
study is based on NASA-s two public dataset. KC4 and KC1. The
actual data sets of 125 cases and 2107 cases respectively, without
any missing values were considered. The data set is used to create
Missing at Random (MAR) data Listwise Deletion(LD), Mean
Substitution(MS), Interpolation, Regression with an error term and
Expectation-Maximization (EM) approaches were used to compare
the effects of the various techniques.
Abstract: As computer network technology becomes
increasingly complex, it becomes necessary to place greater
requirements on the validity of developing standards and the
resulting technology. Communication networks are based on large
amounts of protocols. The validity of these protocols have to be
proved either individually or in an integral fashion. One strategy for
achieving this is to apply the growing field of formal methods.
Formal methods research defines systems in high order logic so that
automated reasoning can be applied for verification. In this research
we represent and implement a formerly announced multicast protocol
in Prolog language so that certain properties of the protocol can be
verified. It is shown that by using this approach some minor faults in
the protocol were found and repaired. Describing the protocol as
facts and rules also have other benefits i.e. leads to a process-able
knowledge. This knowledge can be transferred as ontology between
systems in KQML format. Since the Prolog language can increase its
knowledge base every time, this method can also be used to learn an
intelligent network.
Abstract: ZnO nanostructures including nanowires, nanorods,
and nanoneedles were successfully deposited on GaAs substrates,
respectively, by simple two-step chemical method for the first time. A
ZnO seed layer was firstly pre-coated on the O2-plasma treated
substrate by sol-gel process, followed by the nucleation of ZnO
nanostructures through hydrothermal synthesis. Nanostructures with
different average diameter (15-250 nm), length (0.9-1.8 μm), density
(0.9-16×109 cm-2) were obtained via adjusting the growth time and
concentration of precursors. From the reflectivity spectra, we
concluded ordered and taper nanostructures were preferential for
photovoltaic applications. ZnO nanoneedles with an average diameter
of 106 nm, a moderate length of 2.4 μm, and the density of 7.2×109
cm-2 could be synthesized in the concentration of 0.04 M for 18 h.
Integrated with the nanoneedle array, the power conversion efficiency
of single junction solar cell was increased from 7.3 to 12.2%,
corresponding to a 67% improvement.
Abstract: Nanocrystalline thin film of Na0.1V2O5.nH2O xerogel
obtained by sol gel synthesis was used as gas sensor. Gas sensing
properties of different gases such as hydrogen, petroleum and
humidity were investigated. Applying XRD and TEM the size of the
nanocrystals is found to be 7.5 nm. SEM shows a highly porous
structure with submicron meter-sized voids present throughout the
sample. FTIR measurement shows different chemical groups
identifying the obtained series of gels. The sample was n-type
semiconductor according to the thermoelectric power and electrical
conductivity. It can be seen that the sensor response curves from
130oC to 150oC show a rapid increase in sensitivity for all types of
gas injection, low response values for heating period and the rapid
high response values for cooling period. This result may suggest that
this material is able to act as gas sensor during the heating and
cooling process.