Abstract: Recently, the issue of machine condition monitoring
and fault diagnosis as a part of maintenance system became global
due to the potential advantages to be gained from reduced
maintenance costs, improved productivity and increased machine
availability. The aim of this work is to investigate the effectiveness
of a new fault diagnosis method based on power spectral density
(PSD) of vibration signals in combination with decision trees and
fuzzy inference system (FIS). To this end, a series of studies was
conducted on an external gear hydraulic pump. After a test under
normal condition, a number of different machine defect conditions
were introduced for three working levels of pump speed (1000, 1500,
and 2000 rpm), corresponding to (i) Journal-bearing with inner face
wear (BIFW), (ii) Gear with tooth face wear (GTFW), and (iii)
Journal-bearing with inner face wear plus Gear with tooth face wear
(B&GW). The features of PSD values of vibration signal were
extracted using descriptive statistical parameters. J48 algorithm is
used as a feature selection procedure to select pertinent features from
data set. The output of J48 algorithm was employed to produce the
crisp if-then rule and membership function sets. The structure of FIS
classifier was then defined based on the crisp sets. In order to
evaluate the proposed PSD-J48-FIS model, the data sets obtained
from vibration signals of the pump were used. Results showed that
the total classification accuracy for 1000, 1500, and 2000 rpm
conditions were 96.42%, 100%, and 96.42% respectively. The results
indicate that the combined PSD-J48-FIS model has the potential for
fault diagnosis of hydraulic pumps.
Abstract: A word recognition architecture based on a network
of neural associative memories and hidden Markov models has been
developed. The input stream, composed of subword-units like wordinternal
triphones consisting of diphones and triphones, is provided
to the network of neural associative memories by hidden Markov
models. The word recognition network derives words from this input
stream. The architecture has the ability to handle ambiguities on
subword-unit level and is also able to add new words to the
vocabulary during performance. The architecture is implemented to
perform the word recognition task in a language processing system
for understanding simple command sentences like “bot show apple".
Abstract: The purpose of this research is to increase our
knowledge as regards how Small-and-Medium-Sized Enterprises
(SMEs) tackle ERP implementation projects to achieve successful
adoption and use of these systems within the organization. SMEs
have scare resources to handle these kinds of projects which have
proved to be risky and costly. There are several studies focusing on
ERP implementation in larger companies, however, few studies
report on challenges experienced by SMEs. Our research seeks to
bridge this gap. Through a multiple case study of four companies, we
identified challenges and critical elements within the different phases
(pre-implementation, implementation and post-implementation) of
the ERP life cycle. To interpret our findings, we utilize a well-know
ERP life cycle model and critical success factors developed for larger
companies which are reported in former research literature. We
discuss if these models are relevant for SMEs and suggest additional
critical elements identified in this study to make a framework more
adapted to the SME context.
Abstract: This study aimed at developing a forecasting model on the number of Dengue Haemorrhagic Fever (DHF) incidence in Northern Thailand using time series analysis. We developed Seasonal Autoregressive Integrated Moving Average (SARIMA) models on the data collected between 2003-2006 and then validated the models using the data collected between January-September 2007. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The most suitable model was the SARIMA(2,0,1)(0,2,0)12 model with a Akaike Information Criterion (AIC) of 12.2931 and a Mean Absolute Percent Error (MAPE) of 8.91713. The SARIMA(2,0,1)(0,2,0)12 model fitting was adequate for the data with the Portmanteau statistic Q20 = 8.98644 ( x20,95= 27.5871, P>0.05). This indicated that there was no significant autocorrelation between residuals at different lag times in the SARIMA(2,0,1)(0,2,0)12 model.
Abstract: Distributed Power generation has gained a lot of
attention in recent times due to constraints associated with
conventional power generation and new advancements in DG
technologies .The need to operate the power system economically
and with optimum levels of reliability has further led to an increase
in interest in Distributed Generation. However it is important to place
Distributed Generator on an optimum location so that the purpose of
loss minimization and voltage regulation is dully served on the
feeder. This paper investigates the impact of DG units installation on
electric losses, reliability and voltage profile of distribution networks.
In this paper, our aim would be to find optimal distributed
generation allocation for loss reduction subjected to constraint of
voltage regulation in distribution network. The system is further
analyzed for increased levels of Reliability. Distributed Generator
offers the additional advantage of increase in reliability levels as
suggested by the improvements in various reliability indices such as
SAIDI, CAIDI and AENS. Comparative studies are performed and
related results are addressed. An analytical technique is used in order
to find the optimal location of Distributed Generator. The suggested
technique is programmed under MATLAB software. The results
clearly indicate that DG can reduce the electrical line loss while
simultaneously improving the reliability of the system.
Abstract: Saccharomyces cerevisiae (baker-s yeast) can exhibit
sustained oscillations during the operation in a continuous bioreactor
that adversely affects its stability and productivity. Because of
heterogeneous nature of cell populations, the cell population balance
models can be used to capture the dynamic behavior of such cultures.
In this paper an unstructured, segregated model is used which is
based on population balance equation(PBE) and then in order to
simulation, the 4th order Rung-Kutta is used for time dimension and
three methods, finite difference, orthogonal collocation on finite
elements and Galerkin finite element are used for discretization of the
cell mass domain. The results indicate that the orthogonal collocation
on finite element not only is able to predict the oscillating behavior of
the cell culture but also needs much little time for calculations.
Therefore this method is preferred in comparison with other methods.
In the next step two controllers, a globally linearizing control (GLC)
and a conventional proportional-integral (PI) controller are designed
for controlling the total cell mass per unit volume, and performances
of these controllers are compared through simulation. The results
show that although the PI controller has simpler structure, the GLC
has better performance.
Abstract: In the paper the research of flat textile products for use
as electrodes was presented. Material-s resistance measurements were
carried out to determine the suitability of the textiles. Based on the received results of studies different types of textile electrodes were
designed. Textile electrodes tests were carried out on human
phantoms. The electro-conductive properties of human forearm
phantom were also described. Based on this results special electroconductive
hydrogels with electro-conductive particles were feasible. The hydrogel is an important element of the forearm-s phantom
model of a survey of electrodes for muscle electrostimulation. The
hydrogel is an equivalent human skin and tissue. The hydrogel should
have a permanence and recurrence of the electro-conductive properties.
Abstract: To measure the thickness of the subcutaneous adipose
tissue layer, a non-invasive optical measurement system (λ=1300 nm)
is introduced. Animal and human subjects are used for the
experiments. The results of human subjects are compared with the data
of ultrasound device measurements, and a high correlation (r=0.94 for
n=11) is observed. There are two modes in the corresponding signals
measured by the optical system, which can be explained by
two-layered and three-layered tissue models. If the target tissue is
thinner than the critical thickness, detected data using diffuse
reflectance method follow the three-layered tissue model, so the data
increase as the thickness increases. On the other hand, if the target
tissue is thicker than the critical thickness, the data follow the
two-layered tissue model, so they decrease as the thickness increases.
Abstract: A zero dimensional model has been used to investigate
the combustion performance of a single cylinder direct injection
diesel engine fueled by biofuels with options like supercharging and
exhaust gas recirculation. The numerical simulation was performed at
constant speed. The indicated pressure, temperature diagrams are
plotted and compared for different fuels. The emissions of soot and
nitrous oxide are computed with phenomenological models. The
experimental work was also carried out with biodiesel (palm stearin
methyl ester) diesel blends, ethanol diesel blends to validate
simulation results with experimental results, and observed that the
present model is successful in predicting the engine performance with
biofuels.
Abstract: People from different cultures favor web pages
characterized by the values of their culture and, therefore, tend to
prefer different characteristics of a website according to their cultural
values in terms of navigation, security, product information, customer
service, shopping and design tools. For a company aiming to
globalize its market it is useful to implement country specific cultural
interfaces and different web sites for countries with different cultures.
This paper, following the conclusions proposed by two models of
Hall and Hofstede, and the studies of Marcus and Gould, defines,
through an empirical analysis, the guidelines of web design for both
the Scandinavian countries and Malaysia.
Abstract: Evaluation of contact pressure, surface and
subsurface contact stresses are essential to know the functional
response of surface coatings and the contact behavior mainly depends
on surface roughness, material property, thickness of layer and the
manner of loading. Contact parameter evaluation of real rough
surface contacts mostly relies on statistical single asperity contact
approaches. In this work, a three dimensional layered solid rough
surface in contact with a rigid flat is modeled and analyzed using
finite element method. The rough surface of layered solid is
generated by FFT approach. The generated rough surface is exported
to a finite element method based ANSYS package through which the
bottom up solid modeling is employed to create a deformable solid
model with a layered solid rough surface on top. The discretization
and contact analysis are carried by using the same ANSYS package.
The elastic, elastoplastic and plastic deformations are continuous in
the present finite element method unlike many other contact models.
The Young-s modulus to yield strength ratio of layer is varied in the
present work to observe the contact parameters effect while keeping
the surface roughness and substrate material properties as constant.
The contacting asperities attain elastic, elastoplastic and plastic states
with their continuity and asperity interaction phenomena is inherently
included. The resultant contact parameters show that neighboring
asperity interaction and the Young-s modulus to yield strength ratio
of layer influence the bulk deformation consequently affect the
interface strength.
Abstract: This paper describes a prototype aircraft that can fly
slowly, safely and transmit wireless video for tasks like reconnaissance,
surveillance and target acquisition. The aircraft is designed to
fly in closed quarters like forests, buildings, caves and tunnels which
are often spacious but GPS reception is poor. Envisioned is that a
small, safe and slow flying vehicle can assist in performing dull,
dangerous and dirty tasks like disaster mitigation, search-and-rescue
and structural damage assessment.
Abstract: The purpose of this study was to investigate effects of
modality and redundancy principles on music theory learning among
pupils of different anxiety levels. The lesson of music theory was
developed in three different modes, audio and image (AI), text with
image (TI) and audio with image and text (AIT). The independent
variables were the three modes of courseware. The moderator
variable was the anxiety level, while the dependent variable was the
post test score. The study sample consisted of 405 third-grade pupils.
Descriptive and inferential statistics were conducted to analyze the
collected data. Analyses of covariance (ANCOVA) and Post hoc
were carried out to examine the main effects as well as the
interaction effects of the independent variables on the dependent
variable. The findings of this study showed that medium anxiety
pupils performed significantly better than low and high anxiety
pupils in all the three treatment modes. The AI mode was found to
help pupils with high anxiety significantly more than the TI and AIT
modes.
Abstract: Market based models are frequently used in the resource
allocation on the computational grid. However, as the size of
the grid grows, it becomes difficult for the customer to negotiate
directly with all the providers. Middle agents are introduced to
mediate between the providers and customers and facilitate the
resource allocation process. The most frequently deployed middle
agents are the matchmakers and the brokers. The matchmaking agent
finds possible candidate providers who can satisfy the requirements
of the consumers, after which the customer directly negotiates with
the candidates. The broker agents are mediating the negotiation with
the providers in real time.
In this paper we present a new type of middle agent, the marketmaker.
Its operation is based on two parallel operations - through
the investment process the marketmaker is acquiring resources and
resource reservations in large quantities, while through the resale process
it sells them to the customers. The operation of the marketmaker
is based on the fact that through its global view of the grid it can
perform a more efficient resource allocation than the one possible in
one-to-one negotiations between the customers and providers.
We present the operation and algorithms governing the operation
of the marketmaker agent, contrasting it with the matchmaker and
broker agents. Through a series of simulations in the task oriented
domain we compare the operation of the three agents types. We find
that the use of marketmaker agent leads to a better performance in the
allocation of large tasks and a significant reduction of the messaging
overhead.
Abstract: This paper describes new computer vision algorithms
that have been developed to track moving objects as part of a
long-term study into the design of (semi-)autonomous vehicles. We
present the results of a study to exploit variable kernels for tracking in
video sequences. The basis of our work is the mean shift
object-tracking algorithm; for a moving target, it is usual to define a
rectangular target window in an initial frame, and then process the data
within that window to separate the tracked object from the background
by the mean shift segmentation algorithm. Rather than use the
standard, Epanechnikov kernel, we have used a kernel weighted by the
Chamfer distance transform to improve the accuracy of target
representation and localization, minimising the distance between the
two distributions in RGB color space using the Bhattacharyya
coefficient. Experimental results show the improved tracking
capability and versatility of the algorithm in comparison with results
using the standard kernel. These algorithms are incorporated as part of
a robot test-bed architecture which has been used to demonstrate their
effectiveness.
Abstract: Model-based approaches have been applied successfully
to a wide range of tasks such as specification, simulation, testing, and
diagnosis. But one bottleneck often prevents the introduction of these
ideas: Manual modeling is a non-trivial, time-consuming task.
Automatically deriving models by observing and analyzing running
systems is one possible way to amend this bottleneck. To
derive a model automatically, some a-priori knowledge about the
model structure–i.e. about the system–must exist. Such a model
formalism would be used as follows: (i) By observing the network
traffic, a model of the long-term system behavior could be generated
automatically, (ii) Test vectors can be generated from the model,
(iii) While the system is running, the model could be used to diagnose
non-normal system behavior.
The main contribution of this paper is the introduction of a model
formalism called 'probabilistic regression automaton' suitable for the
tasks mentioned above.
Abstract: An integrated Artificial Neural Network- Particle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world-s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World-s population, Gross domestic product (GDP), oil trade movement and natural gas trade movement are used as socio-economic indicators in this study. For each socio-economic indicator, a feed-forward back propagation artificial neural network is trained and projected for future time domain. STEP 2: in the second step, global electricity consumption is projected based on the oil, natural gas, coal and primary energy consumption using PSO. global electricity consumption is forecasted up to year 2040.
Abstract: The paper describes the evaluation of quality of
control for cases of controlled non-minimal phase plants. Control
circuits containing non-minimal phase plants have different
properties, they manifest reversed reaction at the beginning of unit
step response. For these types of plants are developed special
criterion of quality of control, which considers the difference and can
be helpful for synthesis of optimal controller tuning. All results are
clearly presented using Matlab/Simulink models.
Abstract: The fuzzy technique is an operator introduced in order
to simulate at a mathematical level the compensatory behavior in
process of decision making or subjective evaluation. The following
paper introduces such operators on hand of computer vision
application.
In this paper a novel method based on fuzzy logic reasoning
strategy is proposed for edge detection in digital images without
determining the threshold value. The proposed approach begins by
segmenting the images into regions using floating 3x3 binary matrix.
The edge pixels are mapped to a range of values distinct from each
other. The robustness of the proposed method results for different
captured images are compared to those obtained with the linear Sobel
operator. It is gave a permanent effect in the lines smoothness and
straightness for the straight lines and good roundness for the curved
lines. In the same time the corners get sharper and can be defined
easily.
Abstract: This article describes design of the 8-bit asynchronous
microcontroller simulation model in VHDL. The model is created in
ISE Foundation design tool and simulated in Modelsim tool. This
model is a simple application example of asynchronous systems
designed in synchronous design tools. The design process of creating
asynchronous system with 4-phase bundled-data protocol and with
matching delays is described in the article. The model is described in
gate-level abstraction.
The simulation waveform of the functional construction is the
result of this article. Described construction covers only the
simulation model. The next step would be creating synthesizable
model to FPGA.