Abstract: The uses of road map in daily activities are numerous
but it is a hassle to construct and update a road map whenever there
are changes. In Universiti Malaysia Sarawak, research on Automatic
Road Extraction (ARE) was explored to solve the difficulties in
updating road map. The research started with using Satellite Image
(SI), or in short, the ARE-SI project. A Hybrid Simple Colour Space
Segmentation & Edge Detection (Hybrid SCSS-EDGE) algorithm
was developed to extract roads automatically from satellite-taken
images. In order to extract the road network accurately, the satellite
image must be analyzed prior to the extraction process. The
characteristics of these elements are analyzed and consequently the
relationships among them are determined. In this study, the road
regions are extracted based on colour space elements and edge details
of roads. Besides, edge detection method is applied to further filter
out the non-road regions. The extracted road regions are validated by
using a segmentation method. These results are valuable for building
road map and detecting the changes of the existing road database.
The proposed Hybrid Simple Colour Space Segmentation and Edge
Detection (Hybrid SCSS-EDGE) algorithm can perform the tasks
fully automatic, where the user only needs to input a high-resolution
satellite image and wait for the result. Moreover, this system can
work on complex road network and generate the extraction result in
seconds.
Abstract: Natural gas flow contains undesirable solid particles,
liquid condensation, and/or oil droplets and requires reliable
removing equipment to perform filtration. Recent natural gas
processing applications are demanded compactness and reliability of
process equipment. Since conventional means are sophisticated in
design, poor in efficiency, and continue lacking robust, a supersonic
nozzle has been introduced as an alternative means to meet such
demands.
A 3-D Convergent-Divergent Nozzle is simulated using
commercial Code for pressure ratio (NPR) varies from 1.2 to 2. Six
different shapes of nozzle are numerically examined to illustrate the
position of shock-wave as such spot could be considered as a
benchmark of particle separation. Rectangle, triangle, circular,
elliptical, pentagon, and hexagon nozzles are simulated using Fluent
Code with all have same cross-sectional area.
The simple one-dimensional inviscid theory does not describe the
actual features of fluid flow precisely as it ignores the impact of
nozzle configuration on the flow properties. CFD Simulation results,
however, show that nozzle geometry influences the flow structures
including location of shock wave.
The CFD analysis predicts shock appearance when p01/pa>1.2 for
almost all geometry and locates at the lower area ratio (Ae/At).
Simulation results showed that shock wave in Elliptical nozzle has
the farthest distance from the throat among the others at relatively
small NPR. As NPR increases, hexagon would be the farthest. The
numerical result is compared with available experimental data and
has shown good agreement in terms of shock location and flow
structure.
Abstract: SQL injection on web applications is a very popular
kind of attack. There are mechanisms such as intrusion detection
systems in order to detect this attack. These strategies often rely on
techniques implemented at high layers of the application but do not
consider the low level of system calls. The problem of only
considering the high level perspective is that an attacker can
circumvent the detection tools using certain techniques such as URL
encoding. One technique currently used for detecting low-level
attacks on privileged processes is the tracing of system calls. System
calls act as a single gate to the Operating System (OS) kernel; they
allow catching the critical data at an appropriate level of detail. Our
basic assumption is that any type of application, be it a system
service, utility program or Web application, “speaks” the language of
system calls when having a conversation with the OS kernel. At this
level we can see the actual attack while it is happening. We conduct
an experiment in order to demonstrate the suitability of system call
analysis for detecting SQL injection. We are able to detect the attack.
Therefore we conclude that system calls are not only powerful in
detecting low-level attacks but that they also enable us to detect highlevel
attacks such as SQL injection.
Abstract: Mel Frequency Cepstral Coefficient (MFCC) features
are widely used as acoustic features for speech recognition as well
as speaker recognition. In MFCC feature representation, the Mel frequency
scale is used to get a high resolution in low frequency region,
and a low resolution in high frequency region. This kind of processing
is good for obtaining stable phonetic information, but not suitable
for speaker features that are located in high frequency regions. The
speaker individual information, which is non-uniformly distributed
in the high frequencies, is equally important for speaker recognition.
Based on this fact we proposed an admissible wavelet packet based
filter structure for speaker identification. Multiresolution capabilities
of wavelet packet transform are used to derive the new features.
The proposed scheme differs from previous wavelet based works,
mainly in designing the filter structure. Unlike others, the proposed
filter structure does not follow Mel scale. The closed-set speaker
identification experiments performed on the TIMIT database shows
improved identification performance compared to other commonly
used Mel scale based filter structures using wavelets.
Abstract: A genetic algorithm (GA) based feature subset
selection algorithm is proposed in which the correlation structure of
the features is exploited. The subset of features is validated according
to the classification performance. Features derived from the
continuous wavelet transform are potentially strongly correlated.
GA-s that do not take the correlation structure of features into
account are inefficient. The proposed algorithm forms clusters of
correlated features and searches for a good candidate set of clusters.
Secondly a search within the clusters is performed. Different
simulations of the algorithm on a real-case data set with strong
correlations between features show the increased classification
performance. Comparison is performed with a standard GA without
use of the correlation structure.
Abstract: Analysis of reciprocating equipment piston rod leads
to nonlinear elastic-plastic deformation analysis of rod with initial
imperfection under axial dynamic load. In this paper a new and
effective model and analytical formulations are presented to evaluate
dynamic deformation and elastic-plastic stresses of reciprocating
machine piston rod. This new method has capability to account for
geometric nonlinearity, elastic-plastic deformation and dynamic
effects. Proposed method can be used for evaluation of piston rod
performance for various reciprocating machines under different
operation situations. Rod load curves and maximum allowable rod
load are calculated with presented method for a refinery type
reciprocating compressor. Useful recommendations and guidelines
for rod load, rod load reversal and rod drop monitoring are also
addressed.
Abstract: Stress Concentration Factors are significant in
machine design as it gives rise to localized stress when any change in
the design of surface or abrupt change in the cross section occurs.
Almost all machine components and structural members contain
some form of geometrical or microstructural discontinuities. These
discontinuities are very dangerous and lead to failure. So, it is very
much essential to analyze the stress concentration factors for critical
applications like Turbine Rotors. In this paper Finite Element
Analysis (FEA) with extremely fine mesh in the vicinity of the
blades of Steam Turbine Rotor is applied to determine stress
concentration factors. A model of Steam Turbine Rotor is shown in
Fig. 1.
Abstract: A novel design of two-wheeled robotic vehicle with moving payload is presented in this paper. A mathematical model describing the vehicle dynamics is derived and simulated in Matlab Simulink environment. Two control strategies were developed to stabilise the vehicle in the upright position. A robust Proportional- Integral-Derivative (PID) control strategy has been implemented and initially tested to measure the system performance, while the second control strategy is to use a hybrid fuzzy logic controller (FLC). The results are given on a comparative basis for the system performance in terms of disturbance rejection, control algorithms robustness as well as the control effort in terms of input torque.
Abstract: In the present study, a steady-state simulation model
has been developed to evaluate the system performance of a
transcritical carbon dioxide heat pump system for simultaneous water
cooling and heating. Both the evaporator (including both two-phase
and superheated zone) and gas cooler models consider the highly
variable heat transfer characteristics of CO2 and pressure drop. The
numerical simulation model of transcritical CO2 heat pump has been
validated by test data obtained from experiments on the heat pump
prototype. Comparison between the test results and the model
prediction for system COP variation with compressor discharge
pressure shows a modest agreement with a maximum deviation of
15% and the trends are fairly similar. Comparison for other operating
parameters also shows fairly similar deviation between the test
results and the model prediction. Finally, the simulation results are
presented to study the effects of operating parameters such as,
temperature of heat exchanger fluid at the inlet, discharge pressure,
compressor speed on system performance of CO2 heat pump, suitable
in a dairy plant where simultaneous cooling at 4oC and heating at
73oC are required. Results show that good heat transfer properties of
CO2 for both two-phase and supercritical region and efficient
compression process contribute a lot for high system COPs.
Abstract: According to the theory of capital structure, this paper uses principal component analysis and linear regression analysis to study the relationship between the debt characteristics of the private listed companies in Jiangsu Province and their business performance. The results show that the average debt ratio of the 29 private listed companies selected from the sample is lower. And it is found that for the sample whose debt ratio is lower than 80%, its debt ratio is negatively related to corporate performance, while for the sample whose debt ratio is beyond 80%, the relationship of debt financing and enterprise performance shows the different trends. The conclusions reflect the drawbacks may exist that the debt ratio is relatively low and having not take full advantage of debt governance effect of the private listed companies in Jiangsu Province.
Abstract: In this paper, the Lennard -Jones potential is applied
to molecules of liquid argon as well as its vapor and platinum as solid
surface in order to perform a non-equilibrium molecular dynamics
simulation to study the microscopic aspects of liquid-vapor-solid
interactions. The channel is periodic in x and y directions and along z
direction it is bounded by atomic walls. It was found that density of
the liquids near the solid walls fluctuated greatly and that the
structure was more like a solid than a liquid. This indicates that the
interactions of solid and liquid molecules are very strong. The
resultant surface tension, liquid density and vapor density are found
to be well predicted when compared with the experimental data for
argon. Liquid and vapor densities were found to depend on the cutoff
radius which induces the use of P3M (particle-particle particle-mesh)
method which was implemented for evaluation of force and surface
tension.
Abstract: Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.
Abstract: Reliable information about tool temperature
distribution is of central importance in metal cutting. In this study,
tool-chip interface temperature was determined in cutting of ST37
steel workpiece by applying HSS as the cutting tool in dry turning.
Two different approaches were implemented for temperature
measuring: an embedded thermocouple (RTD) in to the cutting tool
and infrared (IR) camera. Comparisons are made between
experimental data and results of MSC.SuperForm and FLUENT
software.
An investigation of heat generation in cutting tool was performed
by varying cutting parameters at the stable cutting tool geometry and
results were saved in a computer; then the diagrams of tool
temperature vs. various cutting parameters were obtained. The
experimental results reveal that the main factors of the increasing
cutting temperature are cutting speed (V ), feed rate ( S ) and depth
of cut ( h ), respectively. It was also determined that simultaneously
change in cutting speed and feed rate has the maximum effect on
increasing cutting temperature.
Abstract: This paper gives a novel method for improving
classification performance for cancer classification with very few
microarray Gene expression data. The method employs classification
with individual gene ranking and gene subset ranking. For selection
and classification, the proposed method uses the same classifier. The
method is applied to three publicly available cancer gene expression
datasets from Lymphoma, Liver and Leukaemia datasets. Three
different classifiers namely Support vector machines-one against all
(SVM-OAA), K nearest neighbour (KNN) and Linear Discriminant
analysis (LDA) were tested and the results indicate the improvement
in performance of SVM-OAA classifier with satisfactory results on
all the three datasets when compared with the other two classifiers.
Abstract: The most reliable and accurate description of the actual behavior of a software system is its source code. However, not all questions about the system can be answered directly by resorting to this repository of information. What the reverse engineering methodology aims at is the extraction of abstract, goal-oriented “views" of the system, able to summarize relevant properties of the computation performed by the program. While concentrating on reverse engineering we had modeled the C++ files by designing the translator.
Abstract: The company-s ability to draw on a range of external
sources to meet their needs for innovation, has been termed 'open
innovation' (OI). Very few empirical analyses have been conducted
on Small and Medium Enterprises (SMEs) to the extent that they
describe and understand the characteristics and implications of this
new paradigm.
The study's objective is to identify and characterize different
modes of OI, (considering innovation process phases and the variety
and breadth of the collaboration), determinants, barriers and
motivations in SMEs. Therefore a survey was carried out among
Italian manufacturing firms and a database of 105 companies was
obtained. With regard to data elaboration, a factorial and cluster
analysis has been conducted and three different OI modes have
emerged: selective low open, unselective open upstream, and mid-
partners integrated open. The different behaviours of the three
clusters in terms of determinants factors, performance, firm-s
technology intensity, barriers and motivations have been analyzed
and discussed.
Abstract: Nowadays use of a new structural bracing system
called 'Knee Bracing System' have taken the specialists attention too
much. On the other hand nonlinear static analysis procedures in
estimate structures performance in earthquake time have taken
attention too much. One of these procedure is modal pushover
analysis (MPA) procedure. The accuracy of MPA procedure for
simple steel moment resisting frame has been verified and considered
in Chintanapakdee and Chopra-s article in 2003. Since the accuracy
of MPA procedure has not verified for semi-rigid steel frames with
knee bracing, we are going to get through with this matter in this
study. For this purpose, the selected structures are four frames with
different heights, 5 to 20 stories, will be designed according to AISC
criteria. Then MPA procedure is used for the same frames with
different rigidity percentiles of connections. The results of seismic
responses are compared with dynamic nonlinear response history
analysis as exact procedure and accuracy of MPA procedure is
evaluated. It seems that MPA procedure accuracy will come down by
reduction of the rigidity percentiles of semi-rigid connections.
Abstract: Some physical properties of musk lime (Citrus
microcarpa) were determined in this study. The average moisture
content (wet basis) of the fruit was found to be 85.10 (±0.72) %. The
mean of length, width and thickness of the fruit was 26.36 (±0.97),
26.40 (±1.04) and 25.26 (±0.94) mm respectively. The average value
for geometric mean diameter, sphericity, aspect ratio, mass, surface
area, volume, true density, bulk density and porosity was 26.00
(±0.82) mm, 98.67 (±2.04) %, 100.23 (±3.28) %, 10.007 (±0.878) g,
2125.07 (±133.93) mm2, 8800.00 (±731.82) mm3, 1002.87 (±39.16)
kgm-3, 501.70 (±22.58) kgm-3 and 49.89 (±3.15) % respectively.
The coefficient of static friction on four types of structural surface
was found to be varying from 0.238 (±0.025) for glass to 0.247
(±0.024) for steel surface.
Abstract: This paper investigates the performance of a speech
recognizer in an interactive voice response system for various coded
speech signals, coded by using a vector quantization technique namely
Multi Switched Split Vector Quantization Technique. The process of
recognizing the coded output can be used in Voice banking application.
The recognition technique used for the recognition of the coded speech
signals is the Hidden Markov Model technique. The spectral distortion
performance, computational complexity, and memory requirements of
Multi Switched Split Vector Quantization Technique and the
performance of the speech recognizer at various bit rates have been
computed. From results it is found that the speech recognizer is
showing better performance at 24 bits/frame and it is found that the
percentage of recognition is being varied from 100% to 93.33% for
various bit rates.
Abstract: This report shows the performance of composite
biodegradable film from chitosan, starch and sawdust fiber. The main
objectives of this research are to fabricate and characterize composite
biodegradable film in terms of morphology and physical properties.
The film was prepared by casting method. Sawdust fiber was used as
reinforcing agent and starch as polymer matrix in the casting
solution. The morphology of the film was characterized using atomic
force microscope (AFM). The result showed that the film has
smooth structure. Chemical composition of the film was investigated
using Fourier transform infrared (FTIR) where the result revealed
present of starch in the film. The thermal properties were
characterized using thermal gravimetric analyzer (TGA) and
differential scanning calorimetric (DSC) where the results showed
that the film has small difference in melting and degradation
temperature.