Abstract: Clustering in high dimensional space is a difficult
problem which is recurrent in many fields of science and
engineering, e.g., bioinformatics, image processing, pattern
reorganization and data mining. In high dimensional space some of
the dimensions are likely to be irrelevant, thus hiding the possible
clustering. In very high dimensions it is common for all the objects in
a dataset to be nearly equidistant from each other, completely
masking the clusters. Hence, performance of the clustering algorithm
decreases.
In this paper, we propose an algorithmic framework which
combines the (reduct) concept of rough set theory with the k-means
algorithm to remove the irrelevant dimensions in a high dimensional
space and obtain appropriate clusters. Our experiment on test data
shows that this framework increases efficiency of the clustering
process and accuracy of the results.
Abstract: Modeling of the dynamic behavior and motion are
renewed interest in the improved tractive performance of an
intelligent air-cushion tracked vehicle (IACTV). This paper presents
a new dynamical model for the forces on the developed small scale
intelligent air-cushion tracked vehicle moving over swamp peat. The
air cushion system partially supports the 25 % of vehicle total weight
in order to make the vehicle ground contact pressure 7 kN/m2. As the
air-cushion support system can adjust automatically on the terrain, so
the vehicle can move over the terrain without any risks. The springdamper
system is used with the vehicle body to control the aircushion
support system on any undulating terrain by making the
system sinusoidal form. Experiments have been carried out to
investigate the relationships among tractive efficiency, slippage,
traction coefficient, load distribution ratio, tractive effort, motion
resistance and power consumption in given terrain conditions.
Experiment and simulation results show that air-cushion system
improves the vehicle performance by keeping traction coefficient of
71% and tractive efficiency of 62% and the developed model can
meet the demand of transport efficiency with the optimal power
consumption.
Abstract: Auckland has a temperate climate with comfortable warm, dry summers and mild, wet winters. Auckland house design not only focus on winter thermal performance and indoor thermal condition, but also indoor moisture control, which is closely related to indirect health effects such as dust mites, fungi, etc. Most Auckland houses are designed to use temporary heating for winter indoor thermal comfort. Based on field study data of indoor microclimate conditions of two Auckland townhouses with a whole home mechanical ventilation system or a passive wind directional skylight vent, this study is to evaluate and compare indoor moisture conditions of two insulated townhouses only using temporary heating with different ventilation systems.
Abstract: This paper is prepared to provide a review of how an automotive manufacturer, ISUZU HICOM Malaysia Co. Ltd. sustained the supply chain management after business process reengineering in 2007. One of the authors is currently undergoing industrial attachment and has spent almost 6 months researching in the production and operation management system of the company. This study was carried out as part of the tasks in the attachment program. The result shows that delivery lateness and outsourcing are the main barriers that affected productivity. From the gap analysis, the authors found that new business process operation had improved suppliers delivery performance.
Abstract: For numerical prediction of the NOX in the exhaust of
a compression ignition engine a model was developed by considering
the parameter equivalence ratio. This model was validated by
comparing the predicted results of NOX with experimental ones. The
ultimate aim of the work was to access the applicability, robustness
and performance of the improved NOX model against other NOX
models.
Abstract: Wireless Sensor Networks (WSNs) are wireless
networks consisting of number of tiny, low cost and low power
sensor nodes to monitor various physical phenomena like
temperature, pressure, vibration, landslide detection, presence of any
object, etc. The major limitation in these networks is the use of nonrechargeable
battery having limited power supply. The main cause of
energy consumption WSN is communication subsystem. This paper
presents an efficient grid formation/clustering strategy known as Grid
based level Clustering and Aggregation of Data (GCAD). The
proposed clustering strategy is simple and scalable that uses low duty
cycle approach to keep non-CH nodes into sleep mode thus reducing
energy consumption. Simulation results demonstrate that our
proposed GCAD protocol performs better in various performance
metrics.
Abstract: Particle Swarm Optimization (PSO) with elite PSO
parameters has been developed for power flow analysis under
practical constrained situations. Multiple solutions of the power flow
problem are useful in voltage stability assessment of power system.
A method of determination of multiple power flow solutions is
presented using a hybrid of Particle Swarm Optimization (PSO) and
local search technique. The unique and innovative learning factors of
the PSO algorithm are formulated depending upon the node power
mismatch values to be highly adaptive with the power flow problems.
The local search is applied on the pbest solution obtained by the PSO
algorithm in each iteration. The proposed algorithm performs reliably
and provides multiple solutions when applied on standard and illconditioned
systems. The test results show that the performances of
the proposed algorithm under critical conditions are better than the
conventional methods.
Abstract: This paper features the modeling and design of a Fast
Output Sampling (FOS) Feedback control technique for the Active
Vibration Control (AVC) of a smart flexible aluminium cantilever
beam for a Single Input Single Output (SISO) case. Controllers are
designed for the beam by bonding patches of piezoelectric layer as
sensor / actuator to the master structure at different locations along
the length of the beam by retaining the first 2 dominant vibratory
modes. The entire structure is modeled in state space form using the
concept of piezoelectric theory, Euler-Bernoulli beam theory, Finite
Element Method (FEM) and the state space techniques by dividing
the structure into 3, 4, 5 finite elements, thus giving rise to three
types of systems, viz., system 1 (beam divided into 3 finite
elements), system 2 (4 finite elements), system 3 (5 finite elements).
The effect of placing the sensor / actuator at various locations along
the length of the beam for all the 3 types of systems considered is
observed and the conclusions are drawn for the best performance and
for the smallest magnitude of the control input required to control the
vibrations of the beam. Simulations are performed in MATLAB. The
open loop responses, closed loop responses and the tip displacements
with and without the controller are obtained and the performance of
the proposed smart system is evaluated for vibration control.
Abstract: In India, the quarrel between the budding human
populace and the planet-s unchanging supply of freshwater and
falling water tables has strained attention the reuse of gray water as
an alternative water resource in rural development. This paper
present the finest design of laboratory scale gray water treatment
plant, which is a combination of natural and physical operations such
as primary settling with cascaded water flow, aeration, agitation and
filtration, hence called as hybrid treatment process. The economical
performance of the plant for treatment of bathrooms, basins and
laundries gray water showed in terms of deduction competency of
water pollutants such as COD (83%), TDS (70%), TSS (83%), total
hardness (50%), oil and grease (97%), anions (46%) and cations
(49%). Hence, this technology could be a good alternative to treat
gray water in residential rural area.
Abstract: This paper applies Bayesian Networks to support
information extraction from unstructured, ungrammatical, and
incoherent data sources for semantic annotation. A tool has been
developed that combines ontologies, machine learning, and
information extraction and probabilistic reasoning techniques to
support the extraction process. Data acquisition is performed with the
aid of knowledge specified in the form of ontology. Due to the
variable size of information available on different data sources, it is
often the case that the extracted data contains missing values for
certain variables of interest. It is desirable in such situations to
predict the missing values. The methodology, presented in this paper,
first learns a Bayesian network from the training data and then uses it
to predict missing data and to resolve conflicts. Experiments have
been conducted to analyze the performance of the presented
methodology. The results look promising as the methodology
achieves high degree of precision and recall for information
extraction and reasonably good accuracy for predicting missing
values.
Abstract: Recently, many existing partially blind signature scheme based on a single hard problem such as factoring, discrete logarithm, residuosity or elliptic curve discrete logarithm problems. However sooner or later these systems will become broken and vulnerable, if the factoring or discrete logarithms problems are cracked. This paper proposes a secured partially blind signature scheme based on factoring (FAC) problem and elliptic curve discrete logarithms (ECDL) problem. As the proposed scheme is focused on factoring and ECDLP hard problems, it has a solid structure and will totally leave the intruder bemused because it is very unlikely to solve the two hard problems simultaneously. In order to assess the security level of the proposed scheme a performance analysis has been conducted. Results have proved that the proposed scheme effectively deals with the partial blindness, randomization, unlinkability and unforgeability properties. Apart from this we have also investigated the computation cost of the proposed scheme. The new proposed scheme is robust and it is difficult for the malevolent attacks to break our scheme.
Abstract: The ever increasing use of World Wide Web in the
existing network, results in poor performance. Several techniques
have been developed for reducing web traffic by compressing the size
of the file, saving the web pages at the client side, changing the burst
nature of traffic into constant rate etc. No single method was
adequate enough to access the document instantly through the
Internet. In this paper, adaptive hybrid algorithms are developed for
reducing web traffic. Intelligent agents are used for monitoring the
web traffic. Depending upon the bandwidth usage, user-s preferences,
server and browser capabilities, intelligent agents use the best
techniques to achieve maximum traffic reduction. Web caching,
compression, filtering, optimization of HTML tags, and traffic
dispersion are incorporated into this adaptive selection. Using this
new hybrid technique, latency is reduced to 20 – 60 % and cache hit
ratio is increased 40 – 82 %.
Abstract: In this paper we study the use of a new code called
Random Diagonal (RD) code for Spectral Amplitude Coding (SAC)
optical Code Division Multiple Access (CDMA) networks, using
Fiber Bragg-Grating (FBG), FBG consists of a fiber segment whose
index of reflection varies periodically along its length. RD code is
constructed using code level and data level, one of the important
properties of this code is that the cross correlation at data level is
always zero, which means that Phase intensity Induced Phase (PIIN)
is reduced. We find that the performance of the RD code will be
better than Modified Frequency Hopping (MFH) and Hadamard code
It has been observed through experimental and theoretical simulation
that BER for RD code perform significantly better than other codes.
Proof –of-principle simulations of encoding with 3 channels, and 10
Gbps data transmission have been successfully demonstrated together
with FBG decoding scheme for canceling the code level from SAC-signal.
Abstract: The aim of this research is to use artificial neural networks computing technology for estimating the net heating value (NHV) of crude oil by its Properties. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The network with 8 neurons in one hidden layer was selected and prediction of this network has been good agreement with experimental data.
Abstract: Load forecasting has always been the essential part of
an efficient power system operation and planning. A novel approach
based on support vector machines is proposed in this paper for annual
power load forecasting. Different kernel functions are selected to
construct a combinatorial algorithm. The performance of the new
model is evaluated with a real-world dataset, and compared with two
neural networks and some traditional forecasting techniques. The
results show that the proposed method exhibits superior performance.
Abstract: Rice husk is one of the alternative fuels for Thailand because of its high potential and environmental benefits. Nonetheless, the environmental profile of the electricity production from rice husk must be assessed to ensure reduced environmental damage. A 10 MW pilot plant using rice husk as feedstock is the study site. The environmental impacts from rice husk power plant are evaluated by using the Life Cycle Assessment (LCA) methodology. Energy, material and carbon balances have been determined for tracing the system flow. Carbon closure has been used for describing of the net amount of CO2 released from the system in relation to the amount being recycled between the power plant and the CO2 adsorbed by rice husk. The transportation of rice husk to the power plant has significant on global warming, but not on acidification and photo-oxidant formation. The results showed that the impact potentials from rice husk power plant are lesser than the conventional plants for most of the categories considered; except the photo-oxidant formation potential from CO. The high CO from rice husk power plant may be due to low boiler efficiency and high moisture content in rice husk. The performance of the study site can be enhanced by improving the combustion efficiency.
Abstract: The spiral angle of the elementary cellulose fibril in
the wood cell wall, often called microfibril angle, (MFA). Microfibril
angle in hardwood is one of the key determinants of solid timber
performance due to its strong influence on the stiffness, strength,
shrinkage, swelling, thermal-dynamics mechanical properties and
dimensional stability of wood. Variation of MFA (degree) in the S2
layer of the cell walls among Acacia mangium trees was determined
using small-angle X-ray scattering (SAXS). The length and
orientation of the microfibrils of the cell walls in the irradiated
volume of the thin samples are measured using SAXS and optical
microscope for 3D surface measurement. The undetermined
parameters in the analysis are the MFA, (M) and the standard
deviation (σФ) of the intensity distribution arising from the wandering
of the fibril orientation about the mean value. Nine separate pairs of
values are determined for nine different values of the angle of the
incidence of the X-ray beam relative to the normal to the radial
direction in the sample. The results show good agreement. The
curve distribution of scattered intensity for the real cell wall structure
is compared with that calculated with that assembly of rectangular
cells with the same ratio of transverse to radial cell wall length. It is
demonstrated that for β = 45°, the peaks in the curve intensity
distribution for the real and the rectangular cells coincide. If this
peak position is Ф45, then the MFA can be determined from the
relation M = tan-1 (tan Ф45 / cos 45°), which is precise for rectangular
cells. It was found that 92.93% of the variation of MFA can be
attributed to the distance from pith to bark. Here we shall present our
results of the MFA in the cell wall with respect to its shape, structure
and the distance from pith to park as an important fast check and yet
accurate towards the quality of wood, its uses and application.
Abstract: This paper presents a means for reducing the torque
variation during the revolution of a vertical-axis water turbine
(VAWaterT) by increasing the blade number. For this purpose, twodimensional
CFD analyses have been performed on a straight-bladed
Darrieus-type rotor. After describing the computational model and
the relative validation procedure, a complete campaign of
simulations, based on full RANS unsteady calculations, is proposed
for a three, four and five-bladed rotor architectures, characterized by
a NACA 0025 airfoil. For each proposed rotor configuration, flow
field characteristics are investigated at several values of tip speed
ratio, allowing a quantification of the influence of blade number on
flow geometric features and dynamic quantities, such as rotor torque
and power. Finally, torque and power curves are compared for the
three analyzed architectures, achieving a quantification of the effect
of blade number on overall rotor performance.
Abstract: This study demonstrates the use of Class F fly ash in
combination with lime or lime kiln dust in the full depth reclamation
(FDR) of asphalt pavements. FDR, in the context of this paper, is a
process of pulverizing a predetermined amount of flexible pavement
that is structurally deficient, blending it with chemical additives and
water, and compacting it in place to construct a new stabilized base
course. Test sections of two structurally deficient asphalt pavements
were reclaimed using Class F fly ash in combination with lime and
lime kiln dust. In addition, control sections were constructed using
cement, cement and emulsion, lime kiln dust and emulsion, and mill
and fill. The service performance and structural behavior of the FDR
pavement test sections were monitored to determine how the fly ash
sections compared to other more traditional pavement rehabilitation
techniques. Service performance and structural behavior were
determined with the use of sensors embedded in the road and Falling
Weight Deflectometer (FWD) tests. Monitoring results of the FWD
tests conducted up to 2 years after reclamation show that the cement,
fly ash+LKD, and fly ash+lime sections exhibited two year resilient
modulus values comparable to open graded cement stabilized
aggregates (more than 750 ksi). The cement treatment resulted in a
significant increase in resilient modulus within 3 weeks of
construction and beyond this curing time, the stiffness increase was
slow. On the other hand, the fly ash+LKD and fly ash+lime test
sections indicated slower shorter-term increase in stiffness. The fly
ash+LKD and fly ash+lime section average resilient modulus values
at two years after construction were in excess of 800 ksi. Additional
longer-term testing data will be available from ongoing pavement
performance and environmental condition data collection at the two
pavement sites.
Abstract: Cancers could normally be marked by a number of
differentially expressed genes which show enormous potential as
biomarkers for a certain disease. Recent years, cancer classification
based on the investigation of gene expression profiles derived by
high-throughput microarrays has widely been used. The selection of
discriminative genes is, therefore, an essential preprocess step in
carcinogenesis studies. In this paper, we have proposed a novel gene
selector using information-theoretic measures for biological
discovery. This multivariate filter is a four-stage framework through
the analyses of feature relevance, feature interdependence, feature
redundancy-dependence and subset rankings, and having been
examined on the colon cancer data set. Our experimental result show
that the proposed method outperformed other information theorem
based filters in all aspect of classification errors and classification
performance.