Abstract: Large volumes of fingerprints are collected and stored
every day in a wide range of applications, including forensics, access
control etc. It is evident from the database of Federal Bureau of
Investigation (FBI) which contains more than 70 million finger
prints. Compression of this database is very important because of this
high Volume. The performance of existing image coding standards
generally degrades at low bit-rates because of the underlying block
based Discrete Cosine Transform (DCT) scheme. Over the past
decade, the success of wavelets in solving many different problems
has contributed to its unprecedented popularity. Due to
implementation constraints scalar wavelets do not posses all the
properties which are needed for better performance in compression.
New class of wavelets called 'Multiwavelets' which posses more
than one scaling filters overcomes this problem. The objective of this
paper is to develop an efficient compression scheme and to obtain
better quality and higher compression ratio through multiwavelet
transform and embedded coding of multiwavelet coefficients through
Set Partitioning In Hierarchical Trees algorithm (SPIHT) algorithm.
A comparison of the best known multiwavelets is made to the best
known scalar wavelets. Both quantitative and qualitative measures of
performance are examined for Fingerprints.
Abstract: In this paper a unified approach via block-pulse functions (BPFs) or shifted Legendre polynomials (SLPs) is presented to solve the linear-quadratic-Gaussian (LQG) control problem. Also a recursive algorithm is proposed to solve the above problem via BPFs. By using the elegant operational properties of orthogonal functions (BPFs or SLPs) these computationally attractive algorithms are developed. To demonstrate the validity of the proposed approaches a numerical example is included.
Abstract: This project focuses on the development of a line
follower algorithm for a Two Wheels Balancing Robot. In this
project, ATMEGA32 is chosen as the brain board controller to react
towards the data received from Balance Processor Chip on the
balance board to monitor the changes of the environment through
two infra-red distance sensor to solve the inclination angle problem.
Hence, the system will immediately restore to the set point (balance
position) through the implementation of internal PID algorithms at
the balance board. Application of infra-red light sensors with the PID
control is vital, in order to develop a smooth line follower robot. As a
result of combination between line follower program and internal self
balancing algorithms, we are able to develop a dynamically
stabilized balancing robot with line follower function.
Abstract: This paper deals with a portfolio selection problem
based on the possibility theory under the assumption that the returns
of assets are LR-type fuzzy numbers. A possibilistic portfolio model
with transaction costs is proposed, in which the possibilistic mean
value of the return is termed measure of investment return, and the
possibilistic variance of the return is termed measure of investment
risk. Due to considering transaction costs, the existing traditional
optimization algorithms usually fail to find the optimal solution
efficiently and heuristic algorithms can be the best method. Therefore,
a particle swarm optimization is designed to solve the corresponding
optimization problem. At last, a numerical example is given to
illustrate our proposed effective means and approaches.
Abstract: The wireless sensor networks have been extensively
deployed and researched. One of the major issues in wireless sensor
networks is a developing energy-efficient clustering protocol.
Clustering algorithm provides an effective way to prolong the lifetime
of a wireless sensor networks. In the paper, we compare several
clustering protocols which significantly affect a balancing of energy
consumption. And we propose an Energy-Efficient Distributed
Unequal Clustering (EEDUC) algorithm which provides a new way of
creating distributed clusters. In EEDUC, each sensor node sets the
waiting time. This waiting time is considered as a function of residual
energy, number of neighborhood nodes. EEDUC uses waiting time to
distribute cluster heads. We also propose an unequal clustering
mechanism to solve the hot-spot problem. Simulation results show that
EEDUC distributes the cluster heads, balances the energy
consumption well among the cluster heads and increases the network
lifetime.
Abstract: This paper presents the use of Legendre pseudospectral
method for the optimization of finite-thrust orbital transfer for
spacecrafts. In order to get an accurate solution, the System-s
dynamics equations were normalized through a dimensionless method.
The Legendre pseudospectral method is based on interpolating
functions on Legendre-Gauss-Lobatto (LGL) quadrature nodes. This
is used to transform the optimal control problem into a constrained
parameter optimization problem. The developed novel optimization
algorithm can be used to solve similar optimization problems of
spacecraft finite-thrust orbital transfer. The results of a numerical
simulation verified the validity of the proposed optimization method.
The simulation results reveal that pseudospectral optimization method
is a promising method for real-time trajectory optimization and
provides good accuracy and fast convergence.
Abstract: Guard channels improve the probability of successful
handoffs by reserving a number of channels exclusively for handoffs.
This concept has the risk of underutilization of radio spectrum due to
the fact that fewer channels are granted to originating calls even if
these guard channels are not always used, when originating calls are
starving for the want of channels. The penalty is the reduction of
total carried traffic. The optimum number of guard channels can help
reduce this problem. This paper presents fuzzy logic based guard
channel scheme wherein guard channels are reorganized on the basis
of traffic density, so that guard channels are provided on need basis.
This will help in incorporating more originating calls and hence high
throughput of the radio spectrum
Abstract: The group mutual exclusion (GME) problem is an
interesting generalization of the mutual exclusion problem. Several
solutions of the GME problem have been proposed for message
passing distributed systems. However, none of these solutions is
suitable for real time distributed systems. In this paper, we propose a
token-based distributed algorithms for the GME problem in soft real
time distributed systems. The algorithm uses the concepts of priority
queue, dynamic request set and the process state. The algorithm uses
first come first serve approach in selecting the next session type
between the same priority levels and satisfies the concurrent
occupancy property. The algorithm allows all n processors to be
inside their CS provided they request for the same session. The
performance analysis and correctness proof of the algorithm has also
been included in the paper.
Abstract: In this study, an analysis has been performed for
heat and mass transfer of a steady laminar boundary-layer flow
of a viscous flow past a nonlinearly stretching sheet.
Parameters n, Ec, k0, Sc represent the dominance of the
nonlinearly effect, viscous effect, radiation effect and mass
transfer effect which have presented in governing equations,
respectively. The similarity transformation and the
finite-difference method have been used to analyze the present
problem.
Abstract: Global competitiveness has recently become the
biggest concern of both manufacturing and service companies.
Electronic commerce, as a key technology enables the firms to reach
all the potential consumers from all over the world. In this study, we
have presented commonly used electronic payment systems, and then
we have shown the evaluation of these systems in respect to different
criteria. The payment systems which are included in this research are
the credit card, the virtual credit card, the electronic money, the
mobile payment, the credit transfer and the debit instruments. We
have realized a systematic comparison of these systems in respect to
three main criteria: Technical, economical and social. We have
conducted a fuzzy multi-criteria decision making procedure to deal
with the multi-attribute nature of the problem. The subjectiveness
and imprecision of the evaluation process are modeled using
triangular fuzzy numbers.
Abstract: The purposes of this study are 1) to study the over 20-year attempt of Mahakan fort community to negotiate with Bangkok Metropolitan Administration (BMA) to remain in their residential area belonging to the state, and 2) to apply the new social and cultural dimension between the state and the community as an alternative for local participation in keeping their residential area. This is a qualitative research, and the findings reveal that the community claimed their ancestors’ right as owners of this piece of land for over 200 years. The community, therefore, requested to take part in the preservation of land, culture and local intellect and the area management in terms of being a learning resource on the cultural road in Rattanakosin Island. However, BMA imposed the law concerning the community area relocation in Rattanakosin Island. The result of law enforcement led to the failure of the area relocation, and the hard hit on physical structure of the area including the overall deterioration of the cultural road renovated in the year 1982, the 200 years’ celebration of Bangkok. The enforcement of law by the state required the move of the community, and the landscape improvement based on the capital city plan. However, this enforcement resulted in the unending conflicts between the community and the state, and the solution of this problem was unclear. At the same time the community has spent a long time opposing the state’s action, and preparing themselves by administrating the community behind Mahakan fortress with community administrative committee under the suggestion of external organization by registering all community members, providing funds for community administration. At the meantime the state lacked the continuation of the enforcement due to political problem and BMA’s administration problem. It is, therefore, suggested that an alternative solution to this problem lie at the negotiation between the state and the community with the purpose of the collaboration between the two to develop the area under the protective law of each side.
Abstract: In production of medicinal plants, seed germination is
very important problem. The treated seeds (control, hydro priming
and ZnSO4) of Cumin (Cuminum cyminum L.) were evaluated at
germination and seedling growth for tolerance to salt (NaCl and
Na2SO4) conditions at the same water potentials of 0.0, -0.3, -0.6, -
0.9 and -1.2MPa. Electrical conductivity (EC) values of the NaCl
solutions were 0.0, 6.5, 12.7, 18.4 and 23.5 dSm-1, respectively. The
objective of the study was to determine factors responsible for
germination and early seedling growth due to salt toxicity or osmotic
effect and to optimize the best priming treatment for these stress
conditions. Results revealed that germination delayed in both
solutions, having variable germination with different priming
treatments. Germination, shoot and weight, root and shoot length
were higher but mean germination time and abnormal germination
percentage were lower in NaCl than Na2SO4 at the same water
potential. The root / shoot weight and R/S length increased with
increase in osmotic potential in both NaCl and Na2SO4 solutions.
NaCl had less inhibitor effect on seedling growth than the
germination. It was concluded that inhibition of germination at the
same water potential of NaCl and Na2SO4 resulted from salt toxicity
rather than osmotic effect. Hydro priming increased germination and
seedling growth under salt stress. This protocol has practical
importance and could be recommended to farmers to achieve higher
germination and uniform emergence under field conditions.
Abstract: Due to their high power-to-weight ratio and low cost,
pneumatic actuators are attractive for robotics and automation
applications; however, achieving fast and accurate control of their
position have been known as a complex control problem. A
methodology for obtaining high position accuracy with a linear
pneumatic actuator is presented. During experimentation with a
number of PID classical control approaches over many operations of
the pneumatic system, the need for frequent manual re-tuning of the
controller could not be eliminated. The reason for this problem is
thermal and energy losses inside the cylinder body due to the
complex friction forces developed by the piston displacements.
Although PD controllers performed very well over short periods, it
was necessary in our research project to introduce some form of
automatic gain-scheduling to achieve good long-term performance.
We chose a fuzzy logic system to do this, which proved to be an
easily designed and robust approach. Since the PD approach showed
very good behaviour in terms of position accuracy and settling time,
it was incorporated into a modified form of the 1st order Tagaki-
Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler
uses an input variable which automatically changes the PD
gain values of the controller according to the frequency of repeated
system operations. Performance of the new controller was
significantly improved and the need for manual re-tuning was
eliminated without a decrease in performance. The performance of
the controller operating with the above method is going to be tested
through a high-speed web network (GRID) for research purposes.
Abstract: With deep development of software reuse, componentrelated
technologies have been widely applied in the development of
large-scale complex applications. Component identification (CI) is
one of the primary research problems in software reuse, by analyzing
domain business models to get a set of business components with high
reuse value and good reuse performance to support effective reuse.
Based on the concept and classification of CI, its technical stack is
briefly discussed from four views, i.e., form of input business models,
identification goals, identification strategies, and identification
process. Then various CI methods presented in literatures are
classified into four types, i.e., domain analysis based methods,
cohesion-coupling based clustering methods, CRUD matrix based
methods, and other methods, with the comparisons between these
methods for their advantages and disadvantages. Additionally, some
insufficiencies of study on CI are discussed, and the causes are
explained subsequently. Finally, it is concluded with some
significantly promising tendency about research on this problem.
Abstract: Support vector machines (SVMs) are considered to be
the best machine learning algorithms for minimizing the predictive
probability of misclassification. However, their drawback is that for
large data sets the computation of the optimal decision boundary is a
time consuming function of the size of the training set. Hence several
methods have been proposed to speed up the SVM algorithm. Here
three methods used to speed up the computation of the SVM
classifiers are compared experimentally using a musical genre
classification problem. The simplest method pre-selects a random
sample of the data before the application of the SVM algorithm. Two
additional methods use proximity graphs to pre-select data that are
near the decision boundary. One uses k-Nearest Neighbor graphs and
the other Relative Neighborhood Graphs to accomplish the task.
Abstract: It is an important task in Korean-English machine
translation to classify the gender of names correctly. When a sentence
is composed of two or more clauses and only one subject is given as a proper noun, it is important to find the gender of the proper noun
for correct translation of the sentence. This is because a singular pronoun has a gender in English while it does not in Korean. Thus,
in Korean-English machine translation, the gender of a proper noun should be determined. More generally, this task can be expanded into the classification of the general Korean names. This paper proposes a statistical method for this problem. By considering a name as just
a sequence of syllables, it is possible to get a statistics for each name from a collection of names. An evaluation of the proposed method
yields the improvement in accuracy over the simple looking-up of the
collection. While the accuracy of the looking-up method is 64.11%, that of the proposed method is 81.49%. This implies that the proposed
method is more plausible for the gender classification of the Korean names.
Abstract: Digital watermarking has become an important technique for copyright protection but its robustness against attacks remains a major problem. In this paper, we propose a normalizationbased robust image watermarking scheme. In the proposed scheme, original host image is first normalized to a standard form. Zernike transform is then applied to the normalized image to calculate Zernike moments. Dither modulation is adopted to quantize the magnitudes of Zernike moments according to the watermark bit stream. The watermark extracting method is a blind method. Security analysis and false alarm analysis are then performed. The quality degradation of watermarked image caused by the embedded watermark is visually transparent. Experimental results show that the proposed scheme has very high robustness against various image processing operations and geometric attacks.
Abstract: Transmission network expansion planning (TNEP) is
a basic part of power system planning that determines where, when
and how many new transmission lines should be added to the
network. Up till now, various methods have been presented to solve
the static transmission network expansion planning (STNEP)
problem. But in all of these methods, transmission expansion
planning considering network adequacy restriction has not been
investigated. Thus, in this paper, STNEP problem is being studied
considering network adequacy restriction using discrete particle
swarm optimization (DPSO) algorithm. The goal of this paper is
obtaining a configuration for network expansion with lowest
expansion cost and a specific adequacy. The proposed idea has been
tested on the Garvers network and compared with the decimal
codification genetic algorithm (DCGA). The results show that the
network will possess maximum efficiency economically. Also, it is
shown that precision and convergence speed of the proposed DPSO
based method for the solution of the STNEP problem is more than
DCGA approach.
Abstract: The Combination of path planning and path following is the main purpose of this paper. This paper describes the developed practical approach to motion control of the MRL small size robots. An intelligent controller is applied to control omni-directional robots motion in simulation and real environment respectively. The Brain Emotional Learning Based Intelligent Controller (BELBIC), based on LQR control is adopted for the omni-directional robots. The contribution of BELBIC in improving the control system performance is shown as application of the emotional learning in a real world problem. Optimizing of the control effort can be achieved in this method too. Next the implicit communication method is used to determine the high level strategies and coordination of the robots. Some simple rules besides using the environment as a memory to improve the coordination between agents make the robots' decision making system. With this simple algorithm our team manifests a desirable cooperation.
Abstract: Distant-talking voice-based HCI system suffers from
performance degradation due to mismatch between the acoustic
speech (runtime) and the acoustic model (training). Mismatch is
caused by the change in the power of the speech signal as observed at
the microphones. This change is greatly influenced by the change in
distance, affecting speech dynamics inside the room before reaching
the microphones. Moreover, as the speech signal is reflected, its
acoustical characteristic is also altered by the room properties. In
general, power mismatch due to distance is a complex problem. This
paper presents a novel approach in dealing with distance-induced
mismatch by intelligently sensing instantaneous voice power variation
and compensating model parameters. First, the distant-talking speech
signal is processed through microphone array processing, and the
corresponding distance information is extracted. Distance-sensitive
Gaussian Mixture Models (GMMs), pre-trained to capture both
speech power and room property are used to predict the optimal
distance of the speech source. Consequently, pre-computed statistic
priors corresponding to the optimal distance is selected to correct
the statistics of the generic model which was frozen during training.
Thus, model combinatorics are post-conditioned to match the power
of instantaneous speech acoustics at runtime. This results to an
improved likelihood in predicting the correct speech command at
farther distances. We experiment using real data recorded inside two
rooms. Experimental evaluation shows voice recognition performance
using our method is more robust to the change in distance compared
to the conventional approach. In our experiment, under the most
acoustically challenging environment (i.e., Room 2: 2.5 meters), our
method achieved 24.2% improvement in recognition performance
against the best-performing conventional method.