Abstract: The study of the Andaman Sea can be studied by
using the oceanic model; therefore the grid covering the study area
should be generated. This research aims to generate grid covering
the Andaman Sea, situated between longitudes 90◦E to 101◦E and
latitudes 1◦N to 18◦N. A horizontal grid is an orthogonal curvilinear
with 87 × 217 grid points. The methods used in this study are
cubic spline and bilinear interpolations. The boundary grid points
are generated by spline interpolation while the interior grid points
have to be specified by bilinear interpolation method. A vertical grid
is sigma coordinate with 15 layers of water column.
Abstract: Explosive forming is one of the unconventional
techniques in which, most commonly, the water is used as the
pressure transmission medium. One of the newest methods in
explosive forming is gas detonation forming which uses a normal
shock wave derived of gas detonation, to form sheet metals. For this
purpose a detonation is developed from the reaction of H2+O2
mixture in a long cylindrical detonation tube. The detonation wave
goes through the detonation tube and acts as a blast load on the steel
blank and forms it. Experimental results are compared with a finite
element model; and the comparison of the experimental and
numerical results obtained from strain, thickness variation and
deformed geometry is carried out. Numerical and experimental
results showed approximately 75 – 90 % similarity in formability of
desired shape. Also optimum percent of gas mixture obtained when
we mix 68% H2 with 32% O2.
Abstract: This paper presents preliminary results on modeling
and control of a quadrotor UAV. With aerodynamic concepts, a
mathematical model is firstly proposed to describe the dynamics
of the quadrotor UAV. Parameters of this model are identified by
experiments with Matlab Identify Toolbox. A group of PID controllers
are then designed based on the developed model. To verify
the developed model and controllers, simulations and experiments for
altitude control, position control and trajectory tracking are carried
out. The results show that the quadrotor UAV well follows the
referenced commands, which clearly demonstrates the effectiveness
of the proposed approach.
Abstract: Both the minimum energy consumption and
smoothness, which is quantified as a function of jerk, are generally
needed in many dynamic systems such as the automobile and the
pick-and-place robot manipulator that handles fragile equipments.
Nevertheless, many researchers come up with either solely
concerning on the minimum energy consumption or minimum jerk
trajectory. This research paper proposes a simple yet very interesting
when combining the minimum energy and jerk of indirect jerks
approaches in designing the time-dependent system yielding an
alternative optimal solution. Extremal solutions for the cost functions
of the minimum energy, the minimum jerk and combining them
together are found using the dynamic optimization methods together
with the numerical approximation. This is to allow us to simulate
and compare visually and statistically the time history of state inputs
employed by combining minimum energy and jerk designs. The
numerical solution of minimum direct jerk and energy problem are
exactly the same solution; however, the solutions from problem of
minimum energy yield the similar solution especially in term of
tendency.
Abstract: User-based Collaborative filtering (CF), one of the
most prevailing and efficient recommendation techniques, provides
personalized recommendations to users based on the opinions of other
users. Although the CF technique has been successfully applied in
various applications, it suffers from serious sparsity problems. The
cloud-model approach addresses the sparsity problems by
constructing the user-s global preference represented by a cloud
eigenvector. The user-based CF approach works well with dense
datasets while the cloud-model CF approach has a greater
performance when the dataset is sparse. In this paper, we present a
hybrid approach that integrates the predictions from both the
user-based CF and the cloud-model CF approaches. The experimental
results show that the proposed hybrid approach can ameliorate the
sparsity problem and provide an improved prediction quality.
Abstract: In mobile environments, unspecified numbers of transactions
arrive in continuous streams. To prove correctness of their
concurrent execution a method of modelling an infinite number of
transactions is needed. Standard database techniques model fixed
finite schedules of transactions. Lately, techniques based on temporal
logic have been proposed as suitable for modelling infinite schedules.
The drawback of these techniques is that proving the basic
serializability correctness condition is impractical, as encoding (the
absence of) conflict cyclicity within large sets of transactions results
in prohibitively large temporal logic formulae. In this paper, we show
that, under certain common assumptions on the graph structure of
data items accessed by the transactions, conflict cyclicity need only
be checked within all possible pairs of transactions. This results in
formulae of considerably reduced size in any temporal-logic-based
approach to proving serializability, and scales to arbitrary numbers
of transactions.
Abstract: This paper presents the design and implementation of
the WebGD, a CORBA-based document classification and retrieval
system on Internet. The WebGD makes use of such techniques as Web,
CORBA, Java, NLP, fuzzy technique, knowledge-based processing
and database technology. Unified classification and retrieval model,
classifying and retrieving with one reasoning engine and flexible
working mode configuration are some of its main features. The
architecture of WebGD, the unified classification and retrieval model,
the components of the WebGD server and the fuzzy inference engine
are discussed in this paper in detail.
Abstract: In order to develop forest management strategies in
tropical forest in Malaysia, surveying the forest resources and
monitoring the forest area affected by logging activities is essential.
There are tremendous effort has been done in classification of land
cover related to forest resource management in this country as it is a
priority in all aspects of forest mapping using remote sensing and
related technology such as GIS. In fact classification process is a
compulsory step in any remote sensing research. Therefore, the main
objective of this paper is to assess classification accuracy of
classified forest map on Landsat TM data from difference number of
reference data (200 and 388 reference data). This comparison was
made through observation (200 reference data), and interpretation
and observation approaches (388 reference data). Five land cover
classes namely primary forest, logged over forest, water bodies, bare
land and agricultural crop/mixed horticultural can be identified by
the differences in spectral wavelength. Result showed that an overall
accuracy from 200 reference data was 83.5 % (kappa value
0.7502459; kappa variance 0.002871), which was considered
acceptable or good for optical data. However, when 200 reference
data was increased to 388 in the confusion matrix, the accuracy
slightly improved from 83.5% to 89.17%, with Kappa statistic
increased from 0.7502459 to 0.8026135, respectively. The accuracy
in this classification suggested that this strategy for the selection of
training area, interpretation approaches and number of reference data
used were importance to perform better classification result.
Abstract: Construction projects generally take place in
uncontrolled and dynamic environments where construction waste is
a serious environmental problem in many large cities. The total
amount of waste and carbon dioxide emissions from transportation
vehicles are still out of control due to increasing construction
projects, massive urban development projects and the lack of
effective tools for minimizing adverse environmental impacts in
construction. This research is about utilization of the integrated
applications of automated advanced tracking and data storage
technologies in the area of environmental management to monitor
and control adverse environmental impacts such as construction
waste and carbon dioxide emissions. Radio Frequency Identification
(RFID) integrated with the Global Position System (GPS) provides
an opportunity to uniquely identify materials, components, and
equipments and to locate and track them using minimal or no worker
input. The transmission of data to the central database will be carried
out with the help of Global System for Mobile Communications
(GSM).
Abstract: Model Predictive Control (MPC) is increasingly being
proposed for real time applications and embedded systems. However
comparing to PID controller, the implementation of the MPC in
miniaturized devices like Field Programmable Gate Arrays (FPGA)
and microcontrollers has historically been very small scale due to its
complexity in implementation and its computation time requirement.
At the same time, such embedded technologies have become an
enabler for future manufacturing enterprises as well as a transformer
of organizations and markets. Recently, advances in microelectronics
and software allow such technique to be implemented in embedded
systems. In this work, we take advantage of these recent advances
in this area in the deployment of one of the most studied and
applied control technique in the industrial engineering. In fact in
this paper, we propose an efficient framework for implementation
of Generalized Predictive Control (GPC) in the performed STM32
microcontroller. The STM32 keil starter kit based on a JTAG interface
and the STM32 board was used to implement the proposed GPC
firmware. Besides the GPC, the PID anti windup algorithm was
also implemented using Keil development tools designed for ARM
processor-based microcontroller devices and working with C/Cµ
langage. A performances comparison study was done between both
firmwares. This performances study show good execution speed and
low computational burden. These results encourage to develop simple
predictive algorithms to be programmed in industrial standard hardware.
The main features of the proposed framework are illustrated
through two examples and compared with the anti windup PID
controller.
Abstract: In this work, we developed the concept of
supercompression, i.e., compression above the compression standard
used. In this context, both compression rates are multiplied. In fact,
supercompression is based on super-resolution. That is to say,
supercompression is a data compression technique that superpose
spatial image compression on top of bit-per-pixel compression to
achieve very high compression ratios. If the compression ratio is very
high, then we use a convolutive mask inside decoder that restores the
edges, eliminating the blur. Finally, both, the encoder and the
complete decoder are implemented on General-Purpose computation
on Graphics Processing Units (GPGPU) cards. Specifically, the
mentio-ned mask is coded inside texture memory of a GPGPU.
Abstract: In this paper, we propose a fully-utilized, block-based 2D DWT (discrete wavelet transform) architecture, which consists of four 1D DWT filters with two-channel QMF lattice structure. The proposed architecture requires about 2MN-3N registers to save the intermediate results for higher level decomposition, where M and N stand for the filter length and the row width of the image respectively. Furthermore, the proposed 2D DWT processes in horizontal and vertical directions simultaneously without an idle period, so that it computes the DWT for an N×N image in a period of N2(1-2-2J)/3. Compared to the existing approaches, the proposed architecture shows 100% of hardware utilization and high throughput rates. To mitigate the long critical path delay due to the cascaded lattices, we can apply the pipeline technique with four stages, while retaining 100% of hardware utilization. The proposed architecture can be applied in real-time video signal processing.
Abstract: In this paper a study on the vibration of thin
cylindrical shells with ring supports and made of functionally graded
materials (FGMs) composed of stainless steel and nickel is presented.
Material properties vary along the thickness direction of the shell
according to volume fraction power law. The cylindrical shells have
ring supports which are arbitrarily placed along the shell and impose
zero lateral deflections. The study is carried out based on third order
shear deformation shell theory (T.S.D.T). The analysis is carried out
using Hamilton-s principle. The governing equations of motion of
FGM cylindrical shells are derived based on shear deformation
theory. Results are presented on the frequency characteristics,
influence of ring support position and the influence of boundary
conditions. The present analysis is validated by comparing results
with those available in the literature.
Abstract: The development of entrepreneurial competences of
farmers has been pointed out as a necessary condition for the
modernization of land in facing the phenomenon of globalization.
However, the educational processes involved in such a development
have been studied little, especially in emerging economies. This
research aims to enlighten some of the critical issues behind the early
stages of the transformation of farmers into entrepreneurs, through in
depth interviews with farmers, entrepreneurial promoters and public
officials participating in a public pilot project in Mexico. Although
major impacts were expected only in the long run, important positive
changes in the mind set of farmers and other participants were found
in early stages of the intervention. Apparently, the farmers started a
process of becoming more conscious about the importance of
preserving the aquiferous resources, as well as more market and
entrepreneurial oriented.
Abstract: In view of the good properties of nonstationary wavelet frames and the better flexibility of wavelets in Sobolev spaces, the nonstationary dual wavelet frames in a pair of dual Sobolev spaces are studied in this paper. We mainly give the oblique extension principle and the mixed extension principle for nonstationary dual wavelet frames in a pair of dual Sobolev spaces Hs(Rd) and H-s(Rd).
Abstract: Face recognition is a technique to automatically
identify or verify individuals. It receives great attention in
identification, authentication, security and many more applications.
Diverse methods had been proposed for this purpose and also a lot of
comparative studies were performed. However, researchers could not
reach unified conclusion. In this paper, we are reporting an extensive
quantitative accuracy analysis of four most widely used face
recognition algorithms: Principal Component Analysis (PCA),
Independent Component Analysis (ICA), Linear Discriminant
Analysis (LDA) and Support Vector Machine (SVM) using AT&T,
Sheffield and Bangladeshi people face databases under diverse
situations such as illumination, alignment and pose variations.
Abstract: We constructed a method of phase unwrapping for a typical wave-front by utilizing the maximizer of the posterior marginal (MPM) estimate corresponding to equilibrium statistical mechanics of the three-state Ising model on a square lattice on the basis of an analogy between statistical mechanics and Bayesian inference. We investigated the static properties of an MPM estimate from a phase diagram using Monte Carlo simulation for a typical wave-front with synthetic aperture radar (SAR) interferometry. The simulations clarified that the surface-consistency conditions were useful for extending the phase where the MPM estimate was successful in phase unwrapping with a high degree of accuracy and that introducing prior information into the MPM estimate also made it possible to extend the phase under the constraint of the surface-consistency conditions with a high degree of accuracy. We also found that the MPM estimate could be used to reconstruct the original wave-fronts more smoothly, if we appropriately tuned hyper-parameters corresponding to temperature to utilize fluctuations around the MAP solution. Also, from the viewpoint of statistical mechanics of the Q-Ising model, we found that the MPM estimate was regarded as a method for searching the ground state by utilizing thermal fluctuations under the constraint of the surface-consistency condition.
Abstract: The unanticipated brittle fracture of connection of the
steel moment resisting frame (SMRF) occurred in 1994 the Northridge
earthquake. Since then, the researches for the vulnerability of
connection of the existing SMRF and for rehabilitation of those
buildings were conducted. This paper suggests performance-based
optimal seismic retrofit technique using connection upgrade. For
optimal design, a multi-objective genetic algorithm(NSGA-II) is used.
One of the two objective functions is to minimize initial cost and
another objective function is to minimize lifetime seismic damages
cost. The optimal algorithm proposed in this paper is performed
satisfying specified performance objective based on FEMA 356. The
nonlinear static analysis is performed for structural seismic
performance evaluation. A numerical example of SAC benchmark
SMRF is provided using the performance-based optimal seismic
retrofit technique proposed in this paper
Abstract: In this paper we improve the quasilinearization method by barycentric Lagrange interpolation because of its numerical stability and computation speed to achieve a stable semi analytical solution. Then we applied the improved method for solving the Fin problem which is a nonlinear equation that occurs in the heat transferring. In the quasilinearization approach the nonlinear differential equation is treated by approximating the nonlinear terms by a sequence of linear expressions. The modified QLM is iterative but not perturbative and gives stable semi analytical solutions to nonlinear problems without depending on the existence of a smallness parameter. Comparison with some numerical solutions shows that the present solution is applicable.
Abstract: The purpose of this study is to find natural gait of
biped robot such as human being by analyzing the COG (Center Of
Gravity) trajectory of human being's gait. It is discovered that human
beings gait naturally maintain the stability and use the minimum
energy. This paper intends to find the natural gait pattern of biped
robot using the minimum energy as well as maintaining the stability by
analyzing the human's gait pattern that is measured from gait image on
the sagittal plane and COG trajectory on the frontal plane. It is not
possible to apply the torques of human's articulation to those of biped
robot's because they have different degrees of freedom. Nonetheless,
human and 5-link biped robots are similar in kinematics. For this, we
generate gait pattern of the 5-link biped robot by using the GA
algorithm of adaptation gait pattern which utilize the human's ZMP
(Zero Moment Point) and torque of all articulation that are measured
from human's gait pattern. The algorithm proposed creates biped
robot's fluent gait pattern as that of human being's and to minimize
energy consumption because the gait pattern of the 5-link biped robot
model is modeled after consideration about the torque of human's each
articulation on the sagittal plane and ZMP trajectory on the frontal
plane. This paper demonstrate that the algorithm proposed is superior
by evaluating 2 kinds of the 5-link biped robot applied to each gait
patterns generated both in the general way using inverse kinematics
and in the special way in which by considering visuality and
efficiency.