Abstract: This paper describes the design concepts and
implementation of a 5-Joint mechanical arm for a rescue robot named
CEO Mission II. The multi-joint arm is a five degree of freedom
mechanical arm with a four bar linkage, which can be stretched to
125 cm. long. It is controlled by a teleoperator via the user-friendly
control and monitoring GUI program. With Inverse Kinematics
principle, we developed the method to control the servo angles of all
arm joints to get the desired tip position. By clicking the determined
tip position or dragging the tip of the mechanical arm on the
computer screen to the desired target point, the robot will compute
and move its multi-joint arm to the pose as seen on the GUI screen.
The angles of each joint are calculated and sent to all joint servos
simultaneously in order to move the mechanical arm to the desired
pose at once. The operator can also use a joystick to control the
movement of this mechanical arm and the locomotion of the robot.
Many sensors are installed at the tip of this mechanical arm for
surveillance from the high level and getting the vital signs of victims
easier and faster in the urban search and rescue tasks. It works very
effectively and easy to control. This mechanical arm and its software
were developed as a part of the CEO Mission II Rescue Robot that
won the First Runner Up award and the Best Technique award from
the Thailand Rescue Robot Championship 2006. It is a low cost,
simple, but functioning 5-Jiont mechanical arm which is built from
scratch, and controlled via wireless LAN 802.11b/g. This 5-Jiont
mechanical arm hardware concept and its software can also be used
as the basic mechatronics to many real applications.
Abstract: Biclustering is a very useful data mining technique for
identifying patterns where different genes are co-related based on a
subset of conditions in gene expression analysis. Association rules
mining is an efficient approach to achieve biclustering as in
BIMODULE algorithm but it is sensitive to the value given to its
input parameters and the discretization procedure used in the
preprocessing step, also when noise is present, classical association
rules miners discover multiple small fragments of the true bicluster,
but miss the true bicluster itself. This paper formally presents a
generalized noise tolerant bicluster model, termed as μBicluster. An
iterative algorithm termed as BIDENS based on the proposed model
is introduced that can discover a set of k possibly overlapping
biclusters simultaneously. Our model uses a more flexible method to
partition the dimensions to preserve meaningful and significant
biclusters. The proposed algorithm allows discovering biclusters that
hard to be discovered by BIMODULE. Experimental study on yeast,
human gene expression data and several artificial datasets shows that
our algorithm offers substantial improvements over several
previously proposed biclustering algorithms.
Abstract: Research has suggested that implicit learning tasks
may rely on episodic processing to generate above chance
performance on the standard classification tasks. The current
research examines the invariant features task (McGeorge and Burton,
1990) and argues that such episodic processing is indeed important.
The results of the experiment suggest that both rejection and
similarity strategies are used by participants in this task to
simultaneously reject unfamiliar items and to accept (falsely) familiar
items. Primarily these decisions are based on the presence of low or
high frequency goal based features of the stimuli presented in the
incidental learning phase. It is proposed that a goal based analysis of
the incidental learning task provides a simple step in understanding
which features of the episodic processing are most important for
explaining the match between incidental, implicit learning and test
performance.
Abstract: Cardiac pulse-related artifacts in the EEG recorded
simultaneously with fMRI are complex and highly variable. Their
effective removal is an unsolved problem. Our aim is to develop an
adaptive removal algorithm based on the matching pursuit (MP)
technique and to compare it to established methods using a visual
evoked potential (VEP). We recorded the VEP inside the static
magnetic field of an MR scanner (with artifacts) as well as in an
electrically shielded room (artifact free). The MP-based artifact
removal outperformed average artifact subtraction (AAS) and
optimal basis set removal (OBS) in terms of restoring the EEG field
map topography of the VEP. Subsequently, a dipole model was fitted
to the VEP under each condition using a realistic boundary element
head model. The source location of the VEP recorded inside the MR
scanner was closest to that of the artifact free VEP after cleaning
with the MP-based algorithm as well as with AAS. While none of the
tested algorithms offered complete removal, MP showed promising
results due to its ability to adapt to variations of latency, frequency
and amplitude of individual artifact occurrences while still utilizing a
common template.
Abstract: The existing image coding standards generally degrades at low bit-rates because of the underlying block based Discrete Cosine Transform 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 such as orthogonality, short support, linear phase symmetry, and a high order of approximation through vanishing moments simultaneously, which are very much essential for signal processing. New class of wavelets called 'Multiwavelets' which posses more than one scaling function overcomes this problem. This paper presents a new image coding scheme based on non linear approximation of multiwavelet coefficients along with multistage vector quantization. The performance of the proposed scheme is compared with the results obtained from scalar wavelets.
Abstract: Ground-source heat pumps achieve higher efficiencies
than conventional air-source heat pumps because they exchange heat
with the ground that is cooler in summer and hotter in winter than the
air environment. Earth heat exchangers are essential parts of the
ground-source heat pumps and the accurate prediction of their
performance is of fundamental importance. This paper presents the
development and validation of a numerical model through an
incompressible fluid flow, for the simulation of energy and
temperature changes in and around a U-tube borehole heat
exchanger. The FlexPDE software is used to solve the resulting
simultaneous equations that model the heat exchanger. The validated
model (through a comparison with experimental data) is then used to
extract conclusions on how various parameters like the U-tube
diameter, the variation of the ground thermal conductivity and
specific heat and the borehole filling material affect the temperature
of the fluid.
Abstract: In this paper, Speed Sensorless Indirect Field Oriented Control (IFOC) of a Permanent Magnet Synchronous machine (PMSM) is studied. The closed loop scheme of the drive system utilizes fuzzy speed and current controllers. Due to the well known drawbacks of the speed sensor, an algorithm is proposed in this paper to eliminate it. In fact, based on the model of the PMSM, the stator currents and rotor speed are estimated simultaneously using adaptive Luenberger observer for currents and MRAS (Model Reference Adaptive System) observer for rotor speed. To overcome the sensivity of this algorithm against parameter variation, adaptive for on line stator resistance tuning is proposed. The validity of the proposed method is verified by an extensive simulation work.
Abstract: We present a dual-band (Cellular & PCS) dual-path
zero-IF receiver for CDMA2000 diversity, monitoring and
simultaneous-GPS. The secondary path is a SAW-less diversity
CDMA receiver which can be also used for advanced features like
monitoring when supported with an additional external VCO. A GPS
receiver is integrated with its dedicated VCO allowing simultaneous
positioning during a cellular call. The circuit is implemented in a
0.25μm 40GHz-fT BiCMOS process and uses a HVQFN 56-pin
package. It consumes a maximum 300mW from a 2.8V supply in
dual-modes. The chip area is 12.8mm2.
Abstract: In this article, the design of a Supply Chain Network
(SCN) consisting of several suppliers, production plants, distribution
centers and retailers, is considered. Demands of retailers are
considered stochastic parameters, so we generate amounts of data via
simulation to extract a few demand scenarios. Then a mixed integer
two-stage programming model is developed to optimize
simultaneously two objectives: (1) minimization the fixed and
variable cost, (2) maximization the service level. A weighting method
is utilized to solve this two objective problem and a numerical
example is made to show the performance of the model.
Abstract: The concept of e-government has begun to spread among countries. It is based on the use of information communication technology (ICT) to fully utilize government resources, as well as to provide government services to citizens, investors and foreigners. Critical factors are the factors that are determined by the senior management of each organization; the success or failure of the organization depends on the effective implementation of critical factors. These factors vary from one organization to another according to their activity, size and functions. It is very important that organizations identify them in order to avoid the risk of implementing initiatives that may fail to work, while simultaneously exploiting opportunities that may succeed in working. The main focus of this paper is to investigate the majority of critical success factors (CSFs) associated with the implementation of e-government projects. This study concentrates on both technical and nontechnical factors. This paper concludes by listing the majority of CSFs relating to successful e-government implementation in Bahrain.
Abstract: The genetic algorithm (GA) based solution techniques
are found suitable for optimization because of their ability of
simultaneous multidimensional search. Many GA-variants have been
tried in the past to solve optimal power flow (OPF), one of the
nonlinear problems of electric power system. The issues like
convergence speed and accuracy of the optimal solution obtained
after number of generations using GA techniques and handling
system constraints in OPF are subjects of discussion. The results
obtained for GA-Fuzzy OPF on various power systems have shown
faster convergence and lesser generation costs as compared to other
approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF)
using penalty factors to handle line flow constraints and load
bus voltage limits for both normal network and contingency case
with congestion. In addition to crossover and mutation rate
adaptation scheme that adapts crossover and mutation probabilities
for each generation based on fitness values of previous generations, a
block swap operator is also incorporated in proposed EGA-OPF. The
line flow limits and load bus voltage magnitude limits are handled by
incorporating line overflow and load voltage penalty factors
respectively in each chromosome fitness function. The effects of
different penalty factors settings are also analyzed under contingent
state.
Abstract: In this paper, multiobjective design of multi-machine Power System Stabilizers (PSSs) using Particle Swarm Optimization (PSO) is presented. The stabilizers are tuned to simultaneously shift the lightly damped and undamped electro-mechanical modes of all machines to a prescribed zone in the s-plane. A multiobjective problem is formulated to optimize a composite set of objective functions comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes. The PSSs parameters tuning problem is converted to an optimization problem which is solved by PSO with the eigenvalue-based multiobjective function. The proposed PSO based PSSs is tested on a multimachine power system under different operating conditions and disturbances through eigenvalue analysis and some performance indices to illustrate its robust performance.
Abstract: Machining is an important manufacturing process used to produce a wide variety of metallic parts. Among various machining processes, turning is one of the most important one which is employed to shape cylindrical parts. In turning, the quality of finished product is measured in terms of surface roughness. In turn, surface quality is determined by machining parameters and tool geometry specifications. The main objective of this study is to simultaneously model and optimize machining parameters and tool geometry in order to improve the surface roughness for AISI1045 steel. Several levels of machining parameters and tool geometry specifications are considered as input parameters. The surface roughness is selected as process output measure of performance. A Taguchi approach is employed to gather experimental data. Then, based on signal-to-noise (S/N) ratio, the best sets of cutting parameters and tool geometry specifications have been determined. Using these parameters values, the surface roughness of AISI1045 steel parts may be minimized. Experimental results are provided to illustrate the effectiveness of the proposed approach.
Abstract: Bead-on-plate welds were carried out on AISI 316L
(N) austenitic stainless steel (ASS) using flux cored arc welding
(FCAW) process. The bead on plates weld was conducted as per L25
orthogonal array. In this paper, the weld bead geometry such as depth
of penetration (DOP), bead width (BW) and weld reinforcement (R)
of AISI 316L (N) ASS are investigated. Taguchi approach is used as
statistical design of experiment (DOE) technique for optimizing the
selected welding input parameters. Grey relational analysis and
desirability approach are applied to optimize the input parameters
considering multiple output variables simultaneously. Confirmation
experiment has also been conducted to validate the optimized
parameters.
Abstract: This paper aims to propose a novel, robust, and simple method for obtaining a human 3D face model and camera pose (position and orientation) from a video sequence. Given a video sequence of a face recorded from an off-the-shelf digital camera, feature points used to define facial parts are tracked using the Active- Appearance Model (AAM). Then, the face-s 3D structure and camera pose of each video frame can be simultaneously calculated from the obtained point correspondences. This proposed method is primarily based on the combined approaches of Gradient Descent and Powell-s Multidimensional Minimization. Using this proposed method, temporarily occluded point including the case of self-occlusion does not pose a problem. As long as the point correspondences displayed in the video sequence have enough parallax, these missing points can still be reconstructed.
Abstract: As a result of the daily workflow in the design
development departments of companies, databases containing huge
numbers of 3D geometric models are generated. According to the
given problem engineers create CAD drawings based on their design
ideas and evaluate the performance of the resulting design, e.g. by
computational simulations. Usually, new geometries are built either
by utilizing and modifying sets of existing components or by adding
single newly designed parts to a more complex design.
The present paper addresses the two facets of acquiring
components from large design databases automatically and providing
a reasonable overview of the parts to the engineer. A unified
framework based on the topographic non-negative matrix
factorization (TNMF) is proposed which solves both aspects
simultaneously. First, on a given database meaningful components
are extracted into a parts-based representation in an unsupervised
manner. Second, the extracted components are organized and
visualized on square-lattice 2D maps. It is shown on the example of
turbine-like geometries that these maps efficiently provide a wellstructured
overview on the database content and, at the same time,
define a measure for spatial similarity allowing an easy access and
reuse of components in the process of design development.
Abstract: Microarrays technique allows the simultaneous measurements of the expression levels of thousands of mRNAs. By mining this data one can identify the dynamics of the gene expression time series. By recourse of principal component analysis, we uncover the circadian rhythmic patterns underlying the gene expression profiles from Cyanobacterium Synechocystis. We applied PCA to reduce the dimensionality of the data set. Examination of the components also provides insight into the underlying factors measured in the experiments. Our results suggest that all rhythmic content of data can be reduced to three main components.
Abstract: The rate of nitrate adsorption by a nitrate selective ion
exchange resin was investigated in a well-stirred batch experiments.
The kinetic experimental data were simulated with diffusion models including external mass transfer, particle diffusion and chemical
adsorption. Particle pore volume diffusion and particle surface diffusion were taken into consideration separately and simultaneously
in the modeling. The model equations were solved numerically using the Crank-Nicholson scheme. An optimization technique was
employed to optimize the model parameters. All nitrate concentration
decay data were well described with the all diffusion models. The
results indicated that the kinetic process is initially controlled by external mass transfer and then by particle diffusion. The external
mass transfer coefficient and the coefficients of pore volume diffusion and surface diffusion in all experiments were close to each
other with the average value of 8.3×10-3 cm/S for external mass
transfer coefficient. In addition, the models are more sensitive to the
mass transfer coefficient in comparison with particle diffusion. Moreover, it seems that surface diffusion is the dominant particle
diffusion in comparison with pore volume diffusion.
Abstract: In synchronized games players make their moves simultaneously
rather than alternately. Synchronized Quadromineering is
the synchronized version of Quadromineering, a variants of a classical
two-player combinatorial game called Domineering. Experimental
results for small m × n boards (with m + n < 15) and some
theoretical results for general k × n boards (with k = 4, 5, 6) are
presented. Moreover, some Synchronized Quadromineering variants
are also investigated.
Abstract: novel and simple method is introduced for rapid and
highly efficient water treatment by reverse osmosis (RO) method using
multi-walled carbon nanotubes (MWCNTs) / polyacrylonitrile (PAN)
polymer as a flexible, highly efficient, reusable and semi-permeable
mixed matrix membrane (MMM). For this purpose, MWCNTs were
directly synthesized and on-line purified by chemical vapor deposition
(CVD) process, followed by directing the MWCNT bundles towards an
ultrasonic bath, in which PAN polymer was simultaneously suspended
inside a solid porous silica support in water at temperature to ~70 οC.
Fabrication process of MMM was finally completed by hot isostatic
pressing (HIP) process. In accordance with the analytical figures of
merit, the efficiency of fabricated MMM was ~97%. The rate of water
treatment process was also evaluated to 6.35 L min-1. The results reveal
that, the CNT-based MMM is suitable for rapid treatment of different
forms of industrial, sea, drinking and well water samples.