Abstract: Electro Discharge Sawing is a hybrid process
combining the features of SEDM and ECM. Its major characteristic is
extremely fast erosion rate compare to either of the above processes.
This paper brings out its relative feature of SEDM and EDS about
their erosion rates, surface roughness, and morphology of machined
surfaces.
Abstract: This study deals with a multi-criteria optimization
problem which has been transformed into a single objective
optimization problem using Response Surface Methodology (RSM),
Artificial Neural Network (ANN) and Grey Relational Analyses
(GRA) approach. Grey-RSM and Grey-ANN are hybrid techniques
which can be used for solving multi-criteria optimization problem.
There have been two main purposes of this research as follows.
1. To determine optimum and robust fiber dyeing process
conditions by using RSM and ANN based on GRA,
2. To obtain the best suitable model by comparing models
developed by different methodologies.
The design variables for fiber dyeing process in textile are
temperature, time, softener, anti-static, material quantity, pH,
retarder, and dispergator. The quality characteristics to be evaluated
are nominal color consistency of fiber, maximum strength of fiber,
minimum color of dyeing solution. GRA-RSM with exact level
value, GRA-RSM with interval level value and GRA-ANN models
were compared based on GRA output value and MSE (Mean Square
Error) performance measurement of outputs with each other. As a
result, GRA-ANN with interval value model seems to be suitable
reducing the variation of dyeing process for GRA output value of the
model.
Abstract: This paper presents the modeling and simulation of a hybrid proton exchange membrane fuel cell (PEMFC) with an energy storage system for use in a stand-alone distributed generation (DG) system. The simulation model consists of fuel cell DG, lead-acid battery, maximum power point tracking and power conditioning unit which is modeled in the MATLAB/Simulink platform. Poor loadfollowing characteristics and slow response to rapid load changes are some of the weaknesses of PEMFC because of the gas processing reaction and the fuel cell dynamics. To address the load-tracking issues in PEMFC, a hybrid PEMFC and battery storage system is considered and modelled. The model utilizes PEMFC as the main energy source whereas the battery functions as energy storage to compensate for the limitations of PEMFC.Simulation results are given to show the overall system performance under light and heavyloading conditions.
Abstract: The Reverse Monte Carlo (RMC) simulation is applied in the study of an aqueous electrolyte LiCl6H2O. On the basis of the available experimental neutron scattering data, RMC computes pair radial distribution functions in order to explore the structural features of the system. The obtained results include some unrealistic features. To overcome this problem, we use the Hybrid Reverse Monte Carlo (HRMC), incorporating an energy constraint in addition to the commonly used constraints derived from experimental data. Our results show a good agreement between experimental and computed partial distribution functions (PDFs) as well as a significant improvement in pair partial distribution curves. This kind of study can be considered as a useful test for a defined interaction model for conventional simulation techniques.
Abstract: Displacement measurement was conducted on compact normal and shear specimens made of acrylic homogeneous material subjected to mixed-mode loading by digital image correlation. The intelligent hybrid method proposed by Nishioka et al. was applied to the stress-strain analysis near the crack tip. The accuracy of stress-intensity factor at the free surface was discussed from the viewpoint of both the experiment and 3-D finite element analysis. The surface images before and after deformation were taken by a CMOS camera, and we developed the system which enabled the real time stress analysis based on digital image correlation and inverse problem analysis. The great portion of processing time of this system was spent on displacement analysis. Then, we tried improvement in speed of this portion. In the case of cracked body, it is also possible to evaluate fracture mechanics parameters such as the J integral, the strain energy release rate, and the stress-intensity factor of mixed-mode. The 9-points elliptic paraboloid approximation could not analyze the displacement of submicron order with high accuracy. The analysis accuracy of displacement was improved considerably by introducing the Newton-Raphson method in consideration of deformation of a subset. The stress-intensity factor was evaluated with high accuracy of less than 1% of the error.
Abstract: Global approximation using metamodel for complex
mathematical function or computer model over a large variable
domain is often needed in sensibility analysis, computer simulation,
optimal control, and global design optimization of complex, multiphysics
systems. To overcome the limitations of the existing
response surface (RS), surrogate or metamodel modeling methods for
complex models over large variable domain, a new adaptive and
regressive RS modeling method using quadratic functions and local
area model improvement schemes is introduced. The method applies
an iterative and Latin hypercube sampling based RS update process,
divides the entire domain of design variables into multiple cells,
identifies rougher cells with large modeling error, and further divides
these cells along the roughest dimension direction. A small number
of additional sampling points from the original, expensive model are
added over the small and isolated rough cells to improve the RS
model locally until the model accuracy criteria are satisfied. The
method then combines local RS cells to regenerate the global RS
model with satisfactory accuracy. An effective RS cells sorting
algorithm is also introduced to improve the efficiency of model
evaluation. Benchmark tests are presented and use of the new
metamodeling method to replace complex hybrid electrical vehicle
powertrain performance model in vehicle design optimization and
optimal control are discussed.
Abstract: This paper presented a theoretical and numerical investigation of the Compact Antenna Test Range (CATR) equipped with Super Hybrid Modulated Segmented Exponential Serrations (SHMSES). The investigation was based on diffraction theory and, more specifically, the Fresnel diffraction formulation. The CATR provides uniform illumination within the Fresnel region to test antenna. Application of serrated edges has been shown to be a good method to control diffraction at the edges of the reflectors. However, in order to get some insight into the positive effect of serrated edges a less rigorous analysis technique known as Physical Optics (PO) may be used. Ripple free and enhanced quiet zone width are observed for specific values of width and height modulation factors per serrations. The performance of SHMSE serrated reflector is evaluated in order to observe the effects of edge diffraction on the test zone fields.
Abstract: The recent trend has been using hybrid approach rather than using a single intelligent technique to solve the problems. In this paper, we describe and discuss a framework to develop enterprise solutions that are backed by intelligent techniques. The framework not only uses intelligent techniques themselves but it is a complete environment that includes various interfaces and components to develop the intelligent solutions. The framework is completely Web-based and uses XML extensively. It can work like shared plat-form to be accessed by multiple developers, users and decision makers.
Abstract: In this paper performance of Puma 560
manipulator is being compared for hybrid gradient descent
and least square method learning based ANFIS controller with
hybrid Genetic Algorithm and Generalized Pattern Search
tuned radial basis function based Neuro-Fuzzy controller.
ANFIS which is based on Takagi Sugeno type Fuzzy
controller needs prior knowledge of rule base while in radial
basis function based Neuro-Fuzzy rule base knowledge is not
required. Hybrid Genetic Algorithm with generalized Pattern
Search is used for tuning weights of radial basis function
based Neuro- fuzzy controller. All the controllers are checked
for butterfly trajectory tracking and results in the form of
Cartesian and joint space errors are being compared. ANFIS
based controller is showing better performance compared to
Radial Basis Function based Neuro-Fuzzy Controller but rule
base independency of RBF based Neuro-Fuzzy gives it an
edge over ANFIS
Abstract: The development of biomimetic micro-aerial-vehicles
(MAVs) with flapping wings is the future trend in military/domestic
field. The successful flight of MAVs is strongly related to the
understanding of unsteady aerodynamic performance of low Reynolds
number airfoils under dynamic flapping motion. This study explored
the effects of flapping frequency, stroke amplitude, and the inclined
angle of stroke plane on lift force and thrust force of a bio-inspiration
corrugated airfoil with 33 full factorial design of experiment and
ANOVA analysis. Unsteady vorticity flows over a corrugated thin
airfoil executing flapping motion are computed with time-dependent
two-dimensional laminar incompressible Reynolds-averaged
Navier-Stokes equations with the conformal hybrid mesh. The tested
freestream Reynolds number based on the chord length of airfoil as
characteristic length is fixed of 103. The dynamic mesh technique is
applied to model the flapping motion of a corrugated airfoil. Instant
vorticity contours over a complete flapping cycle clearly reveals the
flow mechanisms for lift force generation are dynamic stall, rotational
circulation, and wake capture. The thrust force is produced as the
leading edge vortex shedding from the trailing edge of airfoil to form a
reverse von Karman vortex. Results also indicated that the inclined
angle is the most significant factor on both the lift force and thrust
force. There are strong interactions between tested factors which mean
an optimization study on parameters should be conducted in further
runs.
Abstract: A numerical method for solving nonlinear Fredholm integral equations of second kind is proposed. The Fredholm type equations which have many applications in mathematical physics are then considered. The method is based on hybrid function approximations. The properties of hybrid of block-pulse functions and Chebyshev polynomials are presented and are utilized to reduce the computation of nonlinear Fredholm integral equations to a system of nonlinear. Some numerical examples are selected to illustrate the effectiveness and simplicity of the method.
Abstract: Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.
Abstract: The renewable energy has been attracting attention as
a new alternative energy due to the problem of environmental
pollution and resource depletion. In particular, daylighting and PV
system are regarded as the solutions. In this paper, the hybrid
dimming control system supplied by solar cell and daylighting
system was designed. Daylighting system is main source and PV
system is spare source. PV system operates the LED lamp which
supports daylighting system because daylighting system is unstable
due to the variation of irradiance. In addition, PV system has a role
charging batteries. Battery charging has a benefit that PV system
operate LED lamp in the bad weather. However, LED lamp always
can`t turn on that-s why dimming control system was designed. In
particular, the solar charging robot was designed to check the
interior irradiance intensity. These systems and the application of
the solar charging robot are expected to contribute developing
alternative energy in the near future.
Abstract: Because nodes are usually battery-powered, the energy
presents a very scarce resource in wireless sensor networks. For this
reason, the design of medium access control had to take energy
efficiency as one of its hottest concerns. Accordingly, in order to
improve the energy performance of MAC schemes in wireless sensor
networks, several ways can be followed. In fact, some researchers try
to limit idle listening while others focus on mitigating overhearing
(i.e. a node can hear a packet which is destined to another node)
or reducing the number of the used control packets. We, in this
paper, propose a new hybrid MAC protocol termed ELE-MAC
(i.e. Energy Latency Efficient MAC). The ELE-MAC major design
goals are energy and latency efficiencies. It adopts less control
packets than SMAC in order to preserve energy. We carried out ns-
2 simulations to evaluate the performance of the proposed protocol.
Thus, our simulation-s results prove the ELE-MAC energy efficiency.
Additionally, our solution performs statistically the same or better
latency characteristic compared to adaptive SMAC.
Abstract: We present a hybrid architecture of recurrent neural
networks (RNNs) inspired by hidden Markov models (HMMs). We
train the hybrid architecture using genetic algorithms to learn and
represent dynamical systems. We train the hybrid architecture on a
set of deterministic finite-state automata strings and observe the
generalization performance of the hybrid architecture when presented
with a new set of strings which were not present in the training data
set. In this way, we show that the hybrid system of HMM and RNN
can learn and represent deterministic finite-state automata. We ran
experiments with different sets of population sizes in the genetic
algorithm; we also ran experiments to find out which weight
initializations were best for training the hybrid architecture. The
results show that the hybrid architecture of recurrent neural networks
inspired by hidden Markov models can train and represent dynamical
systems. The best training and generalization performance is
achieved when the hybrid architecture is initialized with random real
weight values of range -15 to 15.
Abstract: Neem is a highly heterozygous and commercially
important perennial plant. Conventionally, it is propagated by seeds
which loose viability within two weeks. Strictly cross pollinating
nature of the plant causes serious barrier to the genetic improvement
by conventional methods. Alternative methods of tree improvement
such as somatic hybridization, mutagenesis and genetic
transformation require an efficient in vitro plant regeneration system.
In this regard, somatic embryogenesis particularly secondary somatic
embryogenesis may offer an effective system for large scale plant
propagation without affecting the clonal fidelity of the regenerants. It
can be used for synthetic seed production, which further bolsters
conservation of this tree species which is otherwise very difficult
The present report describes the culture conditions necessary to
induce and maintain repetitive somatic embryogenesis, for the first
time, in neem. Out of various treatments tested, the somatic embryos
were induced directly from immature zygotic embryos of neem on
MS + TDZ (0.1 μM) + ABA (4 μM), in more than 76 % cultures.
Direct secondary somatic embryogenesis occurred from primary
somatic embryos on MS + IAA (5 μM) + GA3 (5 μM) in 12.5 %
cultures. Embryogenic competence of the explant as well as of the
primary embryos was maintained for a long period by repeated
subcultures at frequent intervals. A maximum of 10 % of these
somatic embryos were converted into plantlets.
Abstract: A Cable-Driven Locomotion Interface provides a low
inertia haptic interface and is used as a way of enabling the user
to walk and interact with virtual surfaces. These surfaces generate
Cartesian wrenches which must be optimized for each motorized
reel in order to reproduce a haptic sensation in both feet. However,
the use of wrench control requires a measure of the cable tensions
applied to the moving platform. The latter measure may be inaccurate
if it is based on sensors located near the reel. Moreover, friction
hysteresis from the reel moving parts needs to be compensated
for with an evaluation of low angular velocity of the motor shaft.
Also, the pose of the platform is not known precisely due to cable
sagging and mechanical deformation. This paper presents a non-ideal
motorized reel design with its corresponding control strategy that
aims at overcoming the aforementioned issues. A transfert function
of the reel based on frequency responses in function of cable tension
and cable length is presented with an optimal adaptative PIDF
controller. Finally, an hybrid position/tension control is discussed with
an analysis of the stability for achieving a complete functionnality of
the haptic platform.
Abstract: This paper proposes a novel approach that combines statistical models and support vector machines. A hybrid scheme which appropriately incorporates the advantages of both the generative and discriminant model paradigms is described and evaluated. Support vector machines (SVMs) are trained to divide the whole speakers' space into small subsets of speakers within a hierarchical tree structure. During testing a speech token is assigned to its corresponding group and evaluation using gaussian mixture models (GMMs) is then processed. Experimental results show that the proposed method can significantly improve the performance of text independent speaker identification task. We report improvements of up to 50% reduction in identification error rate compared to the baseline statistical model.
Abstract: Word sense disambiguation is one of the most important open problems in natural language processing applications such as information retrieval and machine translation. Many approach strategies can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledgebased, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy that employs an unsupervised learning method for disambiguation. We report our investigation of Latent Semantic Indexing (LSI), an information retrieval technique and unsupervised learning, to the task of Thai noun and verbal word sense disambiguation. The Latent Semantic Indexing has been shown to be efficient and effective for Information Retrieval. For the purposes of this research, we report experiments on two Thai polysemous words, namely /hua4/ and /kep1/ that are used as a representative of Thai nouns and verbs respectively. The results of these experiments demonstrate the effectiveness and indicate the potential of applying vector-based distributional information measures to semantic disambiguation.
Abstract: For collecting data from all sensor nodes, some
changes in Dynamic Source Routing (DSR) protocol is proposed. At
each hop level, route-ranking technique is used for distributing
packets to different selected routes dynamically. For calculating rank
of a route, different parameters like: delay, residual energy and
probability of packet loss are used. A hybrid topology of
DMPR(Disjoint Multi Path Routing) and MMPR(Meshed Multi Path
Routing) is formed, where braided topology is used in different
faulty zones of network. For reducing energy consumption, variant
transmission ranges is used instead of fixed transmission range. For
reducing number of packet drop, a fuzzy logic inference scheme is
used to insert different types of delays dynamically. A rule based
system infers membership function strength which is used to
calculate the final delay amount to be inserted into each of the node
at different clusters.
In braided path, a proposed 'Dual Line ACK Link'scheme is
proposed for sending ACK signal from a damaged node or link to a
parent node to ensure that any error in link or any node-failure
message may not be lost anyway. This paper tries to design the
theoretical aspects of a model which may be applied for collecting
data from any large hanging iron structure with the help of wireless
sensor network. But analyzing these data is the subject of material
science and civil structural construction technology, that part is out
of scope of this paper.