Abstract: The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.
Abstract: This paper summarizes the results of a survey on
smart non-structural element dynamic dissipation when installed
in modern high-rise mega-frame prototypes. An innovative glazed
curtain wall was designed using Shape Memory Alloy (SMA)
joints in order to increase the energy dissipation and enhance
the seismic/wind response of the structures. The studied buildings
consisted of thirty- and sixty-storey planar frames, extracted from
reference three-dimensional steel Moment Resisting Frame (MRF)
with outriggers and belt trusses. The internal core was composed of
a CBF system, whilst outriggers were placed every fifteen stories
to limit second order effects and inter-storey drifts. These structural
systems were designed in accordance with European rules and
numerical FE models were developed with an open-source code,
able to account for geometric and material nonlinearities. With
regard to the characterization of non-structural building components,
full-scale crescendo tests were performed on aluminium/glass curtain
wall units at the laboratory of the Construction Technologies
Institute (ITC) of the Italian National Research Council (CNR),
deriving force-displacement curves. Three-dimensional brick-based
inelastic FE models were calibrated according to experimental results,
simulating the fac¸ade response. Since recent seismic events and
extreme dynamic wind loads have generated the large occurrence of
non-structural components failure, which causes sensitive economic
losses and represents a hazard for pedestrians safety, a more
dissipative glazed curtain wall was studied. Taking advantage of the
mechanical properties of SMA, advanced smart joints were designed
with the aim to enhance both the dynamic performance of the single
non-structural unit and the global behavior. Thus, three-dimensional
brick-based plastic FE models were produced, based on the innovated
non-structural system, simulating the evolution of mechanical
degradation in aluminium-to-glass and SMA-to-glass connections
when high deformations occurred. Consequently, equivalent nonlinear
links were calibrated to reproduce the behavior of both tested and
smart designed units, and implemented on the thirty- and sixty-storey
structural planar frame FE models. Nonlinear time history analyses
(NLTHAs) were performed to quantify the potential of the new
system, when considered in the lateral resisting frame system (LRFS)
of modern high-rise MRFs. Sensitivity to the structure height was
explored comparing the responses of the two prototypes. Trends
in global and local performance were discussed to show that, if
accurately designed, advanced materials in non-structural elements provide new sources of energy dissipation.
Abstract: Beam-column connections play an important role in the reinforced concrete moment resisting frame (RCMRF), which is one of the most commonly used structural systems around the world. The premature failure of such connections would severely limit the seismic performance and increase the vulnerability of RCMRF. In the past decades, researchers primarily focused on investigating the structural behaviour and failure mechanisms of conventional beam-column joints, the beam width of which is either smaller than or equal to the column width, while studies in wide beam-column joints were scarce. This paper presents the preliminary experimental results of two full-scale exterior wide beam-column connections, which are mainly designed and detailed according to ACI 318-14 and ACI 352R-02, under reversed cyclic loading. The ratios of the design shear force to the nominal shear strength of these specimens are 1.0 and 1.7, respectively, so as to probe into differences of the joint shear strength between experimental results and predictions by design codes of practice. Flexural failure dominated in the specimen with ratio of 1.0 in which full-width plastic hinges were observed, while both beam hinges and post-peak joint shear failure occurred for the other specimen. No sign of premature joint shear failure was found which is inconsistent with ACI codes’ prediction. Finally, a modification of current codes of practice is provided to accurately predict the joint shear strength in wide beam-column joint.
Abstract: This paper copes with the numerical simulation for convective heat transfer in the stator disk of an axial flux permanent magnet (AFPM) electrical machine. Overheating is one of the main issues in the design of AFMPs, which mainly occurs in the stator disk, so that it needs to be prevented. A rotor-stator configuration with 16 magnets at the periphery of the rotor is considered. Air is allowed to flow through openings in the rotor disk and channels being formed between the magnets and in the gap region between the magnets and the stator surface. The rotating channels between the magnets act as a driving force for the air flow. The significant non-dimensional parameters are the rotational Reynolds number, the gap size ratio, the magnet thickness ratio, and the magnet angle ratio. The goal is to find correlations for the Nusselt number on the stator disk according to these non-dimensional numbers. Therefore, CFD simulations have been performed with the multiple reference frame (MRF) technique to model the rotary motion of the rotor and the flow around and inside the machine. A minimization method is introduced by a pattern-search algorithm to find the appropriate values of the reference temperature. It is found that the correlations are fast, robust and is capable of predicting the stator heat transfer with a good accuracy. The results reveal that the magnet angle ratio diminishes the stator heat transfer, whereas the rotational Reynolds number and the magnet thickness ratio improve the convective heat transfer. On the other hand, there a certain gap size ratio at which the stator heat transfer reaches a maximum.
Abstract: This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.
Abstract: Nowadays, energy dissipation devices are commonly
used in structures. High rate of energy absorption during earthquakes
is the benefit of using such devices, which results in damage
reduction of structural elements, specifically columns. The hysteretic
damping capacity of energy dissipation devices is the key point that it
may adversely make analysis and design process complicated. This
effect may be generally represented by Equivalent Viscous Damping
(EVD). The equivalent viscous damping might be obtained from the
expected hysteretic behavior regarding to the design or maximum
considered displacement of a structure. In this paper, the hysteretic
damping coefficient of a steel Moment Resisting Frame (MRF),
which its performance is enhanced by a Buckling Restrained Brace
(BRB) system has been evaluated. Having foresight of damping
fraction between BRB and MRF is inevitable for seismic design
procedures like Direct Displacement-Based Design (DDBD) method.
This paper presents an approach to calculate the damping fraction for
such systems by carrying out the dynamic nonlinear time history
analysis (NTHA) under harmonic loading, which is tuned to the
natural system frequency. Two MRF structures, one equipped with
BRB and the other without BRB are simultaneously studied.
Extensive analysis shows that proportion of each system damping
fraction may be calculated by its shear story portion. In this way,
contribution of each BRB in the floors and their general contribution
in the structural performance may be clearly recognized, in advance.
Abstract: The coaxial transformer-coupled push-pull circuitry
has been used widely in HF and VHF amplifiers for many decades
without significant changes in the topology of the transformers. Basic
changes over the years concerned the construction and turns ratio of
the transformers as has been imposed upon the newer technologies
active devices demands. The balun transmission line transformers
applied in push-pull amplifiers enable input/output impedance
transformation, but are mainly used to convert the balanced output
into unbalanced and the input unbalanced into balanced. A simple
and affordable alternative solution over the traditional coaxial
transformer is the coreless planar balun. A key advantage over the
traditional approach lies in the high specifications repeatability;
simplifying the amplifier construction requirements as the planar
balun constitutes an integrated part of the PCB copper layout. This
paper presents the performance analysis of a planar LDMOS
MRFE6VP5600 Push-Pull amplifier that enables robust operation in
Band III, DVB-T, DVB-T2 standards but functions equally well in
Band II, for DRM+ new generation transmitters.
Abstract: The present research work investigates the seismic
response of reinforced concrete (RC) frame building considering the
effect of modeling masonry infill (MI) walls. The seismic behavior of
a residential 6-storey RC frame building, considering and ignoring
the effect of masonry, is numerically investigated using response
spectrum (RS) analysis. The considered herein building is designed
as a moment resisting frame (MRF) system following the Egyptian
code (EC) requirements. Two developed models in terms of bare
frame and infill walls frame are used in the study. Equivalent
diagonal strut methodology is used to represent the behavior of infill
walls, whilst the well-known software package ETABS is used for
implementing all frame models and performing the analysis. The
results of the numerical simulations such as base shear,
displacements, and internal forces for the bare frame as well as the
infill wall frame are presented in a comparative way. The results of
the study indicate that the interaction between infill walls and frames
significantly change the responses of buildings during earthquakes
compared to the results of bare frame building model. Specifically,
the seismic analysis of RC bare frame structure leads to
underestimation of base shear and consequently damage or even
collapse of buildings may occur under strong shakings. On the other
hand, considering infill walls significantly decrease the peak floor
displacements and drifts in both X and Y-directions.
Abstract: The computational fluid dynamics (CFD) study of
stirred tank with the air-water interface are carried out in the presence
of different types of the impeller and with or without baffles. A
multiple reference frame (MRF) approach with the volume of fluid
(VOF) method is used to capture the air-water interface. The RANS
(Reynolds Averaged Navier-Stokes) equations with k-ε turbulence
model are solved to predict the flow behavior of water and air phase
which are treated as a different phases. The predicted results have
shown that the VOF method is able to capture the interface in the
unbaffled tank. While, the VOF method is showing an unfeasible
results in the baffled tank with high rotational impeller speed. For
continuous stirred tank, the air-water interface is disturbed by the
inflow and the level of water is also increased with time.
Abstract: Tumor is an uncontrolled growth of tissues in any part
of the body. Tumors are of different types and they have different
characteristics and treatments. Brain tumor is inherently serious and
life-threatening because of its character in the limited space of the
intracranial cavity (space formed inside the skull). Locating the tumor
within MR (magnetic resonance) image of brain is integral part of the
treatment of brain tumor. This segmentation task requires
classification of each voxel as either tumor or non-tumor, based on
the description of the voxel under consideration. Many studies are
going on in the medical field using Markov Random Fields (MRF) in
segmentation of MR images. Even though the segmentation process
is better, computing the probability and estimation of parameters is
difficult. In order to overcome the aforementioned issues, Conditional
Random Field (CRF) is used in this paper for segmentation, along
with the modified artificial bee colony optimization and modified
fuzzy possibility c-means (MFPCM) algorithm. This work is mainly
focused to reduce the computational complexities, which are found in
existing methods and aimed at getting higher accuracy. The
efficiency of this work is evaluated using the parameters such as
region non-uniformity, correlation and computation time. The
experimental results are compared with the existing methods such as
MRF with improved Genetic Algorithm (GA) and MRF-Artificial
Bee Colony (MRF-ABC) algorithm.
Abstract: There are many researches on parameters affecting seismic behavior of steel moment frames. Great deal of these researches considers cover plate connections with or without haunch and direct beam to column connection for exterior columns. Also there are experimental results for interior connections with equal beam depth on both sides but not much research has been performed on the seismic behavior of joints with unequal beam depth. Based on previous experimental results, a series of companion analyses have been set up considering different beam height and connection detailing configuration to investigate the seismic behavior of the connections. Results of this study indicate that when the differences between beams height on both side increases, use of haunch connection system leads to significant improvement in the seismic response whereas other configurations did not provide satisfying results.
Abstract: The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the Gauss- Markov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance.
Abstract: This paper introduces a novel approach to estimate the
clique potentials of Gibbs Markov random field (GMRF) models
using the Support Vector Machines (SVM) algorithm and the Mean
Field (MF) theory. The proposed approach is based on modeling the
potential function associated with each clique shape of the GMRF
model as a Gaussian-shaped kernel. In turn, the energy function of
the GMRF will be in the form of a weighted sum of Gaussian
kernels. This formulation of the GMRF model urges the use of the
SVM with the Mean Field theory applied for its learning for
estimating the energy function. The approach has been tested on
synthetic texture images and is shown to provide satisfactory results
in retrieving the synthesizing parameters.
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: Texture classification is a trendy and a catchy
technology in the field of texture analysis. Textures, the repeated
patterns, have different frequency components along different
orientations. Our work is based on Texture Classification and its
applications. It finds its applications in various fields like Medical
Image Classification, Computer Vision, Remote Sensing,
Agricultural Field, and Textile Industry. Weed control has a major
effect on agriculture. A large amount of herbicide has been used for
controlling weeds in agriculture fields, lawns, golf courses, sport
fields, etc. Random spraying of herbicides does not meet the exact
requirement of the field. Certain areas in field have more weed
patches than estimated. So, we need a visual system that can
discriminate weeds from the field image which will reduce or even
eliminate the amount of herbicide used. This would allow farmers to
not use any herbicides or only apply them where they are needed. A
machine vision precision automated weed control system could
reduce the usage of chemicals in crop fields. In this paper, an
intelligent system for automatic weeding strategy Multi Resolution
Combined Statistical & spatial Frequency is used to discriminate the
weeds from the crops and to classify them as narrow, little and broad
weeds.
Abstract: In this paper, we present the region based hidden Markov random field model (RBHMRF), which encodes the characteristics of different brain regions into a probabilistic framework for brain MR image segmentation. The recently proposed TV+L1 model is used for region extraction. By utilizing different spatial characteristics in different brain regions, the RMHMRF model performs beyond the current state-of-the-art method, the hidden Markov random field model (HMRF), which uses identical spatial information throughout the whole brain. Experiments on both real and synthetic 3D MR images show that the segmentation result of the proposed method has higher accuracy compared to existing algorithms.
Abstract: In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.
Abstract: Finger spelling is an art of communicating by signs
made with fingers, and has been introduced into sign language to serve
as a bridge between the sign language and the verbal language.
Previous approaches to finger spelling recognition are classified into
two categories: glove-based and vision-based approaches. The
glove-based approach is simpler and more accurate recognizing work
of hand posture than vision-based, yet the interfaces require the user to
wear a cumbersome and carry a load of cables that connected the
device to a computer. In contrast, the vision-based approaches provide
an attractive alternative to the cumbersome interface, and promise
more natural and unobtrusive human-computer interaction. The
vision-based approaches generally consist of two steps: hand
extraction and recognition, and two steps are processed independently.
This paper proposes real-time vision-based Korean finger spelling
recognition system by integrating hand extraction into recognition.
First, we tentatively detect a hand region using CAMShift algorithm.
Then fill factor and aspect ratio estimated by width and height
estimated by CAMShift are used to choose candidate from database,
which can reduce the number of matching in recognition step. To
recognize the finger spelling, we use DTW(dynamic time warping)
based on modified chain codes, to be robust to scale and orientation
variations. In this procedure, since accurate hand regions, without
holes and noises, should be extracted to improve the precision, we use
graph cuts algorithm that globally minimize the energy function
elegantly expressed by Markov random fields (MRFs). In the
experiments, the computational times are less than 130ms, and the
times are not related to the number of templates of finger spellings in
database, as candidate templates are selected in extraction step.
Abstract: In this paper the design of maximally flat linear phase
finite impulse response (FIR) filters is considered. The problem is
handled with totally two different approaches. The first one is
completely deterministic numerical approach where the problem is
formulated as a Linear Complementarity Problem (LCP). The other
one is based on a combination of Markov Random Fields (MRF's)
approach with messy genetic algorithm (MGA). Markov Random
Fields (MRFs) are a class of probabilistic models that have been
applied for many years to the analysis of visual patterns or textures.
Our objective is to establish MRFs as an interesting approach to
modeling messy genetic algorithms. We establish a theoretical result
that every genetic algorithm problem can be characterized in terms of
a MRF model. This allows us to construct an explicit probabilistic
model of the MGA fitness function and introduce the Ising MGA.
Experimentations done with Ising MGA are less costly than those
done with standard MGA since much less computations are involved.
The least computations of all is for the LCP. Results of the LCP,
random search, random seeded search, MGA, and Ising MGA are
discussed.
Abstract: We study dynamic instability in high-rise steel moment
resisting frames (SMRFs) subjected to synthetic long-period ground
motions caused by hypothetical huge subduction earthquakes. Since
long duration as well as long dominant periods is a characteristic of
long-period ground motions, interstory drifts may enter the negative
postyield stiffness range many times when high-rise buildings are
subjected to long-period ground motions. Through the case studies of
9 high-rise SMRFs designed in accordance with the Japanese design
practice in 1980s, we demonstrate that drifting, or accumulation of
interstory drifts in one direction, occurs at the lower stories of the
SMRFs, if their natural periods are close to the dominant periods of the
long-period ground motions. The drifting led to residual interstory
drift ratio over 0.01, or to collapse if the design base shear was small.