Abstract: This paper is motivated by the importance of multi-sensor image fusion with specific focus on Infrared (IR) and Visible image (VI) fusion for various applications including military reconnaissance. Image fusion can be defined as the process of combining two or more source images into a single composite image with extended information content that improves visual perception or feature extraction. These images can be from different modalities like Visible camera & IR Thermal Imager. While visible images are captured by reflected radiations in the visible spectrum, the thermal images are formed from thermal radiation (IR) that may be reflected or self-emitted. A digital color camera captures the visible source image and a thermal IR camera acquires the thermal source image. In this paper, some image fusion algorithms based upon Multi-Scale Transform (MST) and region-based selection rule with consistency verification have been proposed and presented. This research includes implementation of the proposed image fusion algorithm in MATLAB along with a comparative analysis to decide the optimum number of levels for MST and the coefficient fusion rule. The results are presented, and several commonly used evaluation metrics are used to assess the suggested method's validity. Experiments show that the proposed approach is capable of producing good fusion results. While deploying our image fusion algorithm approaches, we observe several challenges from the popular image fusion methods. While high computational cost and complex processing steps of image fusion algorithms provide accurate fused results, but they also make it hard to become deployed in system and applications that require real-time operation, high flexibility and low computation ability. So, the methods presented in this paper offer good results with minimum time complexity.
Abstract: This paper comprehensively investigates current
development status of global power grids and fossil energy pipelines
(oil and natural gas), proposes a standard visual platform of global
power and fossil energy based on Geographic Information System
(GIS) technology. In this visual platform, a series of systematic
visual models is proposed with global spatial data, systematic
energy and power parameters. Under this visual platform, the
current Global Power Grids Map and Global Fossil Energy Pipelines
Map are plotted within more than 140 countries and regions
across the world. Using the multi-scale fusion data processing
and modeling methods, the world’s global fossil energy pipelines
and power grids information system basic database is established,
which provides important data supporting global fossil energy and
electricity research. Finally, through the systematic and comparative
study of global fossil energy pipelines and global power grids, the
general status of global fossil energy and electricity development
are reviewed, and energy transition in key areas are evaluated and
analyzed. Through the comparison analysis of fossil energy and
clean energy, the direction of relevant research is pointed out for
clean development and energy transition.
Abstract: The exploration of urban spatial evolution is an important part of urban development research. Therefore, the evolutionary modern Yangzhou urban spatial texture was taken as the research object, and Spatial Syntax was used as the main research tool, this paper explored Yangzhou spatial evolution law and its driving factors from the urban street network scale, district scale and street scale. The study has concluded that at the urban scale, Yangzhou urban spatial evolution is the result of a variety of causes, including physical and geographical condition, policy and planning factors, and traffic conditions, and the evolution of space also has an impact on social, economic, environmental and cultural factors. At the district and street scales, changes in space will have a profound influence on the history of the city and the activities of people. At the end of the article, the matters needing attention during the evolution of urban space were summarized.
Abstract: Sheet Molding Compounds (SMCs) with special microstructures are very attractive to use in automobile structures especially when they are accidentally subjected to collision type accidents because of their high energy absorption capacity. These are materials designated as standard SMC, Advanced Sheet Molding Compounds (A-SMC), Low-Density SMC (LD-SMC) and etc. In this study, testing methods have been performed to compare the mechanical responses and damage phenomena of SMC, LD-SMC, and A-SMC under quasi-static and high strain rate tensile tests. The paper also aims at investigating the effect of an initial pre-damage induced by fatigue on the tensile dynamic behavior of A-SMC. In the case of SMCs and A-SMCs, whatever the fibers orientation and applied strain rate are, the first observed phenomenon of damage corresponds to decohesion of the fiber-matrix interface which is followed by coalescence and multiplication of these micro-cracks and their propagations. For LD-SMCs, damage mechanisms depend on the presence of Hollow Glass Microspheres (HGM) and fibers orientation.
Abstract: Healthcare delivery systems around the world are in
crisis. The need to improve health outcomes while decreasing
healthcare costs have led to an imminent call to action to transform
the healthcare delivery system. While Bioinformatics and Biomedical
Engineering have primarily focused on biological level data and
biomedical technology, there is clear evidence of the importance
of the delivery of care on patient outcomes. Classic singular
decomposition approaches from reductionist science are not capable
of explaining complex systems. Approaches and methods from
systems science and systems engineering are utilized to structure
healthcare delivery system data. Specifically, systems architecture is
used to develop a multi-scale and multi-dimensional characterization
of the healthcare delivery system, defined here as the Healthcare
Delivery System Knowledge Base. This paper is the first to contribute
a new method of structuring and visualizing a multi-dimensional and
multi-scale healthcare delivery system using systems architecture in
order to better understand healthcare delivery.
Abstract: During an earthquake, a bridge crane may be
subjected to multiple impacts between crane wheels and rail. In order
to model such phenomena, a time-history dynamic analysis with a
multi-scale approach is performed. The high frequency aspect of the
impacts between wheels and rails is taken into account by a Lagrange
explicit event-capturing algorithm based on a velocity-impulse
formulation to resolve contacts and impacts. An implicit temporal
scheme is used for the rest of the structure. The numerical coupling
between the implicit and the explicit schemes is achieved with a
heterogeneous asynchronous time-integrator.
Abstract: Mammography is widely used technique for breast cancer
screening. There are various other techniques for breast cancer screening
but mammography is the most reliable and effective technique. The
images obtained through mammography are of low contrast which
causes problem for the radiologists to interpret. Hence, a high quality
image is mandatory for the processing of the image for extracting any
kind of information from it. Many contrast enhancement algorithms have
been developed over the years. In the present work, an efficient
morphology based technique is proposed for contrast enhancement of
masses in mammographic images. The proposed method is based on
Multiscale Morphology and it takes into consideration the scale of the
structuring element. The proposed method is compared with other stateof-
the-art techniques. The experimental results show that the proposed
method is better both qualitatively and quantitatively than the other
standard contrast enhancement techniques.
Abstract: This work assesses the cortical and the sub-cortical
neural activity recorded from rodents using entropy and mutual
information based approaches to study how hypothermia affects neural
activity. By applying the multi-scale entropy and Shannon entropy, we
quantify the degree of the regularity embedded in the cortical and
sub-cortical neurons and characterize the dependency of entropy of
these regions on temperature. We study also the degree of the mutual
information on thalamocortical pathway depending on temperature.
The latter is most likely an indicator of coupling between these highly
connected structures in response to temperature manipulation leading
to arousal after global cerebral ischemia.
Abstract: This paper presents powerful techniques for the
development of a new monitoring method based on multi-scale
entropy (MSE) in order to characterize the behaviour of the
concentrations of different gases present in the synthesis of Ammonia
and soft-sensor based on Principal Component Analysis (PCA).
Abstract: Speech Segmentation is the measure of the change
point detection for partitioning an input speech signal into regions
each of which accords to only one speaker. In this paper, we apply
two features based on multi-scale product (MP) of the clean speech,
namely the spectral centroid of MP, and the zero crossings rate of
MP. We focus on multi-scale product analysis as an important tool
for segmentation extraction. The MP is based on making the product
of the speech wavelet transform coefficients (WTC). We have
estimated our method on the Keele database. The results show the
effectiveness of our method. It indicates that the two features can find
word boundaries, and extracted the segments of the clean speech.
Abstract: These days, the field of tissue engineering is getting
serious attention due to its usefulness. Bone tissue engineering helps
to address and sort-out the critical sized and non-healing orthopedic
problems by the creation of manmade bone tissue. We will design
and validate an efficient numerical model, which will simulate the
effective diffusivity in bone tissue engineering. Our numerical model
will be based on the finite element analysis of the diffusion-reaction
equations. It will have the ability to optimize the diffusivity, even
at multi-scale, with the variation of time. It will also have a special
feature “parametric sweep”, with which we will be able to predict
the oxygen, glucose and cell density dynamics, more accurately. We
will fix these problems by modifying the governing equations, by
selecting appropriate spatio-temporal finite element schemes and by
transient analysis.
Abstract: In this research, waterglass based aerogel powder was
prepared by sol–gel process and ambient pressure drying. Inspired by
limited dust releasing, aerogel powder was introduced to the PET
electrospinning solution in an attempt to create required bulk and
surface structure for the nanofibers to improve their hydrophobic and
insulation properties. The samples evaluation was carried out by
measuring density, porosity, contact angle, heat transfer, FTIR, BET,
and SEM. According to the results, porous silica aerogel powder was
fabricated with mean pore diameter of 24 nm and contact angle of
145.9º. The results indicated the usefulness of the aerogel powder
confined into nanofibers to control surface roughness for
manipulating superhydrophobic nanowebs with water contact angle
of 147º. It can be due to a multi-scale surface roughness which was
created by nanowebs structure itself and nanofibers surface
irregularity in presence of the aerogels while a layer of fluorocarbon
created low surface energy. The wettability of a solid substrate is an
important property that is controlled by both the chemical
composition and geometry of the surface. Also, a decreasing trend in
the heat transfer was observed from 22% for the nanofibers without
any aerogel powder to 8% for the nanofibers with 4% aerogel
powder. The development of thermal insulating materials has become
increasingly more important than ever in view of the fossil energy
depletion and global warming that call for more demanding energysaving
practices.
Abstract: In the implementation of Carbon Nanotube Reinforced Polymer matrix Composites in structural applications, deflection and stress analysis are important considerations. In the present study, a multi scale analysis of deflection and stress analysis of carbon nanotube (CNT) reinforced polymer composite plates is presented. A micromechanics model based on the Mori-Tanaka method is developed by introducing straight CNTs aligned in one direction. The effect of volume fraction and diameter of CNTs on plate deflection and the stresses are investigated using classical laminate plate theory (CLPT). The study is primarily conducted with the intention of observing the suitability of CNT reinforced polymer composite plates under static loading for structural applications.
Abstract: Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular / nanoscale models is demonstrated.
Abstract: The objective of this work was to examine the
changes in the microstructure and macro physical properties caused
by the carbonation of normalised CEM II mortar. Samples were
prepared and subjected to accelerated carbonation at 20°C, 65%
relative humidity and 20% CO2 concentration. On the microstructure
scale, the evolutions of the cumulative pore volume, pore size
distribution, and specific surface area during carbonation were
calculated from the adsorption desorption isotherms of nitrogen. We
also examined the evolution of macro physical properties such as the
porosity accessible to water, the gas permeability, and thermal
conductivity. The conflict between the results of nitrogen porosity
and water porosity indicated that the porous domains explored using
these two techniques are different and help to complementarily
evaluate the effects of carbonation. This is a multi-scale study where
results on microstructural changes can help to explain the evolution
of macro physical properties.
Abstract: In this paper, a novel road extraction method using Stationary Wavelet Transform is proposed. To detect road features from color aerial satellite imagery, Mexican hat Wavelet filters are used by applying the Stationary Wavelet Transform in a multiresolution, multi-scale, sense and forming the products of Wavelet coefficients at a different scales to locate and identify road features at a few scales. In addition, the shifting of road features locations is considered through multiple scales for robust road extraction in the asymmetry road feature profiles. From the experimental results, the proposed method leads to a useful technique to form the basis of road feature extraction. Also, the method is general and can be applied to other features in imagery.
Abstract: A new technique of topological multi-scale analysis is
introduced. By performing a clustering recursively to build a
hierarchy, and analyzing the co-scale and intra-scale similarities, an
Iterated Function System can be extracted from any data set. The study
of fractals shows that this method is efficient to extract
self-similarities, and can find elegant solutions the inverse problem of
building fractals. The theoretical aspects and practical
implementations are discussed, together with examples of analyses of
simple fractals.
Abstract: This paper proposes method of diagnosing ball screw
preload loss through the Hilbert-Huang Transform （HHT） and
Multiscale entropy （MSE） process. The proposed method can
diagnose ball screw preload loss through vibration signals when the
machine tool is in operation. Maximum dynamic preload of 2 %, 4 %,
and 6 % ball screws were predesigned, manufactured, and tested
experimentally. Signal patterns are discussed and revealed using
Empirical Mode Decomposition（EMD）with the Hilbert Spectrum.
Different preload features are extracted and discriminated using HHT.
The irregularity development of a ball screw with preload loss is
determined and abstracted using MSE based on complexity
perception. Experiment results show that the proposed method can
predict the status of ball screw preload loss. Smart sensing for the
health of the ball screw is also possible based on a comparative
evaluation of MSE by the signal processing and pattern matching of
EMD/HHT. This diagnosis method realizes the purposes of prognostic
effectiveness on knowing the preload loss and utilizing convenience.
Abstract: The overall objective of this paper is to retrieve soil
surfaces parameters namely, roughness and soil moisture related to
the dielectric constant by inverting the radar backscattered signal
from natural soil surfaces.
Because the classical description of roughness using statistical
parameters like the correlation length doesn't lead to satisfactory
results to predict radar backscattering, we used a multi-scale
roughness description using the wavelet transform and the Mallat
algorithm. In this description, the surface is considered as a
superposition of a finite number of one-dimensional Gaussian
processes each having a spatial scale. A second step in this study
consisted in adapting a direct model simulating radar backscattering
namely the small perturbation model to this multi-scale surface
description. We investigated the impact of this description on radar
backscattering through a sensitivity analysis of backscattering
coefficient to the multi-scale roughness parameters.
To perform the inversion of the small perturbation multi-scale
scattering model (MLS SPM) we used a multi-layer neural network
architecture trained by backpropagation learning rule. The inversion
leads to satisfactory results with a relative uncertainty of 8%.
Abstract: As a tool for human spatial cognition and thinking, the map has been playing an important role. Maps are perhaps as fundamental to society as language and the written word. Economic and social development requires extensive and in-depth understanding of their own living environment, from the scope of the overall global to urban housing. This has brought unprecedented opportunities and challenges for traditional cartography . This paper first proposed the concept of scaleless-map and its basic characteristics, through the analysis of the existing multi-scale representation techniques. Then some strategies are presented for automated mapping compilation. Taking into account the demand of automated map compilation, detailed proposed the software - WJ workstation must have four technical features, which are generalization operators, symbol primitives, dynamically annotation and mapping process template. This paper provides a more systematic new idea and solution to improve the intelligence and automation of the scaleless cartography.