Abstract: The calculation of buckling length factor (K) for steel
frames columns is a major and governing processes to determine the
dimensions steel frame columns cross sections during design. The
buckling length of steel frames columns has a direct effect on the cost
(weight) of using cross section. A new formula is required to
determine buckling length factor (K) by simplified way. In this
research a new formula for buckling length factor (K) was established
to determine by accurate method for a limited interval of columns
ends rigidity (GA, GB). The new formula can be used ease to
evaluate the buckling length factor without needing to complicated
equations or difficult charts.
Abstract: In this study concept of experimental design is
successfully applied for the determination of optimum condition to
produce PP/SWCNT (Polypropylene/Single wall carbon nanotube)
nanocomposite. Central composite design as one of experimental
design techniques is employed for the optimization and statistical
determination of the significant factors influencing on the tensile
modulus and yield stress as mechanical properties of this
nanocomposite. The significant factors are SWCNT weight fraction
and acid treatment time for functionalizing the nanoparticles.
Optimum conditions are in 0.7 % of SWCNT weight fraction and 210
min as acid treatment time for 1112.75 ± 28 MPa as maximum tensile
modulus and in 216 min and 0.65 % as acid treatment time and
SWCNT weight fraction respectively for 40.26 ± 0.3 MPa as
maximum yield stress. Also after setting new experiments for test
these optimum conditions, found excelent agreement with predicted
values.
Abstract: En bloc assumes modeling all phases of the orthostatic test with the only one mathematical model, which allows the complex parametric view of orthostatic response. The work presents the implementation of a mathematical model for processing of the measurements of systolic, diastolic blood pressure and heart rate performed on volunteers during orthostatic test. The original assumption of model hypothesis that every postural change means only one Stressor, did not complying with the measurements of physiological circulation factor-time profiles. Results of the identification support the hypothesis that second postural change of orthostatic test causes induced Stressors, with the observation of a physiological regulation mechanism. Maximal demonstrations are on the heart rate and diastolic blood pressure-time profile, minimal are for the measurements of the systolic blood pressure. Presented study gives a new view on orthostatic test with impact on clinical practice.
Abstract: Nanostructured materials have attracted many
researchers due to their outstanding mechanical and physical
properties. For example, carbon nanotubes (CNTs) or carbon
nanofibres (CNFs) are considered to be attractive reinforcement
materials for light weight and high strength metal matrix composites.
These composites are being projected for use in structural
applications for their high specific strength as well as functional
materials for their exciting thermal and electrical characteristics. The
critical issues of CNT-reinforced MMCs include processing
techniques, nanotube dispersion, interface, strengthening mechanisms
and mechanical properties. One of the major obstacles to the effective
use of carbon nanotubes as reinforcements in metal matrix
composites is their agglomeration and poor distribution/dispersion
within the metallic matrix. In order to tap into the advantages of the
properties of CNTs (or CNFs) in composites, the high dispersion of
CNTs (or CNFs) and strong interfacial bonding are the key issues
which are still challenging. Processing techniques used for synthesis
of the composites have been studied with an objective to achieve
homogeneous distribution of carbon nanotubes in the matrix.
Modified mechanical alloying (ball milling) techniques have emerged
as promising routes for the fabrication of carbon nanotube (CNT)
reinforced metal matrix composites. In order to obtain a
homogeneous product, good control of the milling process, in
particular control of the ball movement, is essential. The control of
the ball motion during the milling leads to a reduction in grinding
energy and a more homogeneous product. Also, the critical inner
diameter of the milling container at a particular rotational speed can
be calculated. In the present work, we use conventional and modified
mechanical alloying to generate a homogenous distribution of 2 wt.
% CNT within Al powders. 99% purity Aluminium powder (Acros,
200mesh) was used along with two different types of multiwall
carbon nanotube (MWCNTs) having different aspect ratios to
produce Al-CNT composites. The composite powders were processed
into bulk material by compaction, and sintering using a cylindrical
compaction and tube furnace. Field Emission Scanning electron
microscopy (FESEM), X-Ray diffraction (XRD), Raman
spectroscopy and Vickers macro hardness tester were used to
evaluate CNT dispersion, powder morphology, CNT damage, phase
analysis, mechanical properties and crystal size determination.
Despite the success of ball milling in dispersing CNTs in Al powder,
it is often accompanied with considerable strain hardening of the Al
powder, which may have implications on the final properties of the
composite. The results show that particle size and morphology vary
with milling time. Also, by using the mixing process and sonication
before mechanical alloying and modified ball mill, dispersion of the
CNTs in Al matrix improves.
Abstract: In this paper, estimation of the linear regression
model is made by ordinary least squares method and the
partially linear regression model is estimated by penalized
least squares method using smoothing spline. Then, it is
investigated that differences and similarity in the sum of
squares related for linear regression and partial linear
regression models (semi-parametric regression models). It is
denoted that the sum of squares in linear regression is reduced
to sum of squares in partial linear regression models.
Furthermore, we indicated that various sums of squares in the
linear regression are similar to different deviance statements in
partial linear regression. In addition to, coefficient of the
determination derived in linear regression model is easily
generalized to coefficient of the determination of the partial
linear regression model. For this aim, it is made two different
applications. A simulated and a real data set are considered to
prove the claim mentioned here. In this way, this study is
supported with a simulation and a real data example.
Abstract: To investigates the effect of fiberglass clamping
process improvement on drape simulation prediction. This has
great effect on the mould and the fiber during manufacturing
process. This also, improves the fiber strain, the quality of the
fiber orientation in the area of folding and wrinkles formation
during the press-forming process. Drape simulation software
tool was used to digitalize the process, noting the formation
problems on the contour sensitive part. This was compared
with the real life clamping processes using single and double
frame set-ups to observe the effects. Also, restrains are
introduced by using clips, and the G-clamps with predetermine
revolution to; restrain the fabric deformation during the
forming process.The incorporation of clamping and fabric
restrain deformation improved on the prediction of the
simulation tool. Therefore, for effective forming process,
incorporation of clamping process into the drape simulation
process will assist in the development of fiberglass application
in manufacturing process.
Abstract: Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.
Abstract: This work focuses on the remediation of polycyclic
aromatic hydrocarbons (PAHs)-contaminated soil via Fenton
treatment coupled with novel chelating agent (CA). The feasibility of
chelated modified Fenton (MF) treatment to promote PAH oxidation
in artificially contaminated soils was investigated in laboratory scale
batch experiments at natural pH. The effects of adding inorganic and
organic CA are discussed. Experiments using different iron catalyst
to CA ratios were conducted, resulting in hydrogen peroxide: soil:
iron: CA weight ratios that varied from 0.049: 1: 0.072: 0.008 to
0.049: 1: 0.072: 0.067. The results revealed that (1) inorganic CA
could provide much higher PAH removal efficiency and (2) most of
the proposed CAs were more efficient than commonly utilised CAs
even at mild ratio. This work highlights the potential of novel
chelating agents in maintaining a suitable environment throughout
the Fenton treatment, particularly in soils with high buffer capacity.
Abstract: Abu Dhabi is one of the fastest developed cities in the region. On top of all the current and future environmental challenges, Abu Dhabi aims to be among the top governments in the world in sustainable development. Abu Dhabi plans to create an attractive, livable and sustainable managed urban environment in which all necessary services and infrastructure are provided in a sustainable and timely manner. Abu Dhabi is engaged in a difficult challenge to develop credible environmental indicators that would assess the ambitious environmental targets. The aim of those indicators is to provide reliable guidance to decision makers and the public concerning key factors that determine the state of urban environment and identify major areas for policy intervention. In order to ensure sustainable development in UAE in general, and of Abu Dhabi City in particular, relevant and contextual environmental indicators need to be carefully considered. These indicators provide a gauge at a national government scale of how close countries are to establish environmental policy goals. The environment indicators assist city decision-making in such areas as identification of significant environmental aspects and observation of environmental performance trends. Those can help to find ways of reducing environmental pollution and in improving eco-efficiency. This paper outlines recent strategies implemented in Abu Dhabi that aims to improve the sustainable performance of the city-s built environment. The paper explores the variety of current and possible indicators at different levels and their roles in the development of the city.
Abstract: The Goursat partial differential equation arises in
linear and non linear partial differential equations with mixed
derivatives. This equation is a second order hyperbolic partial
differential equation which occurs in various fields of study such as
in engineering, physics, and applied mathematics. There are many
approaches that have been suggested to approximate the solution of
the Goursat partial differential equation. However, all of the
suggested methods traditionally focused on numerical differentiation
approaches including forward and central differences in deriving the
scheme. An innovation has been done in deriving the Goursat partial
differential equation scheme which involves numerical integration
techniques. In this paper we have developed a new scheme to solve
the Goursat partial differential equation based on the Adomian
decomposition (ADM) and associated with Boole-s integration rule to
approximate the integration terms. The new scheme can easily be
applied to many linear and non linear Goursat partial differential
equations and is capable to reduce the size of computational work.
The accuracy of the results reveals the advantage of this new scheme
over existing numerical method.
Abstract: The paper deals with calculation of the parameters of
ceramic material from a set of destruction tests of ceramic heads of
total hip joint endoprosthesis. The standard way of calculation of the
material parameters consists in carrying out a set of 3 or 4 point
bending tests of specimens cut out from parts of the ceramic material
to be analysed. In case of ceramic heads, it is not possible to cut out
specimens of required dimensions because the heads are too small (if
the cut out specimens were smaller than the normalised ones, the
material parameters derived from them would exhibit higher strength
values than those which the given ceramic material really has). On
that score, a special testing jig was made, in which 40 heads were
destructed. From the measured values of circumferential strains of the
head-s external spherical surface under destruction, the state of stress
in the head under destruction was established using the final elements
method (FEM). From the values obtained, the sought for parameters
of the ceramic material were calculated using Weibull-s weakest-link
theory.
Abstract: As the Computed Tomography(CT) requires normally
hundreds of projections to reconstruct the image, patients are exposed
to more X-ray energy, which may cause side effects such as cancer.
Even when the variability of the particles in the object is very less,
Computed Tomography requires many projections for good quality
reconstruction. In this paper, less variability of the particles in an
object has been exploited to obtain good quality reconstruction.
Though the reconstructed image and the original image have same
projections, in general, they need not be the same. In addition
to projections, if a priori information about the image is known,
it is possible to obtain good quality reconstructed image. In this
paper, it has been shown by experimental results why conventional
algorithms fail to reconstruct from a few projections, and an efficient
polynomial time algorithm has been given to reconstruct a bi-level
image from its projections along row and column, and a known sub
image of unknown image with smoothness constraints by reducing the
reconstruction problem to integral max flow problem. This paper also
discusses the necessary and sufficient conditions for uniqueness and
extension of 2D-bi-level image reconstruction to 3D-bi-level image
reconstruction.
Abstract: Environment both endowed and built are essential for
tourism. However tourism and environment maintains a complex
relationship, where in most cases environment is at the receiving end.
Many tourism development activities have adverse environmental
effects, mainly emanating from construction of general infrastructure
and tourism facilities. These negative impacts of tourism can lead to
the destruction of precious natural resources on which it depends.
These effects vary between locations; and its effect on a hill
destination is highly critical. This study aims at developing a
Sustainable Tourism Planning Model for an environmentally
sensitive tourism destination in Kerala, India. Being part of the
Nilgiri mountain ranges, Munnar falls in the Western Ghats, one of
the biological hotspots in the world. Endowed with a unique high
altitude environment Munnar inherits highly significant ecological
wealth. Giving prime importance to the protection of this ecological
heritage, the study proposes a tourism planning model with resource
conservation and sustainability as the paramount focus. Conceiving a
novel approach towards sustainable tourism planning, the study
proposes to assess tourism attractions using Ecological Sensitivity
Index (ESI) and Tourism Attractiveness Index (TAI). Integration of
these two indices will form the Ecology – Tourism Matrix (ETM),
outlining the base for tourism planning in an environmentally
sensitive destination. The ETM Matrix leads to a classification of
tourism nodes according to its Conservation Significance and
Tourism Significance. The spatial integration of such nodes based on
the Hub & Spoke Principle constitutes sub – regions within the STZ.
Ensuing analyses lead to specific guidelines for the STZ as a whole,
specific tourism nodes, hubs and sub-regions. The study results in a
multi – dimensional output, viz., (1) Classification system for tourism
nodes in an environmentally sensitive region/ destination (2)
Conservation / Tourism Development Strategies and Guidelines for
the micro and macro regions and (3) A Sustainable Tourism Planning
Tool particularly for Ecologically Sensitive Destinations, which can
be adapted for other destinations as well.
Abstract: Discrete particle swarm optimization (DPSO) is a
powerful stochastic evolutionary algorithm that is used to solve the
large-scale, discrete and nonlinear optimization problems. However,
it has been observed that standard DPSO algorithm has premature
convergence when solving a complex optimization problem like
transmission expansion planning (TEP). To resolve this problem an
advanced discrete particle swarm optimization (ADPSO) is proposed
in this paper. The simulation result shows that optimization of lines
loading in transmission expansion planning with ADPSO is better
than DPSO from precision view point.
Abstract: Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.
Abstract: Leading topic of this article is description of Lorentz
forces in the container with cuboid and cylindrical shape. Inside of
the container is an electrically conductive melt. This melt is driven by
rotating magnetic field. Input data for comparing Lorentz forces in
the container with cuboid shape were obtained from the computing
program NS-FEM3D, which uses DDS method of computing. Values
of Lorentz forces for container with cylindrical shape were obtained
from inferred analytical formula.
Abstract: Liver segmentation is the first significant process for
liver diagnosis of the Computed Tomography. It segments the liver
structure from other abdominal organs. Sophisticated filtering techniques
are indispensable for a proper segmentation. In this paper, we
employ a 3D anisotropic diffusion as a preprocessing step. While
removing image noise, this technique preserve the significant parts
of the image, typically edges, lines or other details that are important
for the interpretation of the image. The segmentation task is done
by using thresholding with automatic threshold values selection and
finally the false liver region is eliminated using 3D connected component.
The result shows that by employing the 3D anisotropic filtering,
better liver segmentation results could be achieved eventhough simple
segmentation technique is used.
Abstract: Most file systems overwrite modified file data and
metadata in their original locations, while the Log-structured File
System (LFS) dynamically relocates them to other locations. We
design and implement the Evergreen file system that can select
between overwriting or relocation for each block of a file or metadata.
Therefore, the Evergreen file system can achieve superior write
performance by sequentializing write requests (similar to LFS-style
relocation) when space utilization is low and overwriting when
utilization is high. Another challenging issue is identifying
performance benefits of LFS-style relocation over overwriting on a
newly introduced SSD (Solid State Drive) which has only
Flash-memory chips and control circuits without mechanical parts.
Our experimental results measured on a SSD show that relocation
outperforms overwriting when space utilization is below 80% and vice
versa.
Abstract: In this paper, we propose a morphing method by which face color images can be freely transformed. The main focus of this work is the transformation of one face image to another. This method is fully automatic in that it can morph two face images by automatically detecting all the control points necessary to perform the morph. A face detection neural network, edge detection and medium filters are employed to detect the face position and features. Five control points, for both the source and target images, are then extracted based on the facial features. Triangulation method is then used to match and warp the source image to the target image using the control points. Finally color interpolation is done using a color Gaussian model that calculates the color for each particular frame depending on the number of frames used. A real coded Genetic algorithm is used in both the image warping and color blending steps to assist in step size decisions and speed up the morphing. This method results in ''very smooth'' morphs and is fast to process.
Abstract: A robust AUSM+ upwind discretisation scheme has been developed to simulate multiphase flow using consistent spatial discretisation schemes and a modified low-Mach number diffusion term. The impact of the selection of an interfacial pressure model has also been investigated. Three representative test cases have been simulated to evaluate the accuracy of the commonly-used stiffenedgas equation of state with respect to the IAPWS-IF97 equation of state for water. The algorithm demonstrates a combination of robustness and accuracy over a range of flow conditions, with the stiffened-gas equation tending to overestimate liquid temperature and density profiles.