Abstract: Sandwich panels are widely used in the construction
industry for their ease of assembly, light weight and efficient thermal
performance. They are composed of two RC thin outer layers
separated by an insulating inner layer. In this research the inner
insulating layer is made of lightweight Autoclaved Aerated Concrete
(AAC) blocks which has good thermal insulation properties and yet
possess reasonable mechanical strength. The shear strength of the
AAC infill is relied upon to replace the traditionally used insulating
foam and to provide the shear capacity of the panel. A
comprehensive experimental program was conducted on full scale
sandwich panels subjected to bending. In this paper, detailed
numerical modeling of the tested sandwich panels is reported. Nonlinear
3-D finite element modeling of the composite action of the
sandwich panel is developed using ANSYS. Solid elements with
different crashing and cracking capabilities and different constitutive
laws were selected for the concrete and the AAC. Contact interface
elements are used in this research to adequately model the shear
transfer at the interface between the different layers. The numerical
results showed good correlation with the experimental ones
indicating the adequacy of the model in estimating the loading
capacity of panels.
Abstract: Biomimicry has many potential benefits as many
technologies found in nature are superior to their man-made
counterparts. As technological device components approach the micro
and nanoscale, surface properties such as surface adhesion and friction
may need to be taken into account. Lowering surface adhesion by
manipulating chemistry alone might no longer be sufficient for such
components and thus physical manipulation may be required.
Adhesion reduction is only one of the many surface functions
displayed by micro/nano-structured cuticles of insects. Here, we
present a mini review of our understanding of insect cuticle structures
and the relationship between the structure dimensions and the
corresponding functional mechanisms. It may be possible to introduce
additional properties to material surfaces (indeed multi-functional
properties) based on the design of natural surfaces.
Abstract: This paper investigates the application of large scale (LS-PV) two-axis tracking photovoltaic power plant in Al-Jagbob, Libya. A 50MW PV-grid connected (two-axis tracking) power plant design in Al-Jagbob, Libya has been carried out presently. A hetero-junction with intrinsic thin layer (HIT) type PV module has been selected and modeled. A Microsoft Excel-VBA program has been constructed to compute slope radiation, dew-point, sky temperature, and then cell temperature, maximum power output and module efficiency for this system, for tracking system. The results for energy production show that the total energy output is 128.5 GWh/year. The average module efficiency is 16.6%. The electricity generation capacity factor (CF) and solar capacity factor (SCF) were found to be 29.3% and 70.4% respectively. A 50MW two axis tracking power plant with a total energy output of 128.5 GWh/year would reduce CO2 pollution by 85,581 tonnes of each year. The payback time for the proposed LS-PV photovoltaic power plant was found to be 4 years.
Abstract: Gene expression profiling is rapidly evolving into a
powerful technique for investigating tumor malignancies. The
researchers are overwhelmed with the microarray-based platforms
and methods that confer them the freedom to conduct large-scale
gene expression profiling measurements. Simultaneously,
investigations into cross-platform integration methods have started
gaining momentum due to their underlying potential to help
comprehend a myriad of broad biological issues in tumor diagnosis,
prognosis, and therapy. However, comparing results from different
platforms remains to be a challenging task as various inherent
technical differences exist between the microarray platforms. In this
paper, we explain a simple ratio-transformation method, which can
provide some common ground for cDNA and Affymetrix platform
towards cross-platform integration. The method is based on the
characteristic data attributes of Affymetrix- and cDNA- platform. In
the work, we considered seven childhood leukemia patients and their
gene expression levels in either platform. With a dataset of 822
differentially expressed genes from both these platforms, we carried
out a specific ratio-treatment to Affymetrix data, which subsequently
showed an improvement in the relationship with the cDNA data.
Abstract: The widely used Total Variation de-noising algorithm can preserve sharp edge, while removing noise. However, since fixed regularization parameter over entire image, small details and textures are often lost in the process. In this paper, we propose a modified Total Variation algorithm to better preserve smaller-scaled features. This is done by allowing an adaptive regularization parameter to control the amount of de-noising in any region of image, according to relative information of local feature scale. Experimental results demonstrate the efficient of the proposed algorithm. Compared with standard Total Variation, our algorithm can better preserve smaller-scaled features and show better performance.
Abstract: The problem of FIR system parameter estimation has been considered in the paper. A new robust recursive algorithm for simultaneously estimation of parameters and scale factor of prediction residuals in non-stationary environment corrupted by impulsive noise has been proposed. The performance of derived algorithm has been tested by simulations.
Abstract: The three-time-scale plant model of a wind power
generator, including a wind turbine, a flexible vertical shaft, a Variable
Inertia Flywheel (VIF) module, an Active Magnetic Bearing (AMB)
unit and the applied wind sequence, is constructed. In order to make
the wind power generator be still able to operate as the spindle speed
exceeds its rated speed, the VIF is equipped so that the spindle speed
can be appropriately slowed down once any stronger wind field is
exerted. To prevent any potential damage due to collision by shaft
against conventional bearings, the AMB unit is proposed to regulate
the shaft position deviation. By singular perturbation order-reduction
technique, a lower-order plant model can be established for the
synthesis of feedback controller. Two major system parameter
uncertainties, an additive uncertainty and a multiplicative uncertainty,
are constituted by the wind turbine and the VIF respectively.
Frequency Shaping Sliding Mode Control (FSSMC) loop is proposed
to account for these uncertainties and suppress the unmodeled
higher-order plant dynamics. At last, the efficacy of the FSSMC is
verified by intensive computer and experimental simulations for
regulation on position deviation of the shaft and counter-balance of
unpredictable wind disturbance.
Abstract: Automatic face detection is a complex problem in
image processing. Many methods exist to solve this problem such as
template matching, Fisher Linear Discriminate, Neural Networks,
SVM, and MRC. Success has been achieved with each method to
varying degrees and complexities. In proposed algorithm we used
upright, frontal faces for single gray scale images with decent
resolution and under good lighting condition. In the field of face
recognition technique the single face is matched with single face
from the training dataset. The author proposed a neural network
based face detection algorithm from the photographs as well as if any
test data appears it check from the online scanned training dataset.
Experimental result shows that the algorithm detected up to 95%
accuracy for any image.
Abstract: The objective of this study was to improve our
understanding of vulnerability and environmental change; it's causes
basically show the intensity, its distribution and human-environment
effect on the ecosystem in the Apodi Valley Region, This paper is
identify, assess and classify vulnerability and environmental change
in the Apodi valley region using a combined approach of landscape
pattern and ecosystem sensitivity. Models were developed using the
following five thematic layers: Geology, geomorphology, soil,
vegetation and land use/cover, by means of a Geographical
Information Systems (GIS)-based on hydro-geophysical parameters.
In spite of the data problems and shortcomings, using ESRI-s ArcGIS
9.3 program, the vulnerability score, to classify, weight and combine
a number of 15 separate land cover classes to create a single indicator
provides a reliable measure of differences (6 classes) among regions
and communities that are exposed to similar ranges of hazards.
Indeed, the ongoing and active development of vulnerability
concepts and methods have already produced some tools to help
overcome common issues, such as acting in a context of high
uncertainties, taking into account the dynamics and spatial scale of
asocial-ecological system, or gathering viewpoints from different
sciences to combine human and impact-based approaches. Based on
this assessment, this paper proposes concrete perspectives and
possibilities to benefit from existing commonalities in the
construction and application of assessment tools.
Abstract: The paper presents a computational tool developed for
the evaluation of technical and economic advantages of an innovative
cleaning and conditioning technology of fluidized bed steam/oxygen
gasifiers outlet product gas. This technology integrates into a single
unit the steam gasification of biomass and the hot gas cleaning and
conditioning system. Both components of the computational tool,
process flowsheet and economic evaluator, have been developed
under IPSEpro software. The economic model provides information
that can help potential users, especially small and medium size
enterprises acting in the regenerable energy field, to decide the
optimal scale of a plant and to better understand both potentiality and
limits of the system when applied to a wide range of conditions.
Abstract: Stable nonzero populations without random deaths
caused by the Verhulst factor (Verhulst-free) are a rarity. Majority
either grow without bounds or die of excessive harmful mutations.
To delay the accumulation of bad genes or diseases, a new
environmental parameter Γ is introduced in the simulation. Current
results demonstrate that stability may be achieved by setting Γ = 0.1.
These steady states approach a maximum size that scales inversely
with reproduction age.
Abstract: The principal focus of this study is on the
measurement and analysis of labor learnings in Pakistan. The study
at the aggregate economy level focus on the labor productivity
movements and at large-scale manufacturing level focus on the cost
structure, with isolating the contribution of the learning curve. The
analysis of S-shaped curve suggests that learnings are only below one
half of aggregate learning curve and other half shows the retardation
in learning, hence retardation in productivity movements. The study
implies the existence of learning economies in term of cost reduction
that is input cost per unit produced decreases by 0.51 percent every
time the cumulative production output doubles.
Abstract: A series of tests on cold-formed steel (CFS) wall plate system subjected to uplift force at the mid span of the wall plate is presented. The aim of the study was to study the behaviour and identify the modes of failure of CFS wall plate system. Two parameters were considered in these studies: 1) different dimension of U-bracket at the supports and 2) different sizes of lipped C-channel. The lipped C-channels used were C07508, C07512 and C10012. The dimensions of the leg of U-bracket were 50x35 mm and 50x60 mm respectively, where 25 mm clearance was provided to the connections for specimens with clearance. Results show that specimens with and without clearance experienced the same mode of failure. Failure began with the yielding of the connectors followed by distortional buckling of the wall plate. However, when C075 sections were used as wall plate, the system behaved differently. There was a large deformation in the wall plate and failure began in the distortional buckling of the wall plate followed by bearing of the connecting plates at the supports (U-bracket). The ultimate strength of the system also decreased dramatically when C075 sections were used.
Abstract: A numerical method is developed for simulating
the motion of particles with arbitrary shapes in an effectively
infinite or bounded viscous flow. The particle translational and
angular motions are numerically investigated using a fluid-structure
interaction (FSI) method based on the Arbitrary-Lagrangian-Eulerian
(ALE) approach and the dynamic mesh method (smoothing and
remeshing) in FLUENT ( ANSYS Inc., USA). Also, the effects of
arbitrary shapes on the dynamics are studied using the FSI method
which could be applied to the motions and deformations of a single
blood cell and multiple blood cells, and the primary thrombogenesis
caused by platelet aggregation. It is expected that, combined with a
sophisticated large-scale computational technique, the simulation
method will be useful for understanding the overall properties of blood
flow from blood cellular level (microscopic) to the resulting
rheological properties of blood as a mass (macroscopic).
Abstract: Several models of vulnerability assessment have been proposed. The selection of one of these models depends on the objectives of the study. The classical methodologies for seismic vulnerability analysis, as a part of seismic risk analysis, have been formulated with statistical criteria based on a rapid observation. The information relating to the buildings performance is statistically elaborated. In this paper, we use the European Macroseismic Scale EMS-98 to define the relationship between damage and macroseismic intensity to assess the seismic vulnerability. Applying to Algiers area, the first step is to identify building typologies and to assign vulnerability classes. In the second step, damages are investigated according to EMS-98.
Abstract: Modern managements of water distribution system
(WDS) need water quality models that are able to accurately predict
the dynamics of water quality variations within the distribution system
environment. Before water quality models can be applied to solve
system problems, they should be calibrated. Although former
researchers use GA solver to calibrate relative parameters, it is
difficult to apply on the large-scale or medium-scale real system for
long computational time. In this paper a new method is designed
which combines both macro and detailed model to optimize the water
quality parameters. This new combinational algorithm uses radial
basis function (RBF) metamodeling as a surrogate to be optimized for
the purpose of decreasing the times of time-consuming water quality
simulation and can realize rapidly the calibration of pipe wall reaction
coefficients of chlorine model of large-scaled WDS. After two cases
study this method is testified to be more efficient and promising, and
deserve to generalize in the future.
Abstract: This study aimed at developing visualization tools for integrating CloudSat images and Water Vapor Satellite images. KML was used for integrating data from CloudSat Satellite and GMS-6 Water Vapor Satellite. CloudSat 2D images were transformed into 3D polygons in order to achieve 3D images. Before overlaying the images on Google Earth, GMS-6 water vapor satellite images had to be rescaled into linear images. Web service was developed using webMathematica. Shoreline from GMS-6 images was compared with shoreline from LandSat images on Google Earth for evaluation. The results showed that shoreline from GMS-6 images was highly matched with the shoreline in LandSat images from Google Earth. For CloudSat images, the visualizations were compared with GMS-6 images on Google Earth. The results showed that CloudSat and GMS-6 images were highly correlated.
Abstract: Chronic conditions carry with them strong emotions
and often lead to charged relationships between patients and their
health providers and, by extension, patients and health researchers.
Persons are both autonomous and relational and a purely cognitive
model of autonomy neglects the social and relational basis of chronic
illness. Ensuring genuine informed consent in research requires a
thorough understanding of how participants perceive a study and
their reasons for participation. Surveys may not capture the
complexities of reasoning that underlies study participation.
Contradictory reasons for participation, for instance an initial claim
of altruism as rationale and a subsequent claim of personal benefit
(therapeutic misconception), affect the quality of informed consent.
Individuals apply principles through the filter of personal values and
lived experience. Authentic autonomy, and hence authentic consent
to research, occurs within the context of patients- unique life
narratives and illness experiences.
Abstract: System MEMORI automatically detects and recognizes rotated and/or rescaled versions of the objects of a database within digital color images with cluttered background. This task is accomplished by means of a region grouping algorithm guided by heuristic rules, whose parameters concern some geometrical properties and the recognition score of the database objects. This paper focuses on the strategies implemented in MEMORI for the estimation of the heuristic rule parameters. This estimation, being automatic, makes the system a highly user-friendly tool.
Abstract: Recent years have seen a growing trend towards the
integration of multiple information sources to support large-scale
prediction of protein-protein interaction (PPI) networks in model
organisms. Despite advances in computational approaches, the
combination of multiple “omic" datasets representing the same type
of data, e.g. different gene expression datasets, has not been
rigorously studied. Furthermore, there is a need to further investigate
the inference capability of powerful approaches, such as fullyconnected
Bayesian networks, in the context of the prediction of PPI
networks. This paper addresses these limitations by proposing a
Bayesian approach to integrate multiple datasets, some of which
encode the same type of “omic" data to support the identification of
PPI networks. The case study reported involved the combination of
three gene expression datasets relevant to human heart failure (HF).
In comparison with two traditional methods, Naive Bayesian and
maximum likelihood ratio approaches, the proposed technique can
accurately identify known PPI and can be applied to infer potentially
novel interactions.