Abstract: Understanding how airborne pathogens are
transported through hospital wards is essential for determining the
infection risk to patients and healthcare workers. This study utilizes
Computational Fluid Dynamics (CFD) simulations to explore
possible pathogen transport within a six-bed partitioned Nightingalestyle
hospital ward.
Grid independence of a ward model was addressed using the Grid
Convergence Index (GCI) from solutions obtained using three fullystructured
grids. Pathogens were simulated using source terms in
conjunction with a scalar transport equation and a RANS turbulence
model. Errors were found to be less than 4% in the calculation of air
velocities but an average of 13% was seen in the scalar field.
A parametric study of variations in the pathogen release point
illustrated that its distribution is strongly influenced by the local
velocity field and the degree of air mixing present.
Abstract: Document image processing has become an
increasingly important technology in the automation of office
documentation tasks. During document scanning, skew is inevitably
introduced into the incoming document image. Since the algorithm
for layout analysis and character recognition are generally very
sensitive to the page skew. Hence, skew detection and correction in
document images are the critical steps before layout analysis. In this
paper, a novel skew detection method is presented for binary
document images. The method considered the some selected
characters of the text which may be subjected to thinning and Hough
transform to estimate skew angle accurately. Several experiments
have been conducted on various types of documents such as
documents containing English Documents, Journals, Text-Book,
Different Languages and Document with different fonts, Documents
with different resolutions, to reveal the robustness of the proposed
method. The experimental results revealed that the proposed method
is accurate compared to the results of well-known existing methods.
Abstract: This paper discusses E-government, in particular the
challenges that face adoption in Saudi Arabia. E-government can be
defined based on an existing set of requirements. In this research we
define E-government as a matrix of stakeholders: governments to
governments, governments to business and governments to citizens,
using information and communications technology to deliver and
consume services. E-government has been implemented for a
considerable time in developed countries. However, E-government
services still face many challenges in their implementation and
general adoption in many countries including Saudi Arabia. It has
been noted that the introduction of E-government is a major
challenge facing the government of Saudi Arabia, due to possible
concerns raised by its citizens. In addition, the literature review and
the discussion identify the influential factors that affect the citizens’
intention to adopt E-government services in Saudi Arabia.
Consequently, these factors have been defined and categorized
followed by an exploratory study to examine the importance of these
factors. Therefore, this research has identified factors that determine
if the citizen will adopt E-government services and thereby aiding
governments in accessing what is required to increase adoption.
Abstract: This paper discusses the causal explanation capability
of QRIOM, a tool aimed at supporting learning of organic chemistry
reactions. The development of the tool is based on the hybrid use of
Qualitative Reasoning (QR) technique and Qualitative Process
Theory (QPT) ontology. Our simulation combines symbolic,
qualitative description of relations with quantity analysis to generate
causal graphs. The pedagogy embedded in the simulator is to both
simulate and explain organic reactions. Qualitative reasoning through
a causal chain will be presented to explain the overall changes made
on the substrate; from initial substrate until the production of final
outputs. Several uses of the QPT modeling constructs in supporting
behavioral and causal explanation during run-time will also be
demonstrated. Explaining organic reactions through causal graph
trace can help improve the reasoning ability of learners in that their
conceptual understanding of the subject is nurtured.
Abstract: Structural representation and technology mapping of
a Boolean function is an important problem in the design of nonregenerative
digital logic circuits (also called combinational logic
circuits). Library aware function manipulation offers a solution to
this problem. Compact multi-level representation of binary networks,
based on simple circuit structures, such as AND-Inverter Graphs
(AIG) [1] [5], NAND Graphs, OR-Inverter Graphs (OIG), AND-OR
Graphs (AOG), AND-OR-Inverter Graphs (AOIG), AND-XORInverter
Graphs, Reduced Boolean Circuits [8] does exist in
literature. In this work, we discuss a novel and efficient graph
realization for combinational logic circuits, represented using a
NAND-NOR-Inverter Graph (NNIG), which is composed of only
two-input NAND (NAND2), NOR (NOR2) and inverter (INV) cells.
The networks are constructed on the basis of irredundant disjunctive
and conjunctive normal forms, after factoring, comprising terms with
minimum support. Construction of a NNIG for a non-regenerative
function in normal form would be straightforward, whereas for the
complementary phase, it would be developed by considering a virtual
instance of the function. However, the choice of best NNIG for a
given function would be based upon literal count, cell count and
DAG node count of the implementation at the technology
independent stage. In case of a tie, the final decision would be made
after extracting the physical design parameters.
We have considered AIG representation for reduced disjunctive
normal form and the best of OIG/AOG/AOIG for the minimized
conjunctive normal forms. This is necessitated due to the nature of
certain functions, such as Achilles- heel functions. NNIGs are found
to exhibit 3.97% lesser node count compared to AIGs and
OIG/AOG/AOIGs; consume 23.74% and 10.79% lesser library cells
than AIGs and OIG/AOG/AOIGs for the various samples considered.
We compare the power efficiency and delay improvement achieved
by optimal NNIGs over minimal AIGs and OIG/AOG/AOIGs for
various case studies. In comparison with functionally equivalent,
irredundant and compact AIGs, NNIGs report mean savings in power
and delay of 43.71% and 25.85% respectively, after technology
mapping with a 0.35 micron TSMC CMOS process. For a
comparison with OIG/AOG/AOIGs, NNIGs demonstrate average
savings in power and delay by 47.51% and 24.83%. With respect to
device count needed for implementation with static CMOS logic
style, NNIGs utilize 37.85% and 33.95% lesser transistors than their
AIG and OIG/AOG/AOIG counterparts.
Abstract: User-Centered Design (UCD), Usability Engineering (UE) and Participatory Design (PD) are the common Human- Computer Interaction (HCI) approaches that are practiced in the software development process, focusing towards issues and matters concerning user involvement. It overlooks the organizational perspective of HCI integration within the software development organization. The Management Information Systems (MIS) perspective of HCI takes a managerial and organizational context to view the effectiveness of integrating HCI in the software development process. The Human-Centered Design (HCD) which encompasses all of the human aspects including aesthetic and ergonomic, is claimed as to provide a better approach in strengthening the HCI approaches to strengthen the software development process. In determining the effectiveness of HCD in the software development process, this paper presents the findings of a content analysis of HCI approaches by viewing those approaches as a technology which integrates user requirements, ranging from the top management to other stake holder in the software development process. The findings obtained show that HCD approach is a technology that emphasizes on human, tools and knowledge in strengthening the HCI approaches to strengthen the software development process in the quest to produce a sustainable, usable and useful software product.
Abstract: Ozone (O3) is considered as one of the most
phytotoxic pollutants with deleterious effects on living and non living
components of Ecosystems. It reduces growth and yield of many
crops as well as alters the physiology and crop quality. The present
study described series of experiments to investigate the effects of
ambient O3 at different locations with different ambient levels of O3
depending on proximity to pollutant source and ranged between 17
ppb/h in control experiment to 112 ppb/h in industrial area
respectively. The ambient levels in other three locations (King Saud
University botanical garden, King Fahd Rd, and Almanakh Garden)
were 61,61,77 ppb/h respectively. Tow legume crops species (vicia
vaba L ; and Pisum sativum) differ in their phenology and sensitivity
were used. The results showed a significant negative effect to ozone
on morphology, number of injured leaves, growth and productivity
with a difference in the degree of response depending on the plant
type. Visia Faba showed sensitivity to ozone to number and leaf area
and the degree of injury leaves 3, pisum sativum show higher
sensitivity for the gas for degree of injury 1,The relative growth rate
and seed weight, it turns out there is no significant difference
between the two plants in plant height and number of seeds.
Abstract: One of the most important areas of knowledge management studies is knowledge sharing. Measured in terms of number of scientific articles and organization-s applications, knowledge sharing stands as an example of success in the field. This paper reviews the related papers in the context of the underlying individual behavioral variables to providea direction framework for future research and writing.
Abstract: In many applications, it is a priori known that the
target function should satisfy certain constraints imposed by, for
example, economic theory or a human-decision maker. Here we
consider partially monotone problems, where the target variable
depends monotonically on some of the predictor variables but not all.
We propose an approach to build partially monotone models based
on the convolution of monotone neural networks and kernel
functions. The results from simulations and a real case study on
house pricing show that our approach has significantly better
performance than partially monotone linear models. Furthermore, the
incorporation of partial monotonicity constraints not only leads to
models that are in accordance with the decision maker's expertise,
but also reduces considerably the model variance in comparison to
standard neural networks with weight decay.
Abstract: The effect of calcination temperature and MgO crystallite sizes on the structure and catalytic performance of TiO2 supported nano-MgO catalyst for the trans-esterification of soybean oil has been studied. The catalyst has been prepared by deposition precipitation method, characterised by XRD and FTIR and tested in an autoclave at 225oC. The soybean oil conversion after 15 minutes of the trans-esterification reaction increased when the calcination temperature was increased from 500 to 600oC and decreased with further increase in calcination temperature. Some glycerolysis activity was also detected on catalysts calcined at 600 and 700oC after 45 minutes of reaction. The trans-esterification reaction rate increased with the decrease in MgO crystallite size for the first 30 min.
Abstract: Various models have been derived by studying large number of completed software projects from various organizations and applications to explore how project sizes mapped into project effort. But, still there is a need to prediction accuracy of the models. As Neuro-fuzzy based system is able to approximate the non-linear function with more precision. So, Neuro-Fuzzy system is used as a soft computing approach to generate model by formulating the relationship based on its training. In this paper, Neuro-Fuzzy technique is used for software estimation modeling of on NASA software project data and performance of the developed models are compared with the Halstead, Walston-Felix, Bailey-Basili and Doty Models mentioned in the literature.
Abstract: The use of neural networks is popular in various
building applications such as prediction of heating load, ventilation
rate and indoor temperature. Significant is, that only few papers deal
with indoor carbon dioxide (CO2) prediction which is a very good
indicator of indoor air quality (IAQ). In this study, a data-driven
modelling method based on multilayer perceptron network for indoor
air carbon dioxide in an apartment building is developed.
Temperature and humidity measurements are used as input variables
to the network. Motivation for this study derives from the following
issues. First, measuring carbon dioxide is expensive and sensors
power consumptions is high and secondly, this leads to short
operating times of battery-powered sensors. The results show that
predicting CO2 concentration based on relative humidity and
temperature measurements, is difficult. Therefore, more additional
information is needed.
Abstract: The problem of frequent itemset mining is considered in this paper. One new technique proposed to generate frequent patterns in large databases without time-consuming candidate generation. This technique is based on focusing on transaction instead of concentrating on itemset. This algorithm based on take intersection between one transaction and others transaction and the maximum shared items between transactions computed instead of creating itemset and computing their frequency. With applying real life transactions and some consumption is taken from real life data, the significant efficiency acquire from databases in generation association rules mining.
Abstract: Design patterns describe good solutions to common
and reoccurring problems in program design. Applying design
patterns in software design and implementation have significant
effects on software quality metrics such as flexibility, usability,
reusability, scalability and robustness. There is no standard rule for
using design patterns. There are some situations that a pattern is
applied for a specific problem and this pattern uses another pattern.
In this paper, we study the effect of using chain of patterns on
software quality metrics.
Abstract: Transpedicular screw fixation in spinal fractures,
degenerative changes, or deformities is a well-established procedure.
However, important rate of fixation failure due to screw bending,
loosening, or pullout are still reported particularly in weak bone stock
in osteoporosis. To overcome the problem, mechanism of failure has
to be fully investigated in vitro. Post-mortem human subjects are less
accessible and animal cadavers comprise limitations due to different
geometry and mechanical properties. Therefore, the development of a
synthetic model mimicking the realistic human vertebra is highly
demanded. A bone surrogate, composed of Polyurethane (PU) foam
analogous to cancellous bone porous structure, was tested for 3
different densities in this study. The mechanical properties were
investigated under uniaxial compression test by minimizing the end
artifacts on specimens. The results indicated that PU foam of 0.32
g.cm-3 density has comparable mechanical properties to human
cancellous bone in terms of young-s modulus and yield strength.
Therefore, the obtained information can be considered as primary
step for developing a realistic cancellous bone of human vertebral
body. Further evaluations are also recommended for other density
groups.
Abstract: In this paper, we propose an adaptation of the Patricia-Tree for sparse datasets to generate non redundant rule associations. Using this adaptation, we can generate frequent closed itemsets that are more compact than frequent itemsets used in Apriori approach. This adaptation has been experimented on a set of datasets benchmarks.
Abstract: Human perceives color in categories, which may be
identified using color name such as red, blue, etc. The categorization
is unique for each human being. However despite the individual
differences, the categorization is shared among members in society.
This allows communication among them, especially when using
color name. Sociable robot, to live coexist with human and become
part of human society, must also have the shared color
categorization, which can be achieved through learning. Many
works have been done to enable computer, as brain of robot, to learn
color categorization. Most of them rely on modeling of human color
perception and mathematical complexities. Differently, in this work,
the computer learns color categorization through interaction with
humans. This work aims at developing the innate ability of the
computer to learn the human-like color categorization. It focuses on
the representation of color categorization and how it is built and
developed without much mathematical complexity.
Abstract: The paper presents an analytical solution for dispersion
of a solute in the peristaltic motion of a couple stress fluid
through a porous medium with slip condition in the presence of both
homogeneous and heterogeneous chemical reactions. The average
effective dispersion coefficient has been found using Taylor-s limiting
condition and long wavelength approximation. The effects of various
relevant parameters on the average coefficient of dispersion have been
studied. The average effective dispersion coefficient tends to increase
with permeability parameter but tends to decrease with homogeneous
chemical reaction rate parameter, couple stress parameter, slip parameter
and heterogeneous reaction rate parameter.
Abstract: This work offers a study of new simple compact model
of dual-drain Magnetic Field Effect Transistor (MAGFET) including
geometrical effects and biasing dependency. An explanation of the
sensitivity is investigated, involving carrier deflection as the dominant
operating principle. Finally, model verification with simulation results
is introduced to ensure that acceptable error of 2% is achieved.
Abstract: In this era of competitiveness, there is a growing need for supply chains also to become competitive enough to handle pressures like varying customer’s expectations, low cost high quality products to be delivered at the minimum time and the most important is throat cutting competition at world wide scale. In the recent years, supply chain competitiveness has been, therefore, accepted as one of the most important philosophies in the supply chain literature. Various researchers and practitioners have tried to identify and implement strategies in supply chains which can bring competitiveness in the supply chains i.e. supply chain competitiveness. The purpose of this paper is to suggest select strategies for supply chain competitiveness in the Indian manufacturing sector using an integrated approach of literature review and exploratory interviews with eminent professionals from the supply chain area in various industries, academia and research. The aim of the paper is to highlight the important area of competitiveness in the supply chain and to suggest recommendations to the industry and managers of manufacturing sector.