Abstract: In this paper we present the efficient parallel
implementation of elastoplastic problems based on the TFETI (Total
Finite Element Tearing and Interconnecting) domain decomposition
method. This approach allow us to use parallel solution and compute
this nonlinear problem on the supercomputers and decrease the
solution time and compute problems with millions of DOFs. In
our approach we consider an associated elastoplastic model with
the von Mises plastic criterion and the combination of linear
isotropic-kinematic hardening law. This model is discretized by
the implicit Euler method in time and by the finite element
method in space. We consider the system of nonlinear equations
with a strongly semismooth and strongly monotone operator. The
semismooth Newton method is applied to solve this nonlinear
system. Corresponding linearized problems arising in the Newton
iterations are solved in parallel by the above mentioned TFETI. The
implementation of this problem is realized in our in-house MatSol
packages developed in MatLab.
Abstract: This paper presents circuit models to analyze the
conducted susceptibility of multiconductor shielded cables in
frequency domains using Branin’s method, which is referred to as the
method of characteristics. These models, which can be used directly
in the time and frequency domains, take into account the presence of
both the transfer impedance and admittance. The conducted
susceptibility is studied by using an injection current on the cable
shield as the source. Two examples are studied; a coaxial shielded
cable and shielded cables with two parallel wires (i.e., twinax cables).
This shield has an asymmetry (one slot on the side). Results obtained
by these models are in good agreement with those obtained by other
methods.
Abstract: Customer churn prediction is one of the most useful
areas of study in customer analytics. Due to the enormous amount
of data available for such predictions, machine learning and data
mining have been heavily used in this domain. There exist many
machine learning algorithms directly applicable for the problem of
customer churn prediction, and here, we attempt to experiment on
a novel approach by using a cognitive learning based technique in
an attempt to improve the results obtained by using a combination
of supervised learning methods, with cognitive unsupervised learning
methods.
Abstract: New physical insights into the nonlinear Lorenz
equations related to flow resistance is discussed in this work. The
chaotic dynamics related to Lorenz equations has been studied in
many papers, which is due to the sensitivity of Lorenz equations to
initial conditions and parameter uncertainties. However, the physical
implication arising from Lorenz equations about convectional motion
attracts little attention in the relevant literature. Therefore, as a first
step to understand the related fluid mechanics of convectional motion,
this paper derives the Lorenz equations again with different forced
conditions in the model. Simulation work of the modified Lorenz
equations without the viscosity or buoyancy force is discussed. The
time-domain simulation results may imply that the states of the
Lorenz equations are related to certain flow speed and flow resistance.
The flow speed of the underlying fluid system increases as the flow
resistance reduces. This observation would be helpful to analyze the
coupling effects of different fluid parameters in a convectional model
in future work.
Abstract: Offering a Product-Service System (PSS) is a
well-accepted strategy that companies may adopt to provide a set of
systemic solutions to customers. PSSs were initially provided in a
simple form but now take diversified and complex forms involving
multiple services, products and technologies. With the growing
interest in the PSS, frameworks for the PSS development have been
introduced by many researchers. However, most of the existing
frameworks fail to examine various relations existing in a complex
PSS. Since designing a complex PSS involves full integration of
multiple products and services, it is essential to identify not only
product-service relations but also product-product/ service-service
relations. It is also equally important to specify how they are related
for better understanding of the system. Moreover, as customers tend to
view their purchase from a more holistic perspective, a PSS should be
developed based on the whole system’s requirements, rather than
focusing only on the product requirements or service requirements.
Thus, we propose a framework to develop a complex PSS that is
coordinated fully with the requirements of both worlds. Specifically,
our approach adopts a multi-domain matrix (MDM). A MDM
identifies not only inter-domain relations but also intra-domain
relations so that it helps to design a PSS that includes highly desired
and closely related core functions/ features. Also, various dependency
types and rating schemes proposed in our approach would help the
integration process.
Abstract: In this paper, we used data mining to extract
biomedical knowledge. In general, complex biomedical data
collected in studies of populations are treated by statistical methods,
although they are robust, they are not sufficient in themselves to
harness the potential wealth of data. For that you used in step two
learning algorithms: the Decision Trees and Support Vector Machine
(SVM). These supervised classification methods are used to make the
diagnosis of thyroid disease. In this context, we propose to promote
the study and use of symbolic data mining techniques.
Abstract: This paper presents two techniques, local feature
extraction using image spectrum and low frequency spectrum
modelling using GMM to capture the underlying statistical
information to improve the performance of face recognition
system. Local spectrum features are extracted using overlap sub
block window that are mapped on the face image. For each of this
block, spatial domain is transformed to frequency domain using
DFT. A low frequency coefficient is preserved by discarding high
frequency coefficients by applying rectangular mask on the
spectrum of the facial image. Low frequency information is non-
Gaussian in the feature space and by using combination of several
Gaussian functions that has different statistical properties, the best
feature representation can be modelled using probability density
function. The recognition process is performed using maximum
likelihood value computed using pre-calculated GMM components.
The method is tested using FERET datasets and is able to achieved
92% recognition rates.
Abstract: This study investigated some results of the use of
digital art tools by junior school children in order to discover if these
tools could promote artistic ability and creativity. The study considers
the ease of use and usefulness of the tools as well as how to assess
artwork produced by digital means. As the use of these tools is a
relatively new development in Art education, this study may help
educators in their choice of which tools to use and when to use them.
The study also aims to present a model for the assessment of
students’ artistic development and creativity by studying their artistic
activity. This model can help in determining differences in students’
creative ability and could be useful both for teachers, as a means of
assessing digital artwork, and for students, by providing the
motivation to use the tools to their fullest extent. Sixteen students
aged nine to ten years old were observed and recorded while they
used the digital drawing tools. The study found that, according to the
students’ own statements, it was not the ease of use but the successful
effects the tools provided which motivated the children to use them.
Abstract: The purpose of this presentation is to describe an interdisciplinary teaching program that integrates physical education concepts using a philosophical approach. The presentation includes a review of: a) the philosophy of American education, b) the philosophy of sports and physical education, c) the interdisciplinary physical education program, d) professional development programs, (e) the Success of this physical education program, f) future of physical education. This unique interdisciplinary program has been implemented in an urban school physical education discipline in East Orange, New Jersey for over 10 years.
During the program the students realize that the bodies go through different experiences. The body becomes a place where a child can recognize in an enjoyable way to express and perceive particular feelings or mental states. Children may distinguish themselves to have high abilities in the social or other domains but low abilities in the field of athletics.
The goal of this program for the individuals is to discover new skills, develop and demonstrate age appropriate mastery level at different tasks, therefore the program consists of 9 to 12 sports, including many game. Each successful experience increases the awareness ability. Engaging in sports and physical activities are social movements involving groups of children in situations such as teams, friends, and recreational settings, which serve as a primary socializing agent for teaching interpersonal skills. As a result of this presentation the audience will reflect and explore how to structure a physical education program to integrate interdisciplinary subjects with philosophical concepts.
Abstract: The objective of this study was to assess whether
living in proximity to a roofing fiber cement factory in southern
Thailand was associated with physical, mental, social, and spiritual
health domains measured in a self-reported health risk assessment
(HRA) questionnaire. A cross-sectional study was conducted among
community members divided into two groups: near population (living
within 0-2km of factory) and far population (living within 2-5km of
factory) (N=198). A greater proportion of those living far from the
factory (65.34%) reported physical health problems than the near
group (51.04%) (p =0.032). This study has demonstrated that the near
population group had higher proportion of participants with positive
ratings on mental assessment (30.34%) and social health impacts
(28.42%) than far population group (10.59% and 16.67%,
respectively) (p
Abstract: Human motion capture has become one of the major
area of interest in the field of computer vision. Some of the major
application areas that have been rapidly evolving include the
advanced human interfaces, virtual reality and security/surveillance
systems. This study provides a brief overview of the techniques and
applications used for the markerless human motion capture, which
deals with analyzing the human motion in the form of mathematical
formulations. The major contribution of this research is that it
classifies the computer vision based techniques of human motion
capture based on the taxonomy, and then breaks its down into four
systematically different categories of tracking, initialization, pose
estimation and recognition. The detailed descriptions and the
relationships descriptions are given for the techniques of tracking and
pose estimation. The subcategories of each process are further
described. Various hypotheses have been used by the researchers in
this domain are surveyed and the evolution of these techniques have
been explained. It has been concluded in the survey that most
researchers have focused on using the mathematical body models for
the markerless motion capture.
Abstract: A large amount of data is typically stored in relational
databases (DB). The latter can efficiently handle user queries which
intend to elicit the appropriate information from data sources.
However, direct access and use of this data requires the end users to
have an adequate technical background, while they should also cope
with the internal data structure and values presented. Consequently
the information retrieval is a quite difficult process even for IT or DB
experts, taking into account the limited contributions of relational
databases from the conceptual point of view. Ontologies enable users
to formally describe a domain of knowledge in terms of concepts and
relations among them and hence they can be used for unambiguously
specifying the information captured by the relational database.
However, accessing information residing in a database using
ontologies is feasible, provided that the users are keen on using
semantic web technologies. For enabling users form different
disciplines to retrieve the appropriate data, the design of a Graphical
User Interface is necessary. In this work, we will present an
interactive, ontology-based, semantically enable web tool that can be
used for information retrieval purposes. The tool is totally based on
the ontological representation of underlying database schema while it
provides a user friendly environment through which the users can
graphically form and execute their queries.
Abstract: An investigation into Cahn-Hilliard equation was
carried out through numerical simulation to identify a possible phase
separation for one and two dimensional domains. It was observed that
this equation can reproduce important mass fluxes necessary for
phase separation within the miscibility gap and for coalescence of
particles.
Abstract: A knowledge-based expert system with the acronym
RASPE is developed as an application tool to help decision makers in
construction companies make informed decisions about managing
risks in pipeline construction projects. Choosing to use expert
systems from all available artificial intelligence techniques is due to
the fact that an expert system is more suited to representing a
domain’s knowledge and the reasoning behind domain-specific
decisions. The knowledge-based expert system can capture the
knowledge in the form of conditional rules which represent various
project scenarios and potential risk mitigation/response actions. The
built knowledge in RASPE is utilized through the underlying
inference engine that allows the firing of rules relevant to a project
scenario into consideration. Paper provides an overview of the
knowledge acquisition process and goes about describing the
knowledge structure which is divided up into four major modules.
The paper shows one module in full detail for illustration purposes
and concludes with insightful remarks.
Abstract: In this paper, a new trend for improvement in semianalytical
method based on scale boundaries in order to solve the 2D
elastodynamic problems is provided. In this regard, only the
boundaries of the problem domain discretization are by specific subparametric
elements. Mapping functions are uses as a class of higherorder
Lagrange polynomials, special shape functions, Gauss-Lobatto-
Legendre numerical integration, and the integral form of the weighted
residual method, the matrix is diagonal coefficients in the equations
of elastodynamic issues. Differences between study conducted and
prior research in this paper is in geometry production procedure of
the interpolation function and integration of the different is selected.
Validity and accuracy of the present method are fully demonstrated
through two benchmark problems which are successfully modeled
using a few numbers of DOFs. The numerical results agree very well
with the analytical solutions and the results from other numerical
methods.
Abstract: Physics Education Research (PER) results have shown
that students do not achieve the expected level of competency in
understanding the concepts of different domains of Physics learning
when taught by the traditional teaching methods, the concepts of
Electricity and Magnetism (E&M) being one among them.
Simulation being one of the valuable instructional tools renders an
opportunity to visualize varied experiences with such concepts.
Considering the electric force concept which requires extensive use
of vector representations, we report here the outcome of the research
results pertaining to the student understanding of this concept and the
role of simulation in using vector representation. The simulation
platform provides a positive impact on the use of vector
representation.
The first stage of this study involves eliciting and analyzing
student responses to questions that probe their understanding of the
concept of electrostatic force and this is followed by four stages of
student interviews as they use the interactive simulations of electric
force in one dimension. Student responses to the questions are
recorded in real time using electronic pad. A validation test interview
is conducted to evaluate students' understanding of the electric force
concept after using interactive simulation. Results indicate lack of
procedural knowledge of the vector representation. The study
emphasizes the need for the choice of appropriate simulation and
mode of induction for learning.
Abstract: Job Scheduling plays an important role for efficient
utilization of grid resources available across different domains and
geographical zones. Scheduling of jobs is challenging and NPcomplete.
Evolutionary / Swarm Intelligence algorithms have been
extensively used to address the NP problem in grid scheduling.
Artificial Bee Colony (ABC) has been proposed for optimization
problems based on foraging behaviour of bees. This work proposes a
modified ABC algorithm, Cluster Heterogeneous Earliest First Min-
Min Artificial Bee Colony (CHMM-ABC), to optimally schedule
jobs for the available resources. The proposed model utilizes a novel
Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm
along with Min-Min algorithm to identify the initial food source.
Simulation results show the performance improvement of the
proposed algorithm over other swarm intelligence techniques.
Abstract: Examining existing experimental results for shallow
rigid foundations subjected to vertical centric load (N), accompanied
or not with a bending moment (M), two main non-linear mechanisms
governing the cyclic response of the soil-foundation system can be
distinguished: foundation uplift and soil yielding. A soil-foundation
failure limit, is defined as a domain of resistance in the two
dimensional (2D) load space (N, M) inside of which lie all the
admissible combinations of loads; these latter correspond to a pure
elastic, non-linear elastic or plastic behavior of the soil-foundation
system, while the points lying on the failure limit correspond to a
combination of loads leading to a failure of the soil-foundation
system. In this study, the proposed resistance domain is constructed
analytically based on mechanics. Original elastic limit, uplift
initiation limit and iso-uplift limits are constructed inside this
domain. These limits give a prediction of the mechanisms activated
for each combination of loads applied to the foundation. A
comparison of the proposed failure limit with experimental tests
existing in the literature shows interesting results. Also, the
developed uplift initiation limit and iso-uplift curves are confronted
with others already proposed in the literature and widely used due to
the absence of other alternatives, and remarkable differences are
noted, showing evident errors in the past proposals and relevant
accuracy for those given in the present work.
Abstract: The Simulation based VLSI Implementation of
FELICS (Fast Efficient Lossless Image Compression System)
Algorithm is proposed to provide the lossless image compression and
is implemented in simulation oriented VLSI (Very Large Scale
Integrated). To analysis the performance of Lossless image
compression and to reduce the image without losing image quality
and then implemented in VLSI based FELICS algorithm. In FELICS
algorithm, which consists of simplified adjusted binary code for
Image compression and these compression image is converted in
pixel and then implemented in VLSI domain. This parameter is used
to achieve high processing speed and minimize the area and power.
The simplified adjusted binary code reduces the number of arithmetic
operation and achieved high processing speed. The color difference
preprocessing is also proposed to improve coding efficiency with
simple arithmetic operation. Although VLSI based FELICS
Algorithm provides effective solution for hardware architecture
design for regular pipelining data flow parallelism with four stages.
With two level parallelisms, consecutive pixels can be classified into
even and odd samples and the individual hardware engine is
dedicated for each one. This method can be further enhanced by
multilevel parallelisms.
Abstract: Science and technology has a major impact on many
societal domains such as communication, medicine, food,
transportation, etc. However, this dominance of modern technology
can have a negative unintended impact on indigenous systems, and in
particular on indigenous foods. This problem serves as a motivation
to this study whose aim is to examine the perceptions of learners on
the usefulness of Information and Communication Technologies
(ICTs) for learning about indigenous foods. This aim will be
subdivided into two types of research objectives. The design and
identification of theories and models will be achieved using literature
content analysis. The objective on the empirical testing of such
theories and models will be achieved through the survey of
Hospitality studies learners from different schools in the iLembe and
Umgungundlovu Districts of the South African Kwazulu-Natal
province. SPSS is used to quantitatively analyze the data collected by
the questionnaire of this survey using descriptive statistics and
Pearson correlations after the assessment of the validity and the
reliability of the data. The main hypothesis behind this study is that
there is a connection between the demographics of learners, their
perceptions on the usefulness of ICTs for learning about indigenous
foods, and the following personality and eLearning related theories
constructs: Computer self-efficacy, Trust in ICT systems, and
Conscientiousness; as suggested by existing studies on learning
theories. This hypothesis was fully confirmed by the survey
conducted by this study except for the demographic factors where
gender and age were not found to be determinant factors of learners’
perceptions on the usefulness of ICTs for learning about indigenous
foods.