Abstract: Data warehousing success is not high enough. User
dissatisfaction and failure to adhere to time frames and budgets are
too common. Most traditional information systems practices are
rooted in hard systems thinking. Today, the great systems thinkers
are forgotten by information systems developers. A data warehouse
is still a system and it is worth investigating whether systems
thinkers such as Churchman can enhance our practices today. This
paper investigates data warehouse development practices from a
systems thinking perspective. An empirical investigation is done in
order to understand the everyday practices of data warehousing
professionals from a systems perspective. The paper presents a
model for the application of Churchman-s systems approach in data
warehouse development.
Abstract: In this study, communities of ammonia-oxidizing
archaea (AOA) and ammonia-oxidizing bacteria (AOB) in nitrifying
activated sludge (NAS) prepared by enriching sludge from a
municipal wastewater treatment plant in three continuous-flow
reactors receiving an inorganic medium containing different
ammonium concentrations of 2, 10, and 30 mM NH4
+-N (NAS2,
NAS10, and NAS30, respectively) were investigated using molecular
analysis. Results suggested that almost all AOA clones from NAS2,
NAS10, and NAS30 fell into the same AOA cluster and AOA
communities in NAS2 and NAS10 were more diverse than those of
NAS30. In contrast to AOA, AOB communities obviously shifted
from the seed sludge to enriched NASs and in each enriched NAS,
communities of AOB varied particularly. The seed sludge contained
members of N. communis cluster and N. oligotropha cluster. After it
was enriched under various ammonium loads, members of N.
communis cluster disappeared from all enriched NASs. AOB with
high affinity to ammonia presented in NAS 2, AOB with low affinity
to ammonia presented in NAS 30, and both types of AOB survived in
NAS 10. These demonstrated that ammonium load significantly
influenced AOB communities, but not AOA communities in enriched
NASs.
Abstract: This paper is concerned with an investigation into the
localized non-stability of a thin elastic orthotropic semi-infinite plate.
In this study, a semi-infinite plate, simply supported on two edges
and different boundary conditions, clamped, hinged, sliding contact
and free on the other edge, are considered. The mathematical model
is used and a general solution is presented the conditions under which
localized solutions exist are investigated.
Abstract: This paper aims to argue that religion and Faith-based Organizations (FBOs) contribute to building democratic process through the provision of education in Sierra Leone. Sierra Leone experienced a civil war from 1991 to 2002 and about 70 percent of the population lives in poverty. While the government has been in the process of rebuilding the nation, many forms of Civil Society Organizations (CSOs), including FBOs, have played a significant role in promoting social development. Education plays an important role in supporting people-s democratic movements through knowledge acquisition, spiritual enlightenment and empowerment. This paper discusses religious tolerance in Sierra Leone and how FBOs have contributed to the provision of primary education in Sierra Leone. This study is based on the author-s field research, which involved interviews with teachers and development stakeholders, notably government officials, Non-governmental Organizations (NGOs) and FBOs, as well as questionnaires completed by pupils, parents and teachers.
Abstract: An accurate procedure to determine free vibrations of
beams and plates is presented.
The natural frequencies are exact solutions of governing vibration
equations witch load to a nonlinear homogeny system.
The bilinear and linear structures considered simulate a bridge.
The dynamic behavior of this one is analyzed by using the theory of
the orthotropic plate simply supported on two sides and free on the
two others. The plate can be excited by a convoy of constant or
harmonic loads. The determination of the dynamic response of the
structures considered requires knowledge of the free frequencies and
the shape modes of vibrations. Our work is in this context. Indeed,
we are interested to develop a self-consistent calculation of the Eigen
frequencies.
The formulation is based on the determination of the solution of
the differential equations of vibrations. The boundary conditions
corresponding to the shape modes permit to lead to a homogeneous
system. Determination of the noncommonplace solutions of this
system led to a nonlinear problem in Eigen frequencies.
We thus, develop a computer code for the determination of the
eigenvalues. It is based on a method of bisection with interpolation
whose precision reaches 10 -12. Moreover, to determine the
corresponding modes, the calculation algorithm that we develop uses
the method of Gauss with a partial optimization of the "pivots"
combined with an inverse power procedure. The Eigen frequencies
of a plate simply supported along two opposite sides while
considering the two other free sides are thus analyzed. The results
could be generalized with the case of a beam by regarding it as a
plate with low width.
We give, in this paper, some examples of treated cases. The
comparison with results presented in the literature is completely
satisfactory.
Abstract: This paper shows the results obtained in the analysis
of the impact of distributed generation (DG) on distribution losses
and presents a new algorithm to the optimal allocation of distributed
generation resources in distribution networks. The optimization is
based on a Hybrid Genetic Algorithm and Particle Swarm
Optimization (HGAPSO) aiming to optimal DG allocation in
distribution network. Through this algorithm a significant
improvement in the optimization goal is achieved. With a numerical
example the superiority of the proposed algorithm is demonstrated in
comparison with the simple genetic algorithm.
Abstract: The paper shows how the CASMAS modeling language,
and its associated pervasive computing architecture, can be
used to facilitate continuity of care by providing members of patientcentered
communities of care with a support to cooperation and
knowledge sharing through the usage of electronic documents and
digital devices. We consider a scenario of clearly fragmented care to
show how proper mechanisms can be defined to facilitate a better
integration of practices and information across heterogeneous care
networks. The scenario is declined in terms of architectural components
and cooperation-oriented mechanisms that make the support
reactive to the evolution of the context where these communities
operate.
Abstract: Nowadays there are many methods for representing
knowledge such as semantic network, neural network, and conceptual
graphs. Nonetheless, these methods are not sufficiently efficient
when applied to perform and deduce on knowledge domains about
supporting in general education such as algebra, analysis or plane
geometry. This leads to the introduction of computational network
which is a useful tool for representation knowledge base, especially
for computational knowledge, especially knowledge domain about
general education. However, when dealing with a practical problem,
we often do not immediately find a new solution, but we search
related problems which have been solved before and then proposing
an appropriate solution for the problem. Besides that, when finding
related problems, we have to determine whether the result of them
can be used to solve the practical problem or not. In this paper, the
extension model of computational network has been presented. In this
model, Sample Problems, which are related problems, will be used
like the experience of human about practical problem, simulate the
way of human thinking, and give the good solution for the practical
problem faster and more effectively. This extension model is applied
to construct an automatic system for solving algebraic problems in
middle school.
Abstract: The flow field over a flat roof model building has been numerically investigated in order to determine threedimensional CFD guidelines for the calculation of the turbulent flow over a structure immersed in an atmospheric boundary layer. To this purpose, a complete validation campaign has been performed through a systematic comparison of numerical simulations with wind tunnel experimental data. Wind tunnel measurements and numerical predictions have been compared for five different vertical positions, respectively from the upstream leading edge to the downstream bottom edge of the analyzed model. Flow field characteristics in the neighborhood of the building model have been numerically investigated, allowing a quantification of the capabilities of the CFD code to predict the flow separation and the extension of the recirculation regions. The proposed calculations have allowed the development of a preliminary procedure to be used as guidance in selecting the appropriate grid configuration and corresponding turbulence model for the prediction of the flow field over a three-dimensional roof architecture dominated by flow separation.
Abstract: Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.
Abstract: This paper describes a novel approach for deriving
modules from protein-protein interaction networks, which combines
functional information with topological properties of the network.
This approach is based on weighted clustering coefficient, which
uses weights representing the functional similarities between the
proteins. These weights are calculated according to the semantic
similarity between the proteins, which is based on their Gene
Ontology terms. We recently proposed an algorithm for identification
of functional modules, called SWEMODE (Semantic WEights for
MODule Elucidation), that identifies dense sub-graphs containing
functionally similar proteins. The rational underlying this approach is
that each module can be reduced to a set of triangles (protein triplets
connected to each other). Here, we propose considering semantic
similarity weights of all triangle-forming edges between proteins. We
also apply varying semantic similarity thresholds between
neighbours of each node that are not neighbours to each other (and
hereby do not form a triangle), to derive new potential triangles to
include in module-defining procedure. The results show an
improvement of pure topological approach, in terms of number of
predicted modules that match known complexes.
Abstract: A prime cordial labeling of a graph G with vertex set V is a bijection f from V to {1, 2, ..., |V |} such that each edge uv is assigned the label 1 if gcd(f(u), f(v)) = 1 and 0 if gcd(f(u), f(v)) > 1, then the number of edges labeled with 0 and the number of edges labeled with 1 differ by at most 1. In this paper we exhibit some characterization results and new constructions on prime cordial graphs.
Abstract: In this paper, we present a novel approach to accurately
detect text regions including shop name in signboard images with
complex background for mobile system applications. The proposed
method is based on the combination of text detection using edge
profile and region segmentation using fuzzy c-means method. In the
first step, we perform an elaborate canny edge operator to extract all
possible object edges. Then, edge profile analysis with vertical and
horizontal direction is performed on these edge pixels to detect
potential text region existing shop name in a signboard. The edge
profile and geometrical characteristics of each object contour are
carefully examined to construct candidate text regions and classify the
main text region from background. Finally, the fuzzy c-means
algorithm is performed to segment and detected binarize text region.
Experimental results show that our proposed method is robust in text
detection with respect to different character size and color and can
provide reliable text binarization result.
Abstract: Learning is the acquisition of new mental schemata, knowledge, abilities and skills which can be used to solve problems potentially more successfully. The learning process is optimum when it is assisted and personalized. Learning is not a single activity, but should involve many possible activities to make learning become meaningful. Many e-learning applications provide facilities to support teaching and learning activities. One way to identify whether the e-learning system is being used by the learners is through the number of hits that can be obtained from the e-learning system's log data. However, we cannot rely solely to the number of hits in order to determine whether learning had occurred meaningfully. This is due to the fact that meaningful learning should engage five characteristics namely active, constructive, intentional, authentic and cooperative. This paper aims to analyze the e-learning activities that is meaningful to learning. By focusing on the meaningful learning characteristics, we match it to the corresponding Moodle e-learning activities. This analysis discovers the activities that have high impact to meaningful learning, as well as activities that are less meaningful. The high impact activities is given high weights since it become important to meaningful learning, while the low impact has less weight and said to be supportive e-learning activities. The result of this analysis helps us categorize which e-learning activities that are meaningful to learning and guide us to measure the effectiveness of e-learning usage.
Abstract: This paper proposes a vertical beamforming concept
to a cellular network employing Fractional Frequency Reuse
technique including with cell sectorization. Two different beams are
utilized in cell-center and cell-edge, separately. The proposed concept
is validated through computer simulation in term of SINR and
channel capacity. Also, comparison when utilizing horizontal and
vertical beam formation is in focus. The obtained results indicate
that the proposed concept can improve the performance of the
cellular networks comparing with the one using horizontal
beamforming.
Abstract: Due to the limited lifetime of the nodes in ad hoc and sensor networks, energy efficiency needs to be an important design consideration in any routing algorithm. It is known that by employing a virtual backbone in a wireless network, the efficiency of any routing scheme for the network can be improved. One common design for routing protocols in mobile ad hoc networks is to use positioning information; we use the node-s geometric locations to introduce an algorithm that can construct the virtual backbone structure locally in 3D environment. The algorithm construction has a constant time.
Abstract: An induced acyclic graphoidal cover of a graph G is a
collection ψ of open paths in G such that every path in ψ has atleast
two vertices, every vertex of G is an internal vertex of at most one
path in ψ, every edge of G is in exactly one path in ψ and every
member of ψ is an induced path. The minimum cardinality of an
induced acyclic graphoidal cover of G is called the induced acyclic
graphoidal covering number of G and is denoted by ηia(G) or ηia.
Here we find induced acyclic graphoidal cover for some classes of
graphs.
Abstract: The predictability of masonry arch bridges and their
behaviour is widely considered doubtful due to the lack of knowledge
about the conditions of a given masonry arch bridge. The assessment
methods for masonry arch bridges are MEXE, ARCHIE, RING and
Frame Analysis Method. The material properties of the masonry and
fill material are extremely difficult to determine accurately.
Consequently, it is necessary to examine the effect of load dispersal
angle through the fill material, the effect of variations in the stiffness
of the masonry, the tensile strength of the masonry mortar continuum
and the compressive strength of the masonry mortar continuum. It is
also important to understand the effect of fill material on load
dispersal angle to determine their influence on ratings. In this paper a
series of parametric studies, to examine the sensitivity of assessment
ratings to the various sets of input data required by the frame analysis
method, are carried out.
Abstract: In this paper, algorithms for the automatic localisation
of two anatomical soft tissue landmarks of the head the medial
canthus (inner corner of the eye) and the tragus (a small, pointed,
cartilaginous flap of the ear), in CT images are describet. These
landmarks are to be used as a basis for an automated image-to-patient
registration system we are developing. The landmarks are localised
on a surface model extracted from CT images, based on surface
curvature and a rule based system that incorporates prior knowledge
of the landmark characteristics. The approach was tested on a dataset
of near isotropic CT images of 95 patients. The position of the
automatically localised landmarks was compared to the position of
the manually localised landmarks. The average difference was 1.5
mm and 0.8 mm for the medial canthus and tragus, with a maximum
difference of 4.5 mm and 2.6 mm respectively.The medial canthus
and tragus can be automatically localised in CT images, with
performance comparable to manual localisation
Abstract: Ontologies and tagging systems are two different ways to organize the knowledge present in the current Web. In this paper we propose a simple method to model folksonomies, as tagging systems, with ontologies. We show the scalability of the method using real data sets. The modeling method is composed of a generic ontology that represents any folksonomy and an algorithm to transform the information contained in folksonomies to the generic ontology. The method allows representing folksonomies at any instant of time.