Abstract: The term Enterprise 2.0 (E2.0) describes a collection of organizational and IT practices that help organizations establish flexible work models, visible knowledge-sharing practices, and higher levels of community participation. E2.0 parallels and builds on another term commonly being used in the industry – Web 2.0. E2.0 represents also new packaging for strategic collaboration and Knowledge Management (KM). Organizations rely on collaboration and KM initiatives to attain innovation, growth, productivity, and performance goals.
Abstract: Undoubtedly, chassis is one of the most important
parts of a vehicle. Chassis that today are produced for vehicles are
made up of four parts. These parts are jointed together by screwing.
Transverse parts are called cross member.
This study reviews the stress generated by cyclic laboratory loads
in front cross member of Peugeot 405. In this paper the finite element
method is used to simulate the welding process and to determine the
physical response of the spot-welded joints. Analysis is done by the
Abaqus software.
The Stresses generated in cross member structure are generally
classified into two groups: The stresses remained in form of residual
stresses after welding process and the mechanical stress generated by
cyclic load. Accordingly the total stress must be obtained by
determining residual stress and mechanical stress separately and then
sum them according to the superposition principle.
In order to improve accuracy, material properties including
physical, thermal and mechanical properties were supposed to be
temperature-dependent. Simulation shows that maximum Von Misses
stresses are located at special points. The model results are then
compared to the experimental results which are reported by
producing factory and good agreement is observed.
Abstract: Color constancy algorithms are generally based on the
simplified assumption about the spectral distribution or the reflection
attributes of the scene surface. However, in reality, these assumptions
are too restrictive. The methodology is proposed to extend existing
algorithm to applying color constancy locally to image patches rather
than globally to the entire images.
In this paper, a method based on low-level image features using
superpixels is proposed. Superpixel segmentation partition an image
into regions that are approximately uniform in size and shape. Instead
of using entire pixel set for estimating the illuminant, only superpixels
with the most valuable information are used. Based on large scale
experiments on real-world scenes, it can be derived that the estimation
is more accurate using superpixels than when using the entire image.
Abstract: In projects like waterpower, transportation and
mining, etc., proving up the rock-mass structure and hidden tectonic
to estimate the geological body-s activity is very important.
Integrating the seismic results, drilling and trenching data,
CSAMT method was carried out at a planning dame site in southwest
China to evaluate the stability of a deformation. 2D and imitated 3D
inversion resistivity results of CSAMT method were analyzed. The
results indicated that CSAMT was an effective method for defining
an outline of deformation body to several hundred meters deep; the
Lung Pan Deformation was stable in natural conditions; but uncertain
after the future reservoir was impounded.
This research presents a good case study of the fine surveying and
research on complex geological structure and hidden tectonic in
engineering project.
Abstract: This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compares with earlier methods.
Abstract: Modern organizations operate under the pressure of
dynamic and often unpredictable changes, both in external and
internal environment. Market success, in this context, requires a
particular competence in the form of flexibility, interpreted here both
on the level of individuals and on the level of organization. This
paper addresses the changes taking place in the sphere of
employment, as observed in economic entities operating on Polish
market. Based on own empirical studies, the authors focus on the
progressing trend of ‘flexibilization’ of employment, particularly in
the context of transformations in organizational structure, designed to
facilitate the transition into management by projects and
differentiation of labor forms.
Abstract: Artificial Neural Network (ANN) has been
extensively used for classification of heart sounds for its
discriminative training ability and easy implementation. However, it
suffers from overparameterization if the number of nodes is not
chosen properly. In such cases, when the dataset has redundancy
within it, ANN is trained along with this redundant information that
results in poor validation. Also a larger network means more
computational expense resulting more hardware and time related
cost. Therefore, an optimum design of neural network is needed
towards real-time detection of pathological patterns, if any from heart
sound signal. The aims of this work are to (i) select a set of input
features that are effective for identification of heart sound signals and
(ii) make certain optimum selection of nodes in the hidden layer for a
more effective ANN structure. Here, we present an optimization
technique that involves Singular Value Decomposition (SVD) and
QR factorization with column pivoting (QRcp) methodology to
optimize empirically chosen over-parameterized ANN structure.
Input nodes present in ANN structure is optimized by SVD followed
by QRcp while only SVD is required to prune undesirable hidden
nodes. The result is presented for classifying 12 common
pathological cases and normal heart sound.
Abstract: To help the client to select a competent agent
construction enterprise (ACE), this study aims to investigate the
selection standards by using the Fuzzy Analytic Hierarchy Process
(FAHP) and build an evaluation mathematical model with Grey
Relational Analysis (GRA). According to the outputs of literature
review, four orderly levels are established within the model, taking the
consideration of various agent construction models in practice. Then,
the process of applying FAHP and GRA is discussed in detailed.
Finally, through a case study, this paper illustrates how to apply these
methods in getting the weights of each standard and the final
assessment result.