Abstract: We present a general comparison of punctual kriging based image restoration for different neighbourhood sizes. The formulation of the technique under consideration is based on punctual kriging and fuzzy concepts for image restoration in spatial domain. Three different neighbourhood windows are considered to estimate the semivariance at different lags for studying its effect in reduction of negative weights resulted in punctual kriging, consequently restoration of degraded images. Our results show that effect of neighbourhood size higher than 5x5 on reduction in negative weights is insignificant. In addition, image quality measures, such as structure similarity indices, peak signal to noise ratios and the new variogram based quality measures; show that 3x3 window size gives better performance as compared with larger window sizes.
Abstract: An international cooperation between educators in
Australia and the US has led to a reconceptualization of the teaching
of a library science course at Appalachian State University. The
pedagogy of Action Learning coupled with a 3D virtual learning
environment immerses students in a social constructivist learning
space that incorporates and supports interaction and reflection. The
intent of this study was to build a bridge between theory and practice
by providing students with a tool set that promoted personal and
social reflection, and created and scaffolded a community of practice.
Besides, action learning is an educational process whereby the fifty
graduate students experienced their own actions and experience to
improve performance.
Abstract: A complex valued neural network is a neural network, which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in image and vision processing. In Neural networks, radial basis functions are often used for interpolation in multidimensional space. A Radial Basis function is a function, which has built into it a distance criterion with respect to a centre. Radial basis functions have often been applied in the area of neural networks where they may be used as a replacement for the sigmoid hidden layer transfer characteristic in multi-layer perceptron. This paper aims to present exhaustive results of using RBF units in a complex-valued neural network model that uses the back-propagation algorithm (called 'Complex-BP') for learning. Our experiments results demonstrate the effectiveness of a Radial basis function in a complex valued neural network in image recognition over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error on a neural network model with RBF units. Some inherent properties of this complex back propagation algorithm are also studied and discussed.
Abstract: Development of intelligent assembly cell conception includes new solution kind of how to create structures of automated and flexible assembly system. The current trend of the final product quality increasing is affected by time analysis of the entire manufacturing process. The primary requirement of manufacturing is to produce as many products as soon as possible, at the lowest possible cost, but of course with the highest quality. Such requirements may be satisfied only if all the elements entering and affecting the production cycle are in a fully functional condition. These elements consist of sensory equipment and intelligent control elements that are essential for building intelligent manufacturing systems. Intelligent behavior of the system as the control system will repose on monitoring of important parameters of the system in the real time. Intelligent manufacturing system itself should be a system that can flexibly respond to changes in entering and exiting the process in interaction with the surroundings.
Abstract: The results obtained after incorporating the competence “creativity" to the subject Technical Drawing of the first course of the Degree in Forestry, Technical University of Madrid, are presented in this study.At first, learning activities which could serve two functions at the same time -developing students- creativity and developing other specific competences of the subject- were considered. Besides, changes in the assessment procedure were made and a method which analyzes two aspects of the assessment of the competence creativity was established. On the one hand, the products are evaluated by analyzing the outcomes obtained by students in the essays suggested and by establishing a parameter to assess the creativity expressed in those essays. On the other, an assessment of the student is directly carried out through a psychometric test which has been previously chosen by the team.Moreover, these results can be applied to similar or could be of general application.
Abstract: Dual bell nozzle is a promising one among the altitude
adaptation nozzle concepts, which offer increased nozzle
performance in rocket engines. Its advantage is the simplicity it offers
due to the absence of any additional mechanical device or movable
parts. Hence it offers reliability along with improved nozzle
performance as demanded by future launch vehicles. Among other
issues, the flow transition to the extension nozzle of a dual bell
nozzle is one of the major issues being studied in the development of
dual bell nozzle. A parameter named over-expansion factor, which
controls the value of the wall inflection angle, has been reported to
have substantial influence in this transition process. This paper
studies, through CFD and cold flow experiments, the effect of overexpansion
factor on flow transition in dual bell nozzles.
Abstract: The use of e-business in small and medium-sized
enterprises (SMEs) has been recently received an enormous attention
in information systems research by both academic and practitioners.
With the adoption of new and efficient technologies to enhance
businesses, Thai SMEs should be able to compete worldwide.
Unfortunately, most of the owners are not used to new technologies.
It is clear that most Thai SMEs prefer to work manually rather than
electronically. This paper aims to provide a fundamental conceptual
framework for E-business adoption by Thai SMEs. Rooted in
Knowledge transfer model, several factors are identified, which drive
and enable e-business adoption. By overlooking the benefits
associated with implementing new technologies, it is difficult for
Thai SMEs to perform well enough to compete globally. The paper
also helps Thai SMEs to understand factors related to E-business
adoption.
Abstract: This paper invites to dialogue and reflections on
innovation and entrepreneurship by presenting concepts of innovation
leading to the introduction of a complex theoretical framework;
Cooperative Innovation (CO-IN). CO-IN is a didactic model
enhancing and scaffolding processes of cooperation creating
innovation drawing on a Scandinavian tradition.
CO-IN is based on a cross-sectorial and multidisciplinary
approach. We introduce the concept of complementarity to help
capture the validity of diversity and we suggest the concept of “the
space in between" to understand the creation of identity as a
collective mind. We see dialogue and the use of multi modal
techniques as essential tools for conceptualizations giving possibility
for clarification of the complexity and diversity leading to decision
making based on knowledge as commons.
We introduce the didactic design and present our empirical
findings from an innovation workshop in Argentina. In a final
paragraph we reflect on the design as a support of the development of
common ground, collective mind and collective action and the
creation of knowledge as commons to facilitate innovation and
entrepreneurship.
Abstract: The main objective of this study was to demonstrate that differentiation of infected and vaccinated animals (DIVA) strategy using different ELISA tests is possible when a subunit vaccine (Haemagglutinin protein) is used to prevent Avian influenza. Special emphasis was placed on the differentiation in the serological response to different components of the AIV (Nucleoprotein, Neuraminidase, Haemagglutinin, Nucleocapsid) between chickens that were vaccinated with a whole virus kill vaccine and recombinant vaccine. Furthermore, the potential use of this DIVA strategy using ELISA assays to detect Neuraminidase 1 (N1) was analyzed as strategy in countries where the field virus is H5N1 and the vaccine used is formulated with H5N2. Detection of AIV-s antibodies to any component in serum was negative for all animals on the study days 0-13. At study day 14 the titers of antibodies against Nucleoprotein (NP) and Nucleocapsid (NC) rose in the experimental groups vaccinated with Volvac® AI KV and were negatives during all the trial in the experimental groups vaccinated with a subunit H5; significant statistically differences were observed between these groups (p < 0.05). The seroconversion either Haemagglutinin or Neuraminidase was evident after 21 days post-vaccination in the experimental groups vaccinated with the respective viral fraction. Regarding the main aim of this study and according with the results that were obtained, use a combination of different ELISA test as a DIVA strategy is feasible when the vaccination is carry out with a subunit H5 vaccine. Also is possible to use the ELISA kit to detect Neuraminidase (either N1 or N2) as a DIVA concept in countries where H5N1 is present and the vaccination programs are done with H5N2 vaccine.
Abstract: The following paper shows an interactive tool which
main purpose is to teach how to play a flute. It consists of three
stages the first one is the instruction and teaching process through a
software application, the second is the practice part when the user
starts to play the flute (hardware specially designed for this
application) this flute is capable of capturing how is being played the
flute and the final stage is the one in which the data captured are sent
to the software and the user is evaluated in order to give him / she a
correction or an acceptance
Abstract: One of the most important parts of a cement factory is
the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral
movement of air and materials, together with chemical reactions take
place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only
in exceptional case; however, a large number of the involved parameter were crossed out and an approximation model was
presented instead. This issue caused many problems for designing a
cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement rotary kiln by using
nonlinear identification technique on the Locally Linear Neuro-
Fuzzy (LLNF) model. For the first time, a simulator model as well as
a predictor one with a precise fifteen minute prediction horizon for a
cement rotary kiln is presented. These models are trained by
LOLIMOT algorithm which is an incremental tree-structure
algorithm. At the end, the characteristics of these models are expressed. Furthermore, we presented the pros and cons of these
models. The data collected from White Saveh Cement Company is used for modeling.
Abstract: Subdivision surfaces were applied to the entire
meshes in order to produce smooth surfaces refinement from coarse
mesh. Several schemes had been introduced in this area to provide a
set of rules to converge smooth surfaces. However, to compute and
render all the vertices are really inconvenient in terms of memory
consumption and runtime during the subdivision process. It will lead
to a heavy computational load especially at a higher level of
subdivision. Adaptive subdivision is a method that subdivides only at
certain areas of the meshes while the rest were maintained less
polygons. Although adaptive subdivision occurs at the selected areas,
the quality of produced surfaces which is their smoothness can be
preserved similar as well as regular subdivision. Nevertheless,
adaptive subdivision process burdened from two causes; calculations
need to be done to define areas that are required to be subdivided and
to remove cracks created from the subdivision depth difference
between the selected and unselected areas. Unfortunately, the result
of adaptive subdivision when it reaches to the higher level of
subdivision, it still brings the problem with memory consumption.
This research brings to iterative process of adaptive subdivision to
improve the previous adaptive method that will reduce memory
consumption applied on triangular mesh. The result of this iterative
process was acceptable better in memory and appearance in order to
produce fewer polygons while it preserves smooth surfaces.
Abstract: Inventory decisional environment of short life-cycle
products is full of uncertainties arising from randomness and
fuzziness of input parameters like customer demand requiring
modeling under hybrid uncertainty. Prior inventory models
incorporating fuzzy demand have unfortunately ignored stochastic
variation of demand. This paper determines an unambiguous optimal
order quantity from a set of n fuzzy observations in a newsvendor
inventory setting in presence of fuzzy random variable demand
capturing both fuzzy perception and randomness of customer
demand. The stress of this paper is in providing solution procedure
that attains optimality in two steps with demand information
availability in linguistic phrases leading to fuzziness along with
stochastic variation. The first step of solution procedure identifies
and prefers one best fuzzy opinion out of all expert opinions and the
second step determines optimal order quantity from the selected
event that maximizes profit. The model and solution procedure is
illustrated with a numerical example.
Abstract: Cavitation, usually known as a destructive
phenomenon, involves turbulent unsteady two-phase flow. Having
such features, cavitating flows have been turned to a challenging
topic in numerical studies and many researches are being done for
better understanding of bubbly flows and proposing solutions to
reduce its consequent destructive effects. Aeration may be regarded
as an effective protection against cavitation erosion in many
hydraulic structures, like gated tunnels. The paper concerns
numerical simulation of flow in discharge gated tunnel of a dam
using ing RNG k -ε model coupled with the volume of fluid (VOF)
method and the zone which is susceptible of cavitation inception in
the tunnel is predicted. In the second step, a vent is considered in the
mentioned zone for aeration and the numerical simulation is done
again to study the effects of aeration. The results show that aeration
is an impressively useful method to exclude cavitation in mentioned
tunnels.
Abstract: Guard channels improve the probability of successful
handoffs by reserving a number of channels exclusively for handoffs.
This concept has the risk of underutilization of radio spectrum due to
the fact that fewer channels are granted to originating calls even if
these guard channels are not always used, when originating calls are
starving for the want of channels. The penalty is the reduction of
total carried traffic. The optimum number of guard channels can help
reduce this problem. This paper presents fuzzy logic based guard
channel scheme wherein guard channels are reorganized on the basis
of traffic density, so that guard channels are provided on need basis.
This will help in incorporating more originating calls and hence high
throughput of the radio spectrum
Abstract: Data mining is an extraordinarily demanding field referring to extraction of implicit knowledge and relationships, which are not explicitly stored in databases. A wide variety of methods of data mining have been introduced (classification, characterization, generalization...). Each one of these methods includes more than algorithm. A system of data mining implies different user categories,, which mean that the user-s behavior must be a component of the system. The problem at this level is to know which algorithm of which method to employ for an exploratory end, which one for a decisional end, and how can they collaborate and communicate. Agent paradigm presents a new way of conception and realizing of data mining system. The purpose is to combine different algorithms of data mining to prepare elements for decision-makers, benefiting from the possibilities offered by the multi-agent systems. In this paper the agent framework for data mining is introduced, and its overall architecture and functionality are presented. The validation is made on spatial data. Principal results will be presented.
Abstract: The group mutual exclusion (GME) problem is an
interesting generalization of the mutual exclusion problem. Several
solutions of the GME problem have been proposed for message
passing distributed systems. However, none of these solutions is
suitable for real time distributed systems. In this paper, we propose a
token-based distributed algorithms for the GME problem in soft real
time distributed systems. The algorithm uses the concepts of priority
queue, dynamic request set and the process state. The algorithm uses
first come first serve approach in selecting the next session type
between the same priority levels and satisfies the concurrent
occupancy property. The algorithm allows all n processors to be
inside their CS provided they request for the same session. The
performance analysis and correctness proof of the algorithm has also
been included in the paper.
Abstract: Object: Review recent publications of patient safety
culture to investigate the relationship between leadership behavior,
safety culture, and safety performance in the healthcare industry.
Method: This study is a cross-sectional study, 350 questionnaires were
mailed to hospital workers with 195 valid responses obtained, and a
55.7% valid response rate. Confirmatory factor analysis (CFA) was
carried out to test the factor structure and determine if the composite
reliability was significant with a factor loading of >0.5, resulting in an
acceptable model fit. Results: Through the analysis of One-way
ANOVA, the results showed that physicians significantly have more
negative patient safety culture perceptions and safety performance
perceptions than non- physicians. Conclusions: The path analysis
results show that leadership behavior affects safety culture and safety
performance in the health care industry. Safety performance was
affected and improved with contingency leadership and a positive
patient safety organization culture. The study suggests improving
safety performance by providing a well-managed system that
includes: consideration of leadership, hospital worker training
courses, and a solid safety reporting system.
Abstract: Today-s economy is in a permanent change, causing
merger and acquisitions and co operations between enterprises. As a
consequence, process adaptations and realignments result in systems
integration and software development projects. Processes and
procedures to execute such projects are still reliant on craftsman-ship
of highly skilled workers. A generally accepted, industrialized
production, characterized by high efficiency and quality, seems
inevitable.
In spite of this, current concepts of software industrialization are
aimed at traditional software engineering and do not consider the
characteristics of systems integration. The present work points out
these particularities and discusses the applicability of existing
industrial concepts in the systems integration domain. Consequently
it defines further areas of research necessary to bring the field of
systems integration closer to an industrialized production, allowing a
higher efficiency, quality and return on investment.
Abstract: Intelligence tests are series of tasks designed to measure the capacity to make abstractions, to learn, and to deal with novel situations. Testing of the visual abilities of the shape understanding system (SUS) is performed based on the visual intelligence tests. In this paper the progressive matrices tests are formulated as tasks given to SUS. These tests require good visual problem solving abilities of the human subject. SUS solves these tests by performing complex visual reasoning transforming the visual forms (tests) into the string forms. The experiment proved that the proposed method, which is part of the SUS visual understanding abilities, can solve a test that is very difficult for human subject.