Abstract: Incompressible Navier-Stokes equations are reviewed
in this work. Three-dimensional Navier-Stokes equations are solved
analytically. The Mathematical derivation shows that the solutions
for the zero and constant pressure gradients are similar. Descriptions
of the proposed formulation and validation against two laminar
experiments and three different turbulent flow cases are reported in
this paper. Even though, the analytical solution is derived for nonreacting
flows, it could reproduce trends for cases including
combustion.
Abstract: Policies that support entrepreneurship are keys to the
generation of new business. In Brazil, seed capital, installation of
technology parks, programs and zero interest financing, economic
subsidy as Program First Innovative Company (PRIME) are
examples of incentive policies. For the implementation of PRIME, in
particular the Brazilian Innovation Agency (FINEP) decentralized
operationalization so that business incubators could select innovative
projects. This paper analyzes the program PRIME Business Incubator
Center of the State of Sergipe (CISE) after calculating the mean and
standard deviation of the grades obtained by companies in the factors
of innovation, market potential, financial return economic, market
strategy and staff and application of the Mann-Whitney test.
Abstract: Traditional higher-education classrooms allow lecturers to observe students- behaviours and responses to a particular pedagogy during learning in a way that can influence changes to the pedagogical approach. Within current e-learning systems it is difficult to perform continuous analysis of the cohort-s behavioural tendency, making real-time pedagogical decisions difficult. This paper presents a Virtual Learning Process Environment (VLPE) based on the Business Process Management (BPM) conceptual framework. Within the VLPE, course designers can model various education pedagogies in the form of learning process workflows using an intuitive flow diagram interface. These diagrams are used to visually track the learning progresses of a cohort of students. This helps assess the effectiveness of the chosen pedagogy, providing the information required to improve course design. A case scenario of a cohort of students is presented and quantitative statistical analysis of their learning process performance is gathered and displayed in realtime using dashboards.
Abstract: This paper proposes a Particle Swarm Optimization
(PSO) based technique for the optimal allocation of Distributed
Generation (DG) units in the power systems. In this paper our aim is
to decide optimal number, type, size and location of DG units for
voltage profile improvement and power loss reduction in distribution
network. Two types of DGs are considered and the distribution load
flow is used to calculate exact loss. Load flow algorithm is combined
appropriately with PSO till access to acceptable results of this
operation. The suggested method is programmed under MATLAB
software. Test results indicate that PSO method can obtain better
results than the simple heuristic search method on the 30-bus and 33-
bus radial distribution systems. It can obtain maximum loss reduction
for each of two types of optimally placed multi-DGs. Moreover,
voltage profile improvement is achieved.
Abstract: The paper relates to a catalyst, comprising copperchromium
spinel, coated on carrier γ-Al2O3. The effect of preparation
conditions on the active component composition and activity
behavior of the catalysts is discussed. It was found that the activity of
carbon monoxide, DME, formaldehyde and methanol oxidation
reaches a maximum at an active component content of 20 – 30 wt. %.
Temperature calcination at 500oC seems to be optimal for the γ–
alumina supported CuO-Cr2O3 catalysts for CO, DME, formaldehyde
and methanol oxidation. A three months industrial experiment was
carried out to elucidate the changes in the catalyst composition
during industrial exploitation of the catalyst and the main reasons for
catalyst deactivation.
It was concluded that the CuO–Cr2O3/γ–alumina supported
catalysts have enhanced activity toward CO, DME, formaldehyde
and methanol oxidation and that these catalysts are suitable for
industrial application. The main reason for catalyst deactivation
seems to be the deposition of iron and molybdenum, coming from the
main reactor, on the active component surface.
Abstract: In this paper we suggest a method for setting
electronic credits for the customers. In this method banks and
market-sites help each other to make doing large shopping through
internet so easy. By developing this system, the people who have less
money to buy most of the things they want, become able to buy all of
them just through a credit. This credit is given by market-sites
through a banking control on it. The method suggested can stop
being imprisoned because of banking debts.
Abstract: In this paper the problem of estimating the time delay
between two spatially separated noisy sinusoidal signals by system
identification modeling is addressed. The system is assumed to be
perturbed by both input and output additive white Gaussian noise. The
presence of input noise introduces bias in the time delay estimates.
Normally the solution requires a priori knowledge of the input-output
noise variance ratio. We utilize the cascade of a self-tuned filter with
the time delay estimator, thus making the delay estimates robust to
input noise. Simulation results are presented to confirm the superiority
of the proposed approach at low input signal-to-noise ratios.
Abstract: Fire disaster is the major factor to endanger the public
and environmental safety. People lost their life during fire disaster
mainly be attributed to the dense smoke and toxic gas under
combustion, which hinder the escape of people and the rescue of
firefighters under fire disaster. The smoke suppression effect of
several transitional metals oxide on the epoxy resin treated with
intumescent flame retardant and titanate couple agent
(EP/IFR/Titanate) system have been investigated. The results showed
manganese dioxide has great effect on reducing the smoke density rate
(SDR) of EP/IFR/Titanate system; however it has little effect to reduce
the maximum smoke density (MSD) of EP/IFR/Titanate system.
Copper oxide can decrease the maximum smoke density (MSD) and
smoke density rate of EP/IFR/Titanate system substantially. The MSD
and SDR of EP/IFR/Titanate system can reduce 20.3% and 39.1%
respectively when 2% of copper oxide is introduced.
Abstract: Rural villagers in Thailand have unique skill for producing craft using local materials. However, the appearance and function of their products are not suited to the demand of international market. The Thai government policy on sustainable economy emphasises the necessity to incorporate a design strategy that will draw out the unique qualities and add value to the products, while raising the satisfaction of international consumer. As an industrial designer, the author sees opportunities that design can enhance sustainability of Thai local products through the potentials that available in village-based enterprises. This research attempts to address, how best use design to practically solve the problems in the development of Thais product in. The privilege solution is expressed through the design of design strategy that supports sustain economic development of microenterprise in Thailand in the way that aligns with product design development. This consideration integrates together with global business outlook in the development of products from rural communities.
Abstract: Bagging and boosting are among the most popular re-sampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. Boosting algorithms are considered stronger than bagging on noise-free data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using an averaging methodology of bagging and boosting ensembles with 10 sub-learners in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-learners on standard benchmark datasets and the proposed ensemble gave better accuracy.
Abstract: A cognitive collaborative reinforcement learning
algorithm (CCRL) that incorporates an advisor into the learning
process is developed to improve supervised learning. An autonomous
learner is enabled with a self awareness cognitive skill to decide
when to solicit instructions from the advisor. The learner can also
assess the value of advice, and accept or reject it. The method is
evaluated for robotic motion planning using simulation. Tests are
conducted for advisors with skill levels from expert to novice. The
CCRL algorithm and a combined method integrating its logic with
Clouse-s Introspection Approach, outperformed a base-line fully
autonomous learner, and demonstrated robust performance when
dealing with various advisor skill levels, learning to accept advice
received from an expert, while rejecting that of less skilled
collaborators. Although the CCRL algorithm is based on RL, it fits
other machine learning methods, since advisor-s actions are only
added to the outer layer.
Abstract: This paper presents a model of case based corporate
memory named ReCaRo (REsource, CAse, ROle). The approach
suggested in ReCaRo decomposes the domain to model through a set
of components. These components represent the objects developed by
the company during its activity. They are reused, and sometimes,
while bringing adaptations. These components are enriched by
knowledge after each reuse. ReCaRo builds the corporate memory on
the basis of these components. It models two types of knowledge: 1)
Business Knowledge, which constitutes the main knowledge capital
of the company, refers to its basic skill, thus, directly to the
components and 2) the Experience Knowledge which is a specialised
knowledge and represents the experience gained during the handling
of business knowledge. ReCaRo builds corporate memories which
are made up of five communicating ones.
Abstract: The paper outlines the drivers behind the movement
from products to solutions in the Hi-Tech Business-to-Business
markets. The paper lists out the challenges in enabling the
transformation from products to solutions and also attempts to explore
strategic and operational recommendations based on the authors-
factual experiences with Japanese Hi-tech manufacturing
organizations. Organizations in the Hi-Tech Business-to-Business
markets are increasingly being compelled to move to a solutions model
from the conventional products model. Despite the added complexity
of solutions, successful technology commercialization can be achieved
by making prudent choices in defining a relevant solutions model, by
backing the solution model through appropriate organizational design,
and by overhauling the new product development process and
supporting infrastructure.
Abstract: In the LFC problem, the interconnections among some areas are the input of disturbances, and therefore, it is important to suppress the disturbances by the coordination of governor systems. In contrast, tie-line power flow control by TCPS located between two areas makes it possible to stabilize the system frequency oscillations positively through interconnection, which is also expected to provide a new ancillary service for the further power systems. Thus, a control strategy using controlling the phase angle of TCPS is proposed for provide active control facility of system frequency in this paper. Also, the optimum adjustment of PID controller's parameters in a robust way under bilateral contracted scenario following the large step load demands and disturbances with and without TCPS are investigated by Particle Swarm Optimization (PSO), that has a strong ability to find the most optimistic results. This newly developed control strategy combines the advantage of PSO and TCPS and has simple stricture that is easy to implement and tune. To demonstrate the effectiveness of the proposed control strategy a three-area restructured power system is considered as a test system under different operating conditions and system nonlinearities. Analysis reveals that the TCPS is quite capable of suppressing the frequency and tie-line power oscillations effectively as compared to that obtained without TCPS for a wide range of plant parameter changes, area load demands and disturbances even in the presence of system nonlinearities.
Abstract: The effects of dynamic subgrid scale (SGS) models are
investigated in variational multiscale (VMS) LES simulations of bluff
body flows. The spatial discretization is based on a mixed finite
element/finite volume formulation on unstructured grids. In the VMS
approach used in this work, the separation between the largest and the
smallest resolved scales is obtained through a variational projection
operator and a finite volume cell agglomeration. The dynamic version
of Smagorinsky and WALE SGS models are used to account for
the effects of the unresolved scales. In the VMS approach, these
effects are only modeled in the smallest resolved scales. The dynamic
VMS-LES approach is applied to the simulation of the flow around a
circular cylinder at Reynolds numbers 3900 and 20000 and to the flow
around a square cylinder at Reynolds numbers 22000 and 175000. It
is observed as in previous studies that the dynamic SGS procedure
has a smaller impact on the results within the VMS approach than in
LES. But improvements are demonstrated for important feature like
recirculating part of the flow. The global prediction is improved for
a small computational extra cost.
Abstract: This paper presents a novel approach for optimal
reconfiguration of radial distribution systems. Optimal
reconfiguration involves the selection of the best set of branches to
be opened, one each from each loop, such that the resulting radial
distribution system gets the desired performance. In this paper an
algorithm is proposed based on simple heuristic rules and identified
an effective switch status configuration of distribution system for the
minimum loss reduction. This proposed algorithm consists of two
parts; one is to determine the best switching combinations in all loops
with minimum computational effort and the other is simple optimum
power loss calculation of the best switching combination found in
part one by load flows. To demonstrate the validity of the proposed
algorithm, computer simulations are carried out on 33-bus system.
The results show that the performance of the proposed method is
better than that of the other methods.
Abstract: Cryptography, Image watermarking and E-banking are
filled with apparent oxymora and paradoxes. Random sequences are
used as keys to encrypt information to be used as watermark during
embedding the watermark and also to extract the watermark during
detection. Also, the keys are very much utilized for 24x7x365
banking operations. Therefore a deterministic random sequence is
very much useful for online applications. In order to obtain the same
random sequence, we need to supply the same seed to the generator.
Many researchers have used Deterministic Random Number
Generators (DRNGs) for cryptographic applications and Pseudo
Noise Random sequences (PNs) for watermarking. Even though,
there are some weaknesses in PN due to attacks, the research
community used it mostly in digital watermarking. On the other hand,
DRNGs have not been widely used in online watermarking due to its
computational complexity and non-robustness. Therefore, we have
invented a new design of generating DRNG using Pi-series to make it
useful for online Cryptographic, Digital watermarking and Banking
applications.
Abstract: In this paper, we propose a robust face relighting
technique by using spherical space properties. The proposed method
is done for reducing the illumination effects on face recognition.
Given a single 2D face image, we relight the face object by
extracting the nine spherical harmonic bases and the face spherical
illumination coefficients. First, an internal training illumination
database is generated by computing face albedo and face normal
from 2D images under different lighting conditions. Based on the
generated database, we analyze the target face pixels and compare
them with the training bootstrap by using pre-generated tiles. In this
work, practical real time processing speed and small image size were
considered when designing the framework. In contrast to other works,
our technique requires no 3D face models for the training process
and takes a single 2D image as an input. Experimental results on
publicly available databases show that the proposed technique works
well under severe lighting conditions with significant improvements
on the face recognition rates.
Abstract: Genetic Algorithms (GAs) are direct searching
methods which require little information from design space. This
characteristic beside robustness of these algorithms makes them to be
very popular in recent decades. On the other hand, while this method
is employed, there is no guarantee to achieve optimum results. This
obliged designer to run such algorithms more than one time to
achieve more reliable results. There are many attempts to modify the
algorithms to make them more efficient. In this paper, by application
of fractal dimension (particularly, Box Counting Method), the
complexity of design space are established for determination of
mutation and crossover probabilities (Pm and Pc). This methodology
is followed by a numerical example for more clarification. It is
concluded that this modification will improve efficiency of GAs and
make them to bring about more reliable results especially for design
space with higher fractal dimensions.
Abstract: Commercial infrastructures intended for use as leisure
retreats such as golf and ski resorts have been extensively developed in many rural areas of Japan. However, following the burst of the economic bubble in the 1990s, several existing resorts faced tough
management decisions and some were forced to close their business.
In this study, six alternative management options for restructuring the
existing golf courses (park, cemetery, biofuel production, reforestation,
pasturing and abandonment) are examined and their environmental
and economic impacts are quantitatively assessed. In addition,
restructuring scenarios of these options and an ex-ante assessment
model are developed. The scenario analysis by Monte Carlo simulation shows a clear trade-off between GHG savings and benefit/cost (B/C) ratios, of which “Restoring Nature" scenario
absorbs the most CO2 among the four scenarios considered, but its B/C
ratio is the lowest. This study can be used to select or examine options
and scenarios of golf course management and rural environmental
management policies.