Abstract: Based on assumptions of neo-classical economics and
rational choice / public choice theory, this paper investigates the
regulation of industrial land use in Taiwan by homeowners
associations (HOAs) as opposed to traditional government
administration. The comparison, which applies the transaction cost
theory and a polynomial regression analysis, manifested that HOAs
are superior to conventional government administration in terms of
transaction costs and overall efficiency. A case study that compares
Taiwan-s commonhold industrial park, NangKang Software Park, to
traditional government counterparts using limited data on the costs
and returns was analyzed. This empirical study on the relative
efficiency of governmental and private institutions justified the
important theoretical proposition. Numerical results prove the
efficiency of the established model.
Abstract: Modern managements of water distribution system
(WDS) need water quality models that are able to accurately predict
the dynamics of water quality variations within the distribution system
environment. Before water quality models can be applied to solve
system problems, they should be calibrated. Although former
researchers use GA solver to calibrate relative parameters, it is
difficult to apply on the large-scale or medium-scale real system for
long computational time. In this paper a new method is designed
which combines both macro and detailed model to optimize the water
quality parameters. This new combinational algorithm uses radial
basis function (RBF) metamodeling as a surrogate to be optimized for
the purpose of decreasing the times of time-consuming water quality
simulation and can realize rapidly the calibration of pipe wall reaction
coefficients of chlorine model of large-scaled WDS. After two cases
study this method is testified to be more efficient and promising, and
deserve to generalize in the future.
Abstract: Development of motor car safety devices has reduced
fatality rates in car accidents. Yet despite this increase in car safety,
neck injuries resulting from rear impact collisions, particularly at low
speed, remain a primary concern. In this study, FEA(Finite Element
Analysis) of seat was performed to evaluate neck injuries in rear
impact. And the FEA result was verified by comparison with the actual
test results. The dummy used in FE model and actual test is BioRID II
which is regarded suitable for rear impact collision analysis. A
threshold of the BioRID II neck injury indicators was also proposed to
upgrade seat performance in order to reduce whiplash injury. To
optimize the seat for a low-speed rear impact collision, a method was
proposed, which is multi-objective optimization idea using DOE
(Design of Experiments) results.
Abstract: In this paper we present a new multichannel high
voltage driver box to connect up to six MOEMS mirror devices to it that have resonant and also quasistatically driven actuating electrodes. It is possible to drive all resonant axes synchronously
while the amplitude of them can individually be controlled by separate microcontrollers that also operate the quasistatic axes.
Circuit simulations are compared with the measurements done on the
real system and also show the robust driving performance of a
MOEMS mirror.
Abstract: This paper aims at identifying and analyzing the
knowledge transmission channels in textile and clothing clusters
located in Brazil and in Europe. Primary data was obtained through
interviews with key individuals. The collection of primary data was
carried out based on a questionnaire with ten categories of indicators
of knowledge transmission. Secondary data was also collected
through a literature review and through international organizations
sites. Similarities related to the use of the main transmission channels
of knowledge are observed in all cases. The main similarities are:
influence of suppliers of machinery, equipment and raw materials;
imitation of products and best practices; training promoted by
technical institutions and businesses; and cluster companies being
open to acquire new knowledge. The main differences lie in the
relationship between companies, where in Europe the intensity of this
relationship is bigger when compared to Brazil. The differences also
occur in importance and frequency of the relationship with the
government, with the cultural environment, and with the activities of
research and development. It is also found factors that reduce the
importance of geographical proximity in transmission of knowledge,
and in generating trust and the establishment of collaborative
behavior.
Abstract: This paper includes a review of three physics simulation packages that can be used to provide researchers with a virtual ground for modeling, implementing and simulating complex models, as well as testing their control methods with less cost and time of development. The inverted pendulum model was used as a test bed for comparing ODE, DANCE and Webots, while Linear State Feedback was used to control its behavior. The packages were compared with respect to model creation, solving systems of differential equation, data storage, setting system variables, control the experiment and ease of use. The purpose of this paper is to give an overview about our experience with these environments and to demonstrate some of the benefits and drawbacks involved in practice for each package.
Abstract: This paper covered a series of key points in terms of 2D to 3D stereoscopic conversion. A successfully applied stereoscopic conversion approach in current visual effects industry was presented. The purpose of this paper is to cover a detailed workflow and concept, which has been successfully used in 3D stereoscopic conversion for feature films in visual effects industry, and therefore to clarify the process in stereoscopic conversion production and provide a clear idea for those entry-level artists to improve an overall understanding of 3D stereoscopic in digital compositing field as well as to the higher education factor of visual effects and hopefully inspire further collaboration and participants particularly between academia and industry.
Abstract: The ElectroEncephaloGram (EEG) is useful for
clinical diagnosis and biomedical research. EEG signals often
contain strong ElectroOculoGram (EOG) artifacts produced
by eye movements and eye blinks especially in EEG recorded
from frontal channels. These artifacts obscure the underlying
brain activity, making its visual or automated inspection
difficult. The goal of ocular artifact removal is to remove
ocular artifacts from the recorded EEG, leaving the underlying
background signals due to brain activity. In recent times,
Independent Component Analysis (ICA) algorithms have
demonstrated superior potential in obtaining the least
dependent source components. In this paper, the independent
components are obtained by using the JADE algorithm (best
separating algorithm) and are classified into either artifact
component or neural component. Neural Network is used for
the classification of the obtained independent components.
Neural Network requires input features that exactly represent
the true character of the input signals so that the neural
network could classify the signals based on those key
characters that differentiate between various signals. In this
work, Auto Regressive (AR) coefficients are used as the input
features for classification. Two neural network approaches
are used to learn classification rules from EEG data. First, a
Polynomial Neural Network (PNN) trained by GMDH (Group
Method of Data Handling) algorithm is used and secondly,
feed-forward neural network classifier trained by a standard
back-propagation algorithm is used for classification and the
results show that JADE-FNN performs better than JADEPNN.
Abstract: This study aimed at developing visualization tools for integrating CloudSat images and Water Vapor Satellite images. KML was used for integrating data from CloudSat Satellite and GMS-6 Water Vapor Satellite. CloudSat 2D images were transformed into 3D polygons in order to achieve 3D images. Before overlaying the images on Google Earth, GMS-6 water vapor satellite images had to be rescaled into linear images. Web service was developed using webMathematica. Shoreline from GMS-6 images was compared with shoreline from LandSat images on Google Earth for evaluation. The results showed that shoreline from GMS-6 images was highly matched with the shoreline in LandSat images from Google Earth. For CloudSat images, the visualizations were compared with GMS-6 images on Google Earth. The results showed that CloudSat and GMS-6 images were highly correlated.
Abstract: The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.
Abstract: Certifications such as the Passive House Standard aim to reduce the final space heating energy demand of residential buildings. Space conditioning, notably heating, is responsible for nearly 70% of final residential energy consumption in Europe. There is therefore significant scope for the reduction of energy consumption through improvements to the energy efficiency of residential buildings. However, these certifications totally overlook the energy embodied in the building materials used to achieve this greater operational energy efficiency. The large amount of insulation and the triple-glazed high efficiency windows require a significant amount of energy to manufacture. While some previous studies have assessed the life cycle energy demand of passive houses, including their embodied energy, these rely on incomplete assessment techniques which greatly underestimate embodied energy and can lead to misleading conclusions. This paper analyses the embodied and operational energy demands of a case study passive house using a comprehensive hybrid analysis technique to quantify embodied energy. Results show that the embodied energy is much more significant than previously thought. Also, compared to a standard house with the same geometry, structure, finishes and number of people, a passive house can use more energy over 80 years, mainly due to the additional materials required. Current building energy efficiency certifications should widen their system boundaries to include embodied energy in order to reduce the life cycle energy demand of residential buildings.
Abstract: In this paper, we present user pattern learning
algorithm based MDSS (Medical Decision support system) under
ubiquitous. Most of researches are focus on hardware system, hospital
management and whole concept of ubiquitous environment even
though it is hard to implement. Our objective of this paper is to design
a MDSS framework. It helps to patient for medical treatment and
prevention of the high risk patient (COPD, heart disease, Diabetes).
This framework consist database, CAD (Computer Aided diagnosis
support system) and CAP (computer aided user vital sign prediction
system). It can be applied to develop user pattern learning algorithm
based MDSS for homecare and silver town service. Especially this
CAD has wise decision making competency. It compares current vital
sign with user-s normal condition pattern data. In addition, the CAP
computes user vital sign prediction using past data of the patient. The
novel approach is using neural network method, wireless vital sign
acquisition devices and personal computer DB system. An intelligent
agent based MDSS will help elder people and high risk patients to
prevent sudden death and disease, the physician to get the online
access to patients- data, the plan of medication service priority (e.g.
emergency case).
Abstract: Organizational culture fosters innovation, and innovation is the main engine to be sustained within the uncertainty market. Like other countries, the construction industry significantly contributes to the economy, society and technology of Malaysia, yet, innovation is still considered slow compared to other industries such as manufacturing. Given the important role of an architect as the key player and the contributor of new ideas in the construction industry, there is a call to identify the issue and improve the current situation by focusing on the architectural firms. In addition, the existing studies tend to focus only on a few dimensions of organizational culture and very few studies consider whether innovation is being generated or adopted. Hence, the present research tends to fill in the gap by identifying the organizational cultures that foster or hinder innovation generation and/or innovation adoption, and propose a model of organizational culture and innovation generation and/or adoption.
Abstract: This paper proposes the application of a hierarchical fuzzy system (HFS) based on multi-input power system stabilizer (MPSS) and also Static Var Compensator (SVC) in multi-machine environment.The number of rules grows exponentially with the number of variables in a conventional fuzzy logic system. The proposed HFS method is developed to solve this problem. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. In fact, by using HFS the total number of involved rules increases only linearly with the number of input variables. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type Power system stabilizer (PSS). Phasor model of SVC is described and used in this paper. The performances of MPSS, Conventional power system stabilizer (CPSS), hierarchical Fuzzy Multi-input Power System Stabilizer (HFMPSS) and the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. By using digital simulations the comparative study is illustrated. It can be seen that the proposed PSS is performing satisfactorily within the whole range of disturbances.
Abstract: Single-pole switching scheme is widely used in the
Extra High Voltage system. However, the substantial negativesequence
current injected to the turbine-generators imposes the
electromagnetic (E/M) torque of double system- frequency
components during the dead time (between single-pole clearing and
line reclosing). This would induce supersynchronous resonance
(SPSR) torque amplifications on low pressure turbine generator
blades and even lead to fatigue damage. This paper proposes the
design of a mechanical filter (MF) with natural frequency close to
double-system frequency. From the simulation results, it is found that
such a filter not only successfully damps the resonant effect, but also
has the characteristics of feasibility and compact.
Abstract: The modern telecommunication industry demands
higher capacity networks with high data rate. Orthogonal frequency
division multiplexing (OFDM) is a promising technique for high data
rate wireless communications at reasonable complexity in wireless
channels. OFDM has been adopted for many types of wireless
systems like wireless local area networks such as IEEE 802.11a, and
digital audio/video broadcasting (DAB/DVB). The proposed research
focuses on a concatenated coding scheme that improve the
performance of OFDM based wireless communications. It uses a
Redundant Residue Number System (RRNS) code as the outer code
and a convolutional code as the inner code. Here, a direct conversion
of analog signal to residue domain is done to reduce the conversion
complexity using sigma-delta based parallel analog-to-residue
converter. The bit error rate (BER) performances of the proposed
system under different channel conditions are investigated. These
include the effect of additive white Gaussian noise (AWGN),
multipath delay spread, peak power clipping and frame start
synchronization error. The simulation results show that the proposed
RRNS-Convolutional concatenated coding (RCCC) scheme provides
significant improvement in the system performance by exploiting the
inherent properties of RRNS.
Abstract: Selection of maize (Zea mays) hybrids with wide adaptability across diverse farming environments is important, prior to recommending them to achieve a high rate of hybrid adoption. Grain yield of 14 maize hybrids, tested in a randomized completeblock design with four replicates across 22 environments in Iran, was analyzed using site regression (SREG) stability model. The biplot technique facilitates a visual evaluation of superior genotypes, which is useful for cultivar recommendation and mega-environment identification. The objectives of this study were (i) identification of suitable hybrids with both high mean performance and high stability (ii) to determine mega-environments for maize production in Iran. Biplot analysis identifies two mega-environments in this study. The first mega-environments included KRM, KSH, MGN, DZF A, KRJ, DRB, DZF B, SHZ B, and KHM, where G10 hybrid was the best performing hybrid. The second mega-environment included ESF B, ESF A, and SHZ A, where G4 hybrid was the best hybrid. According to the ideal-hybrid biplot, G10 hybrid was better than all other hybrids, followed by the G1 and G3 hybrids. These hybrids were identified as best hybrids that have high grain yield and high yield stability. GGE biplot analysis provided a framework for identifying the target testing locations that discriminates genotypes that are high yielding and stable.
Abstract: Crucial information barely visible to the human eye is
often embedded in a series of low resolution images taken of the
same scene. Super resolution reconstruction is the process of
combining several low resolution images into a single higher
resolution image. The ideal algorithm should be fast, and should add
sharpness and details, both at edges and in regions without adding
artifacts. In this paper we propose a super resolution blind
reconstruction technique for linearly degraded images. In our
proposed technique the algorithm is divided into three parts an image
registration, wavelets based fusion and an image restoration. In this
paper three low resolution images are considered which may sub
pixels shifted, rotated, blurred or noisy, the sub pixel shifted images
are registered using affine transformation model; A wavelet based
fusion is performed and the noise is removed using soft thresolding.
Our proposed technique reduces blocking artifacts and also
smoothens the edges and it is also able to restore high frequency
details in an image. Our technique is efficient and computationally
fast having clear perspective of real time implementation.
Abstract: The operation performance of a valveless micro-pump
is strongly dependent on the shape of connected nozzle/diffuser and
Reynolds number. The aims of present work are to compare the
performance curves of micropump with the original straight
nozzle/diffuser and contoured nozzle/diffuser under different back
pressure conditions. The tested valveless micropumps are assembled
of five pieces of patterned PMMA plates with hot-embracing
technique. The structures of central chamber, the inlet/outlet
reservoirs and the connected nozzle/diffuser are fabricated with laser
cutting machine. The micropump is actuated with circular-type PZT
film embraced on the bottom of central chamber. The deformation of
PZT membrane with various input voltages is measured with a
displacement laser probe. A simple testing facility is also constructed
to evaluate the performance curves for comparison.
In order to observe the evaluation of low Reynolds number
multiple vortex flow patterns within the micropump during suction
and pumping modes, the unsteady, incompressible laminar
three-dimensional Reynolds-averaged Navier-Stokes equations are
solved. The working fluid is DI water with constant thermo-physical
properties. The oscillating behavior of PZT film is modeled with the
moving boundary wall in way of UDF program. With the dynamic
mesh method, the instants pressure and velocity fields are obtained
and discussed.Results indicated that the volume flow rate is not
monotony increased with the oscillating frequency of PZT film,
regardless of the shapes of nozzle/diffuser. The present micropump
can generate the maximum volume flow rate of 13.53 ml/min when
the operation frequency is 64Hz and the input voltage is 140 volts.
The micropump with contoured nozzle/diffuser can provide 7ml/min
flow rate even when the back pressure is up to 400 mm-H2O. CFD
results revealed that the flow central chamber was occupied with
multiple pairs of counter-rotating vortices during suction and
pumping modes. The net volume flow rate over a complete
oscillating periodic of PZT
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.