Abstract: Both prognostic and diagnostic modes of a 3D baroclinic
model in hydrodynamic and sediment transport models of
the Princeton Ocean Model (POM) were conducted to separate
prognose and diagnose effects of different hydrodynamic factors on
transport of suspended sediment discharged from the rivers to the
Gulf of Thailand (GoT). Both transport modes of suspended sediment
distribution in the GoT were numerically simulated. It could be
concluded that the suspended sediment discharged from the rivers
around the GoT. Most of sediments in estuaries and coastal areas are
deposited outside the GoT under the condition of wind-driven current,
and very small amount of the sediments of them are transported
faraway. On the basis of wind forcing, sediments from the lower
GoT to the upper GoT are mainly transported south-northwestward
and also continuously moved north-southwestward. An obvious 3D
characteristic of suspended sediment transport is produced in the
wind-driven current residual circulation condition. In this study, the
transport patterns at the third layer are generally consistent with
the typhoon-induced strong currents in two case studies of Typhoon
Linda 1997. The case studies presented the prognostic and diagnostic
modes during 00UTC28OCT1997 to 12UTC06NOV1997 in a short
period with the current condition for pre-operation of the suspended
sediment transport model in estuaries and coastal areas.
Abstract: The purpose of this paper is to investigate the
influence of a number of variables on the conditional mean and
conditional variance of credit spread changes. The empirical analysis
in this paper is conducted within the context of bivariate GARCH-in-
Mean models, using the so-called BEKK parameterization. We show
that credit spread changes are determined by interest-rate and equityreturn
variables, which is in line with theory as provided by the
structural models of default. We also identify the credit spread
change volatility as an important determinant of credit spread
changes, and provide evidence on the transmission of volatility
between the variables under study.
Abstract: This paper examines the use of mechanical aerator for
oxidation-ditch process. The rotor, which controls the aeration, is the
main component of the aeration process. Therefore, the objective of
this study is to find out the variations in overall oxygen transfer
coefficient (KLa) and aeration efficiency (AE) for different
configurations of aerator by varying the parameters viz. speed of
aerator, depth of immersion, blade tip angles so as to yield higher
values of KLa and AE. Six different configurations of aerator were
developed and fabricated in the laboratory and were tested for abovementioned
parameters. The curved blade rotor (CBR) emerged as a
potential aerator with blade tip angle of 47°.
The mathematical models are developed for predicting the
behaviour of CBR w.r.t kLa and power. In laboratory studies, the
optimum value of KLa and AE were observed to be 10.33 h-1 and
2.269 kg O2/ kWh.
Abstract: Traditional wind tunnel models are meticulously machined from metal in a process that can take several months. While very precise, the manufacturing process is too slow to assess a new design's feasibility quickly. Rapid prototyping technology makes this concurrent study of air vehicle concepts via computer simulation and in the wind tunnel possible. This paper described the Affects layer thickness models product with rapid prototyping on Aerodynamic Coefficients for Constructed wind tunnel testing models. Three models were evaluated. The first model was a 0.05mm layer thickness and Horizontal plane 0.1μm (Ra) second model was a 0.125mm layer thickness and Horizontal plane 0.22μm (Ra) third model was a 0.15mm layer thickness and Horizontal plane 4.6μm (Ra). These models were fabricated from somos 18420 by a stereolithography (SLA). A wing-body-tail configuration was chosen for the actual study. Testing covered the Mach range of Mach 0.3 to Mach 0.9 at an angle-of-attack range of -2° to +12° at zero sideslip. Coefficients of normal force, axial force, pitching moment, and lift over drag are shown at each of these Mach numbers. Results from this study show that layer thickness does have an effect on the aerodynamic characteristics in general; the data differ between the three models by fewer than 5%. The layer thickness does have more effect on the aerodynamic characteristics when Mach number is decreased and had most effect on the aerodynamic characteristics of axial force and its derivative coefficients.
Abstract: This paper studies the optimum design for reducing
optical loss of an 8x8 mechanical type optical switch due to the
temperature change. The 8x8 optical switch is composed of a base, 8
input fibers, 8 output fibers, 3 fixed mirrors and 17 movable mirrors.
First, an innovative switch configuration is proposed with
thermal-compensated design. Most mechanical type optical switches
have a disadvantage that their precision and accuracy are influenced
by the ambient temperature. Therefore, the thermal-compensated
design is to deal with this situation by using materials with different
thermal expansion coefficients (α). Second, a parametric modeling
program is developed to generate solid models for finite element
analysis, and the thermal and structural behaviors of the switch are
analyzed. Finally, an integrated optimum design program, combining
Autodesk Inventor Professional software, finite element analysis
software, and genetic algorithms, is developed for improving the
thermal behaviors that the optical loss of the switch is reduced. By
changing design parameters of the switch in the integrated design
program, the final optimum design that satisfies the design constraints
and specifications can be found.
Abstract: Speckled images arise when coherent microwave,
optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar
systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted
by speckle noise is complicated by the nature of the noise and is not
as straightforward as detection and estimation in additive noise. In
this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The
motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this
context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series
of Laguerre weighted exponential functions, resulting in a doubly
stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form.
It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an
exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.
Abstract: Wireless sensor networks (WSN) consists of many
sensor nodes that are placed on unattended environments such as
military sites in order to collect important information.
Implementing a secure protocol that can prevent forwarding forged
data and modifying content of aggregated data and has low delay
and overhead of communication, computing and storage is very
important. This paper presents a new protocol for concealed data
aggregation (CDA). In this protocol, the network is divided to
virtual cells, nodes within each cell produce a shared key to send
and receive of concealed data with each other. Considering to data
aggregation in each cell is locally and implementing a secure
authentication mechanism, data aggregation delay is very low and
producing false data in the network by malicious nodes is not
possible. To evaluate the performance of our proposed protocol, we
have presented computational models that show the performance
and low overhead in our protocol.
Abstract: This paper examines the problem of strategic
management in highly turbulent dynamic business environmental
conditions. As shown the high complexity of the problem can be
managed with the use of System Dynamics Models and Computer
Simulation in obtaining insights, and thorough understanding of the
interdependencies between the organizational structure and the
business environmental elements, so that effective product –market
strategies can be designed. Simulation reveals the underlying forces
that hold together the structure of an organizational system in relation
to its environment. Such knowledge will contribute to the avoidance
of fundamental planning errors and enable appropriate proactive well
focused action.
Abstract: Diabetes Mellitus is a chronic metabolic disorder, where the improper management of the blood glucose level in the diabetic patients will lead to the risk of heart attack, kidney disease and renal failure. This paper attempts to enhance the diagnostic accuracy of the advancing blood glucose levels of the diabetic patients, by combining principal component analysis and wavelet neural network. The proposed system makes separate blood glucose prediction in the morning, afternoon, evening and night intervals, using dataset from one patient covering a period of 77 days. Comparisons of the diagnostic accuracy with other neural network models, which use the same dataset are made. The comparison results showed overall improved accuracy, which indicates the effectiveness of this proposed system.
Abstract: Recognizing human action from videos is an active
field of research in computer vision and pattern recognition. Human
activity recognition has many potential applications such as video
surveillance, human machine interaction, sport videos retrieval and
robot navigation. Actually, local descriptors and bag of visuals words
models achieve state-of-the-art performance for human action
recognition. The main challenge in features description is how to
represent efficiently the local motion information. Most of the
previous works focus on the extension of 2D local descriptors on 3D
ones to describe local information around every interest point. In this
paper, we propose a new spatio-temporal descriptor based on a spacetime
description of moving points. Our description is focused on an
Accordion representation of video which is well-suited to recognize
human action from 2D local descriptors without the need to 3D
extensions. We use the bag of words approach to represent videos.
We quantify 2D local descriptor describing both temporal and spatial
features with a good compromise between computational complexity
and action recognition rates. We have reached impressive results on
publicly available action data set
Abstract: Wind is among the potential energy resources which
can be harnessed to generate wind energy for conversion into
electrical power. Due to the variability of wind speed with time and
height, it becomes difficult to predict the generated wind energy more
optimally. In this paper, an attempt is made to establish a
probabilistic model fitting the wind speed data recorded at
Makambako site in Tanzania. Wind speeds and direction were
respectively measured using anemometer (type AN1) and wind Vane
(type WD1) both supplied by Delta-T-Devices at a measurement
height of 2 m. Wind speeds were then extrapolated for the height of
10 m using power law equation with an exponent of 0.47. Data were
analysed using MINITAB statistical software to show the variability
of wind speeds with time and height, and to determine the underlying
probability model of the extrapolated wind speed data. The results
show that wind speeds at Makambako site vary cyclically over time;
and they conform to the Weibull probability distribution. From these
results, Weibull probability density function can be used to predict
the wind energy.
Abstract: In this paper, a bond graph dynamic model for a valvecontrolled
hydraulic cylinder has been developed. A simplified bond
graph model of the inter-actuator interactions in a multi-cylinder
hydraulic system has also been presented. The overall bond graph
model of a valve-controlled hydraulic cylinder was developed by
combining the bond graph sub-models of the pump, spool valve and
the actuator using junction structures. Causality was then assigned
in order to obtain a computational model which could be simulated.
The causal bond graph model of the hydraulic cylinder was verified
by comparing the open loop state responses to those of an ODE
model which had been developed in literature based on the same
assumptions. The results were found to correlate very well both
in the shape of the curves, magnitude and the response times,
thus indicating that the developed model represents the hydraulic
dynamics of a valve-controlled cylinder. A simplified model for interactuator
interaction was presented by connecting an effort source with
constant pump pressure to the zero-junction from which the cylinders
in a multi-cylinder system are supplied with a constant pressure from
the pump. On simulating the state responses of the developed model
under different situations of cylinder operations, indicated that such
a simple model can be used to predict the inter-actuator interactions.
Abstract: This study explored the relationship between
psychological traits, demographics and financial behavioral biases for
individual investors in Taiwan stock market. By using questionnaire
survey method conducted in 2010, there are 554 valid convenient
samples collected to examine the determinants of three types of
behavioral biases. Based on literature review, two hypothesized
models are constructed and further used to evaluate the effects of big
five personality traits and demographic variables on investment biases
through Structural Equation Model (SEM) analysis. The results
showed that investment biases of individual investors are significantly
related to four personality traits as well as some demographics.
Abstract: α-Pinene is the main component of the most
turpentine oils. The hydration of α-pinene with acid catalysts leads to
a complex mixture of monoterpenes. In order to obtain more valuable
products, the α-pinene in the turpentine can be hydrated in dilute
mineral acid solutions to produce α-terpineol. The design of
separation processes requires information on phase equilibrium and
related thermodynamic properties. This paper reports the results of
study on liquid-liquid equilibrium (LLE) of system containing α-
pinene + water and α-terpineol + water.
Binary LLE for α-pinene + water system, and α-terpineol + water
systems were determined by experiment at 301K and atmospheric
pressure. The two component mixture was stirred for about 30min,
then the mixture was left for about 2h for complete phase separation.
The composition of both phases was analyzed by using a Gas
Chromatograph. The experimental data were correlated by
considering both NRTL and UNIQUAC activity coefficient models.
The LLE data for the system of α-pinene + water and α-terpineol +
water were correlated successfully by the NRTL model. The
experimental data were not satisfactorily fitted by the UNIQUAC
model. The NRTL model (α =0.3) correlates the LLE data for the
system of α-pinene + water at 301K with RMSD of 0.0404%. And
the NRTL model (α =0.61) at 301K with RMSD of 0.0058 %. The
NRTL model (α =0.3) correlates the LLE data for the system of α-
terpineol + water at 301K with RMSD of 0.1487% and the NRTL
model (α =0.6) at 301K with RMSD of 0.0032%, between the
experimental and calculated mole fractions.
Abstract: The search for factors that influence user behavior has remained an important theme for both the academic and practitioner Information Systems Communities. In this paper we examine relevant user behaviors in the phase after adoption and investigate two factors that are expected to influence such behaviors, namely User Involvement (UI) and Personal Innovativeness in IT (PIIT). We conduct a field study to examine how these factors influence postadoption behavior and how they are interrelated. Building on theoretical premises and prior empirical findings, we propose and test two alternative models of the relationship between these factors. Our results reveal that the best explanation of post-adoption behavior is provided by the model where UI and PIIT independently influence post-adoption behavior. Our findings have important implications for research and practice. To that end, we offer directions for future research.
Abstract: Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.
Abstract: Lateral expansion is a factor defining the level of
confinement in reinforced concrete columns. Therefore, predicting
the lateral strain relationship with axial strain becomes an important
issue. Measuring lateral strains in experiments is difficult and only
few report experimental lateral strains. Among the existing analytical
formulations, two recent models are compared with available test
results in this paper with shortcomings highlighted. A new analytical
model is proposed here for lateral strain axial strain relationship and
is based on the supposition that the concrete behaves linear elastic in
the early stages of loading and then nonlinear hardening up to the
peak stress and then volumetric expansion. The proposal for the
lateral strain axial strain relationship after the peak stress is mainly
based on the hypothesis that the plastic lateral strain varies linearly
with the plastic axial strain and it is shown that this is related to the
lateral confinement level.
Abstract: In this work, a characterization and modeling of
packet loss of a Voice over Internet Protocol (VoIP) communication
is developed. The distributions of the number of consecutive received
and lost packets (namely gap and burst) are modeled from the
transition probabilities of two-state and four-state model.
Measurements show that both models describe adequately the burst
distribution, but the decay of gap distribution for non-homogeneous
losses is better fit by the four-state model. The respective
probabilities of transition between states for each model were
estimated with a proposed algorithm from a set of monitored VoIP
calls in order to obtain representative minimum, maximum and
average values for both models.
Abstract: In this paper three basic approaches and different
methods under each of them for extracting region of interest (ROI)
from stationary images are explored. The results obtained for each of
the proposed methods are shown, and it is demonstrated where each
method outperforms the other. Two main problems in ROI
extraction: the channel selection problem and the saliency reversal
problem are discussed and how best these two are addressed by
various methods is also seen. The basic approaches are 1) Saliency
based approach 2) Wavelet based approach 3) Clustering based
approach. The saliency approach performs well on images containing
objects of high saturation and brightness. The wavelet based
approach performs well on natural scene images that contain regions
of distinct textures. The mean shift clustering approach partitions the
image into regions according to the density distribution of pixel
intensities. The experimental results of various methodologies show
that each technique performs at different acceptable levels for
various types of images.
Abstract: In this work we study the effect of several covariates X on a censored response variable T with unknown probability distribution. In this context, most of the studies in the literature can be located in two possible general classes of regression models: models that study the effect the covariates have on the hazard function; and models that study the effect the covariates have on the censored response variable. Proposals in this paper are in the second class of models and, more specifically, on least squares based model approach. Thus, using the bootstrap estimate of the bias, we try to improve the estimation of the regression parameters by reducing their bias, for small sample sizes. Simulation results presented in the paper show that, for reasonable sample sizes and censoring levels, the bias is always smaller for the new proposals.