Abstract: The use of a Bayesian Hierarchical Model (BHM) to interpret breath measurements obtained during a 13C Octanoic Breath Test (13COBT) is demonstrated. The statistical analysis was implemented using WinBUGS, a commercially available computer package for Bayesian inference. A hierarchical setting was adopted where poorly defined parameters associated with a delayed Gastric Emptying (GE) were able to "borrow" strength from global distributions. This is proved to be a sufficient tool to correct model's failures and data inconsistencies apparent in conventional analyses employing a Non-linear least squares technique (NLS). Direct comparison of two parameters describing gastric emptying ng ( tlag -lag phase, t1/ 2 -half emptying time) revealed a strong correlation between the two methods. Despite our large dataset ( n = 164 ), Bayesian modeling was fast and provided a successful fitting for all subjects. On the contrary, NLS failed to return acceptable estimates in cases where GE was delayed.
Abstract: The effects of equilibrium time, solution pH, and
sorption temperature of cationic methylene blue (MB) adsorption on nanoporous metallosilicoaluminophosphate ZnAPSO-34 was studied
using a batch equilibration method. UV–VIS spectroscopy was used
to obtain the adsorption isotherms at 20° C. The optimum period for
adsorption was 300 min. However, MB removal increased from
81,82 % to 94,81 %. The equilibrium adsorption data was analyzed
by using Langmuir, Freundlich and Temkin isotherm models.
Langmuir isotherm was found to be the better-fitting model and the process followed pseudo second–order kinetics. The results showed
that ZnAPSO-34 could be employed as an effective material and could be an attractive alternative for the removal of dyes and colors
from aqueous solutions.
Abstract: Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EOS) is a modified SAFT EOS with three pure component specific parameters: segment number (m), diameter (σ) and energy (ε). These PC-SAFT parameters need to be determined for each component under the conditions of interest by fitting experimental data, such as vapor pressure, density or heat capacity. PC-SAFT parameters for propane, ethylene and hydrogen in supercritical region were successfully estimated by fitting experimental density data available in literature. The regressed PCSAFT parameters were compared with the literature values by means of estimating pure component density and calculating average absolute deviation between the estimated and experimental density values. PC-SAFT parameters available in literature especially for ethylene and hydrogen estimated density in supercritical region reasonably well. However, the regressed PC-SAFT parameters performed better in supercritical region than the PC-SAFT parameters from literature.
Abstract: This paper present an effective method to accurately reconstruct and measure the 3D curve edges of small industrial parts based on stereo vision. To effectively fit the curve of the measured parts using a series of line segments in the images, a strategy from coarse to fine is employed based on multi-scale curve fitting. After reconstructing the 3D curve of a hole through a curved surface, its axis is adjusted so that it is parallel to the Z axis with least squares error and the dimensions of the hole can be calculated on the XY plane easily. Experimental results show that the presented method can accurately measure the dimensions of round holes through a curved surface.
Abstract: This paper presents a methodology towards the emulation of the electrical power consumption of the RF device during the cellular phone/handset transmission mode using the LTE technology. The emulation methodology takes the physical environmental variables and the logical interface between the baseband and the RF system as inputs to compute the emulated power dissipation of the RF device. The emulated power, in between the measured points corresponding to the discrete values of the logical interface parameters is computed as a polynomial interpolation using polynomial basis functions. The evaluation of polynomial and spline curve fitting models showed a respective divergence (test error) of 8% and 0.02% from the physically measured power consumption. The precisions of the instruments used for the physical measurements have been modeled as intervals. We have been able to model the power consumption of the RF device operating at 5MHz using homotopy between 2 continuous power consumptions of the RF device operating at the bandwidths 3MHz and 10MHz.
Abstract: Based on an analysis of the mechanism of degradation of optical characteristics of the ZnO-pigmented white paint by electron irradiation, a model of single molecular color centers is built. An equation that explains the relationship between the changes of variation of the ZnO-pigmented white paint-s spectrum absorptance and electron fluence is derived. The uncertain parameters in the equation can be calculated using the curve fitting by experimental data. The result indicates that the model can be applied to predict the degradation of optical characteristics of ZnO-pigmented white paint by electron radiation.
Abstract: Circle grid space filling plate is a flow conditioner with a fractal pattern and used to eliminate turbulence originating from pipe fittings in experimental fluid flow applications. In this paper, steady state, incompressible, swirling turbulent flow through circle grid space filling plate has been studied. The solution and the analysis were carried out using finite volume CFD solver FLUENT 6.2. Three turbulence models were used in the numerical investigation and their results were compared with the pressure drop correlation of BS EN ISO 5167-2:2003. The turbulence models investigated here are the standard k-ε, realizable k-ε, and the Reynolds Stress Model (RSM). The results showed that the RSM model gave the best agreement with the ISO pressure drop correlation. The effects of circle grids space filling plate thickness and Reynolds number on the flow characteristics have been investigated as well.
Abstract: The cardiovascular system has become the most
important subject of clinical research, particularly measurement of
arterial blood flow. Therefore correct determination of arterial
diameter is crucial. We propose a novel, semi-automatic method for
artery lumen detection. The method is based on Gaussian probability
function. Usability of our proposed method was assessed by
analyzing ultrasound B-mode CFA video sequences acquired from
eleven healthy volunteers. The correlation coefficient between the
manual and semi-automatic measurement of arterial diameter was
0.996. Our proposed method for detecting artery boundary is novel
and accurate enough for the measurement of artery diameter.
Abstract: The temperature distribution and the heat transfer
rates through a multi-layer door of a furnace were investigated. The
inside of the door was in contact with hot air and the other side of the
door was in contact with room air. Radiation heat transfer from the
walls of the furnace to the door and the door to the surrounding area
was included in the problem. This work is a two dimensional steady
state problem. The Churchill and Chu correlation was used to find
local convection heat transfer coefficients at the surfaces of the
furnace door. The thermophysical properties of air were the functions
of the temperatures. Polynomial curve fitting for the fluid properties
were carried out. Finite difference method was used to discretize for
conduction heat transfer within the furnace door. The Gauss-Seidel
Iteration was employed to compute the temperature distribution in
the door.
The temperature distribution in the horizontal mid plane of the
furnace door in a two dimensional problem agrees with the one
dimensional problem. The local convection heat transfer coefficients
at the inside and outside surfaces of the furnace door are exhibited.
Abstract: This study aimed at developing a forecasting model on the number of Dengue Haemorrhagic Fever (DHF) incidence in Northern Thailand using time series analysis. We developed Seasonal Autoregressive Integrated Moving Average (SARIMA) models on the data collected between 2003-2006 and then validated the models using the data collected between January-September 2007. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The most suitable model was the SARIMA(2,0,1)(0,2,0)12 model with a Akaike Information Criterion (AIC) of 12.2931 and a Mean Absolute Percent Error (MAPE) of 8.91713. The SARIMA(2,0,1)(0,2,0)12 model fitting was adequate for the data with the Portmanteau statistic Q20 = 8.98644 ( x20,95= 27.5871, P>0.05). This indicated that there was no significant autocorrelation between residuals at different lag times in the SARIMA(2,0,1)(0,2,0)12 model.
Abstract: Psoriasis is a widespread skin disease affecting up to 2% population with plaque psoriasis accounting to about 80%. It can be identified as a red lesion and for the higher severity the lesion is usually covered with rough scale. Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. Surface roughness of lesion can be used as a scaliness feature, since existing scale on lesion surface makes the lesion rougher. The dermatologist usually assesses the severity through their tactile sense, therefore direct contact between doctor and patient is required. The problem is the doctor may not assess the lesion objectively. In this paper, a digital image analysis technique is developed to objectively determine the scaliness of the psoriasis lesion and provide the PASI scaliness score. Psoriasis lesion is modelled by a rough surface. The rough surface is created by superimposing a smooth average (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate average surface followed by a subtraction between rough and average surface to give elevation surface (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 444 lesion models. From roughness validation result, only 6 models can not be accepted (percentage error is greater than 10%). These errors occur due the scanned image quality. Roughness algorithm is validated for roughness measurement on abrasive papers at flat surface. The Pearson-s correlation coefficient of grade value (G) of abrasive paper and Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.
Abstract: In this study, the sorption of Malachite green (MG) on Hydrilla verticillata biomass, a submerged aquatic plant, was investigated in a batch system. The effects of operating parameters such as temperature, adsorbent dosage, contact time, adsorbent size, and agitation speed on the sorption of Malachite green were analyzed using response surface methodology (RSM). The proposed quadratic model for central composite design (CCD) fitted very well to the experimental data that it could be used to navigate the design space according to ANOVA results. The optimum sorption conditions were determined as temperature - 43.5oC, adsorbent dosage - 0.26g, contact time - 200min, adsorbent size - 0.205mm (65mesh), and agitation speed - 230rpm. The Langmuir and Freundlich isotherm models were applied to the equilibrium data. The maximum monolayer coverage capacity of Hydrilla verticillata biomass for MG was found to be 91.97 mg/g at an initial pH 8.0 indicating that the optimum sorption initial pH. The external and intra particle diffusion models were also applied to sorption data of Hydrilla verticillata biomass with MG, and it was found that both the external diffusion as well as intra particle diffusion contributes to the actual sorption process. The pseudo-second order kinetic model described the MG sorption process with a good fitting.
Abstract: Realistic 3D face model is more precise in representing
pose, illumination, and expression of face than 2D face model so that it
can be utilized usefully in various applications such as face recognition,
games, avatars, animations, and etc.
In this paper, we propose a 3D face modeling method based on 3D
dense morphable shape model. The proposed 3D modeling method
first constructs a 3D dense morphable shape model from 3D face scan
data obtained using a 3D scanner. Next, the proposed method extracts
and matches facial landmarks from 2D image sequence containing a
face to be modeled, and then reconstructs 3D vertices coordinates of
the landmarks using a factorization-based SfM technique. Then, the
proposed method obtains a 3D dense shape model of the face to be
modeled by fitting the constructed 3D dense morphable shape model
into the reconstructed 3D vertices. Also, the proposed method makes a
cylindrical texture map using 2D face image sequence. Finally, the
proposed method generates a 3D face model by rendering the 3D dense
face shape model using the cylindrical texture map. Through building
processes of 3D face model by the proposed method, it is shown that
the proposed method is relatively easy, fast and precise.
Abstract: Radial flow reactor was focused for large scale
methanol synthesis and in which the heat transfer type was cross-flow.
The effects of operating conditions including the reactor inlet air
temperature, the heating pipe temperature and the air flow rate on the
cross-flow heat transfer was investigated and the results showed that
the temperature profile of the area in front of the heating pipe was
slightly affected by all the operating conditions. The main area whose
temperature profile was influenced was the area behind the heating
pipe. The heat transfer direction according to the air flow directions. In
order to provide the basis for radial flow reactor design calculation, the
dimensionless number group method was used for data fitting of the
bed effective thermal conductivity and the wall heat transfer
coefficient which was calculated by the mathematical model with the
product of Reynolds number and Prandtl number. The comparison of
experimental data and calculated value showed that the calculated
value fit the experimental data very well and the formulas could be
used for reactor designing calculation.
Abstract: Recently, lots of researchers are attracted to retrieving
multimedia database by using some impression words and their values.
Ikezoe-s research is one of the representatives and uses eight pairs of
opposite impression words. We had modified its retrieval interface and
proposed '2D-RIB'. In '2D-RIB', after a retrieval person selects a
single basic music, the system visually shows some other music
around the basic one along relative position. He/she can select one of
them fitting to his/her intention, as a retrieval result. The purpose of
this paper is to improve his/her satisfaction level to the retrieval result
in 2D-RIB. One of our extensions is to define and introduce the
following two measures: 'melody goodness' and 'general acceptance'.
We implement them in different five combinations. According to an
evaluation experiment, both of these two measures can contribute to
the improvement. Another extension is three types of customization.
We have implemented them and clarified which customization is
effective.
Abstract: Camera calibration is an indispensable step for augmented
reality or image guided applications where quantitative information
should be derived from the images. Usually, a camera
calibration is obtained by taking images of a special calibration object
and extracting the image coordinates of projected calibration marks
enabling the calculation of the projection from the 3d world coordinates
to the 2d image coordinates. Thus such a procedure exhibits
typical steps, including feature point localization in the acquired
images, camera model fitting, correction of distortion introduced by
the optics and finally an optimization of the model-s parameters. In
this paper we propose to extend this list by further step concerning
the identification of the optimal subset of images yielding the smallest
overall calibration error. For this, we present a Monte Carlo based
algorithm along with a deterministic extension that automatically
determines the images yielding an optimal calibration. Finally, we
present results proving that the calibration can be significantly
improved by automated image selection.
Abstract: Bone remodeling occurs by the balanced action of
bone resorbing osteoclasts (OC) and bone-building osteoblasts.
Increased bone resorption by excessive OC activity contributes
to malignant and non-malignant diseases including osteoporosis.
To study OC differentiation and function, OC formed in
in vitro cultures are currently counted manually, a tedious
procedure which is prone to inter-observer differences. Aiming
for an automated OC-quantification system, classification of
OC and precursor cells was done on fluorescence microscope
images based on the distinct appearance of fluorescent nuclei.
Following ellipse fitting to nuclei, a combination of eight
features enabled clustering of OC and precursor cell nuclei.
After evaluating different machine-learning techniques, LOGREG
achieved 74% correctly classified OC and precursor cell
nuclei, outperforming human experts (best expert: 55%). In
combination with the automated detection of total cell areas,
this system allows to measure various cell parameters and most
importantly to quantify proteins involved in osteoclastogenesis.
Abstract: In this study, a software has been developed to predict
the optimum conditions for drying of cotton based yarn bobbins in a
hot air dryer. For this purpose, firstly, a suitable drying model has
been specified using experimental drying behavior for different
values of drying parameters. Drying parameters in the experiments
were drying temperature, drying pressure, and volumetric flow rate of
drying air. After obtaining a suitable drying model, additional curve
fittings have been performed to obtain equations for drying time and
energy consumption taking into account the effects of drying
parameters. Then, a software has been developed using Visual Basic
programming language to predict the optimum drying conditions for
drying time and energy consumption.