Abstract: Fischer-Tropsch synthesis is one of the most
important catalytic reactions that convert the synthetic gas to light
and heavy hydrocarbons. One of the main issues is selecting the type
of reactor. The slurry bubble reactor is suitable choice for Fischer-
Tropsch synthesis because of its good qualification to transfer heat
and mass, high durability of catalyst, low cost maintenance and
repair. The more common catalysts for Fischer-Tropsch synthesis are
Iron-based and Cobalt-based catalysts, the advantage of these
catalysts on each other depends on which type of hydrocarbons we
desire to produce. In this study, Fischer-Tropsch synthesis is modeled
with Iron and Cobalt catalysts in a slurry bubble reactor considering
mass and momentum balance and the hydrodynamic relations effect
on the reactor behavior. Profiles of reactant conversion and reactant
concentration in gas and liquid phases were determined as the
functions of residence time in the reactor. The effects of temperature,
pressure, liquid velocity, reactor diameter, catalyst diameter, gasliquid
and liquid-solid mass transfer coefficients and kinetic
coefficients on the reactant conversion have been studied. With 5%
increase of liquid velocity (with Iron catalyst), H2 conversions
increase about 6% and CO conversion increase about 4%, With 8%
increase of liquid velocity (with Cobalt catalyst), H2 conversions
increase about 26% and CO conversion increase about 4%. With
20% increase of gas-liquid mass transfer coefficient (with Iron
catalyst), H2 conversions increase about 12% and CO conversion
increase about 10% and with Cobalt catalyst H2 conversions increase
about 10% and CO conversion increase about 6%. Results show that
the process is sensitive to gas-liquid mass transfer coefficient and
optimum condition operation occurs in maximum possible liquid
velocity. This velocity must be more than minimum fluidization
velocity and less than terminal velocity in such a way that avoid
catalysts particles from leaving the fluidized bed.
Abstract: In this paper, we present C@sa, a multiagent system aiming at modeling, controlling and simulating the behavior of an intelligent house. The developed system aims at providing to architects, designers and psychologists a simulation and control tool for understanding which is the impact of embedded and pervasive technology on people daily life. In this vision, the house is seen as an environment made up of independent and distributed devices, controlled by agents, interacting to support user's goals and tasks.
Abstract: Sparse representation which can represent high dimensional
data effectively has been successfully used in computer vision
and pattern recognition problems. However, it doesn-t consider the
label information of data samples. To overcome this limitation,
we develop a novel dimensionality reduction algorithm namely
dscriminatively regularized sparse subspace learning(DR-SSL) in this
paper. The proposed DR-SSL algorithm can not only make use of
the sparse representation to model the data, but also can effective
employ the label information to guide the procedure of dimensionality
reduction. In addition,the presented algorithm can effectively deal
with the out-of-sample problem.The experiments on gene-expression
data sets show that the proposed algorithm is an effective tool for
dimensionality reduction and gene-expression data classification.
Abstract: Little attention has been paid to information
transmission between the portfolios of large stocks and small stocks in the Korean stock market. This study investigates the return and volatility transmission mechanisms between large and small stocks in
the Korea Exchange (KRX). This study also explores whether bad news in the large stock market leads to a volatility of the small stock
market that is larger than the good news volatility of the large stock market. By employing the Granger causality test, we found
unidirectional return transmissions from the large stocks to medium
and small stocks. This evidence indicates that pat information about
the large stocks has a better ability to predict the returns of the medium and small stocks in the Korean stock market. Moreover, by using the
asymmetric GARCH-BEKK model, we observed the unidirectional relationship of asymmetric volatility transmission from large stocks to
the medium and small stocks. This finding suggests that volatility in
the medium and small stocks following a negative shock in the large
stocks is larger than that following a positive shock in the large stocks.
Abstract: This paper is concerned with a nonautonomous three species food chain model with Crowley–Martin type functional response and time delay. Using the Mawhin-s continuation theorem in theory of degree, sufficient conditions for existence of periodic solutions are obtained.
Abstract: The success of an e-learning system is highly
dependent on the quality of its educational content and how effective,
complete, and simple the design tool can be for teachers. Educational
modeling languages (EMLs) are proposed as design languages
intended to teachers for modeling diverse teaching-learning
experiences, independently of the pedagogical approach and in
different contexts. However, most existing EMLs are criticized for
being too abstract and too complex to be understood and manipulated
by teachers. In this paper, we present a visual EML that simplifies the
process of designing learning scenarios for teachers with no
programming background. Based on the conceptual framework of the
activity theory, our resulting visual EML focuses on using Domainspecific
modeling techniques to provide a pedagogical level of
abstraction in the design process.
Abstract: This study aims to examine the determinants of
purchase intention in C2C e-commerce. Specifically the role of
instant messaging in the C2C e-commerce contextis investigated. In
addition to instant messaging, we brought in two antecedents of
purchase intention - trust and customer satisfaction - to establish a
theoretical research model. Structural equation modeling using
LISREL was used to analyze the data.We discussed the research
findings and suggested some implications for researchers and
practitioners.
Abstract: A key requirement for e-learning materials is
reusability and interoperability, that is the possibility to use at least
part of the contents in different courses, and to deliver them trough
different platforms. These features make possible to limit the cost of
new packages, but require the development of material according to
proper specifications. SCORM (Sharable Content Object Reference
Model) is a set of guidelines suitable for this purpose. A specific
adaptation project has been started to make possible to reuse existing
materials. The paper describes the main characteristics of SCORM
specification, and the procedure used to modify the existing material.
Abstract: The object of this paper is to design and analyze a
proportional – integral (PI) control for positive output elementary
super lift Luo converter (POESLLC), which is the start-of-the-art
DC-DC converter. The positive output elementary super lift Luo
converter performs the voltage conversion from positive source
voltage to positive load voltage. This paper proposes a
development of PI control capable of providing the good static and
dynamic performance compared to proportional – integralderivative
(PID) controller. Using state space average method
derives the dynamic equations describing the positive output
elementary super lift luo converter and PI control is designed. The
simulation model of the positive output elementary super lift Luo
converter with its control circuit is implemented in
Matlab/Simulink. The PI control for positive output elementary
super lift Luo converter is tested for transient region, line changes,
load changes, steady state region and also for components
variations.
Abstract: In this paper, we present an experimental testing for
a new algorithm that determines an optimal controller-s coefficients
for output variance reduction related to Linear Time Invariant (LTI)
Systems. The algorithm features simplicity in calculation, generalization
to minimal and non-minimal phase systems, and could be
configured to achieve reference tracking as well as variance reduction
after compromising with the output variance. An experiment of DCmotor
velocity control demonstrates the application of this new
algorithm in designing the controller. The results show that the
controller achieves minimum variance and reference tracking for a
preset velocity reference relying on an identified model of the motor.
Abstract: This paper proposes an improvement method of classification
efficiency in a classification model. The model is used
in a risk search system and extracts specific labels from articles
posted at bulletin board sites. The system can analyze the important
discussions composed of the articles. The improvement method
introduces ensemble learning methods that use multiple classification
models. Also, it introduces expressions related to the specific labels
into generation of word vectors. The paper applies the improvement
method to articles collected from three bulletin board sites selected
by users and verifies the effectiveness of the improvement method.
Abstract: Artifact free photoplethysmographic (PPG) signals are
necessary for non-invasive estimation of oxygen saturation (SpO2) in
arterial blood. Movement of a patient corrupts the PPGs with motion
artifacts, resulting in large errors in the computation of Sp02. This
paper presents a study on using Kalman Filter in an innovative way
by modeling both the Artillery Blood Pressure (ABP) and the
unwanted signal, additive motion artifact, to reduce motion artifacts
from corrupted PPG signals. Simulation results show acceptable
performance regarding LMS and variable step LMS, thus
establishing the efficacy of the proposed method.
Abstract: Cenozoic basalts found in Jiangsu province of eastern
China include tholeiites and alkali basalts. The present paper analyzed
the major, trace elements, rare earth elements of these Cenozoic
basalts and combined with Sr-Nd isotopic compositions proposed by
Chen et al. (1990)[1] in the literatures to discuss the petrogenesis of
these basalts and the geochemical characteristics of the source mantle.
Based on major, trace elements and fractional crystallization model
established by Brooks and Nielsen (1982)[2] we suggest that the
basaltic magma has experienced olivine + clinopyroxene fractionation
during its evolution. The chemical compositions of basaltic rocks from
Jiangsu province indicate that these basalts may belong to the same
magmatic system. Spidergrams reveal that Cenozoic basalts from
Jiangsu province have geochemical characteristics similar to those of
ocean island basalts(OIB). The slight positive Nb and Ti anomalies
found in basaltic rocks of this study suggest the presence of Ti-bearing
minerals in the mantle source and these Ti-bearing minerals had
contributed to basaltic magma during partial melting, indicating a
metasomatic event might have occurred before the partial melting.
Based on the Sr vs. Nd isotopic ratio plots, we suggest that Jiangsu
basalts may be derived from partial melting of mantle source which
may represent two-end members mixing of DMM and EM-I. Some
Jiangsu basaltic magma may be derived from partial melting of EM-I
heated by the upwelling asthenospheric mantle or asthenospheric
diapirism.
Abstract: Gene, principal unit of inheritance, is an ordered
sequence of nucleotides. The genes of eukaryotic organisms include
alternating segments of exons and introns. The region of
Deoxyribonucleic acid (DNA) within a gene containing instructions
for coding a protein is called exon. On the other hand, non-coding
regions called introns are another part of DNA that regulates gene
expression by removing from the messenger Ribonucleic acid (RNA)
in a splicing process. This paper proposes to determine splice
junctions that are exon-intron boundaries by analyzing DNA
sequences. A splice junction can be either exon-intron (EI) or intron
exon (IE). Because of the popularity and compatibility of the
artificial neural network (ANN) in genetic fields; various ANN
models are applied in this research. Multi-layer Perceptron (MLP),
Radial Basis Function (RBF) and Generalized Regression Neural
Networks (GRNN) are used to analyze and detect the splice junctions
of gene sequences. 10-fold cross validation is used to demonstrate
the accuracy of networks. The real performances of these networks
are found by applying Receiver Operating Characteristic (ROC)
analysis.
Abstract: The purpose of this paper is to present two different
approaches of financial distress pre-warning models appropriate for
risk supervisors, investors and policy makers. We examine a sample
of the financial institutions and electronic companies of Taiwan
Security Exchange (TSE) market from 2002 through 2008. We
present a binary logistic regression with paned data analysis. With
the pooled binary logistic regression we build a model including
more variables in the regression than with random effects, while the
in-sample and out-sample forecasting performance is higher in
random effects estimation than in pooled regression. On the other
hand we estimate an Adaptive Neuro-Fuzzy Inference System
(ANFIS) with Gaussian and Generalized Bell (Gbell) functions and
we find that ANFIS outperforms significant Logit regressions in both
in-sample and out-of-sample periods, indicating that ANFIS is a
more appropriate tool for financial risk managers and for the
economic policy makers in central banks and national statistical
services.
Abstract: The three-time-scale plant model of a wind power
generator, including a wind turbine, a flexible vertical shaft, a Variable
Inertia Flywheel (VIF) module, an Active Magnetic Bearing (AMB)
unit and the applied wind sequence, is constructed. In order to make
the wind power generator be still able to operate as the spindle speed
exceeds its rated speed, the VIF is equipped so that the spindle speed
can be appropriately slowed down once any stronger wind field is
exerted. To prevent any potential damage due to collision by shaft
against conventional bearings, the AMB unit is proposed to regulate
the shaft position deviation. By singular perturbation order-reduction
technique, a lower-order plant model can be established for the
synthesis of feedback controller. Two major system parameter
uncertainties, an additive uncertainty and a multiplicative uncertainty,
are constituted by the wind turbine and the VIF respectively.
Frequency Shaping Sliding Mode Control (FSSMC) loop is proposed
to account for these uncertainties and suppress the unmodeled
higher-order plant dynamics. At last, the efficacy of the FSSMC is
verified by intensive computer and experimental simulations for
regulation on position deviation of the shaft and counter-balance of
unpredictable wind disturbance.
Abstract: The main focus of the work was concerned with hydrodynamic and thermal analysis of the plate heat exchanger channel with corrugation patterns suggested to be triangular, sinusoidal, and square corrugation. This study was to numerically model and validate the triangular corrugated channel with dimensions/parameters taken from open literature, and then model/analyze both sinusoidal, and square corrugated channel referred to the triangular model. Initially, 2D modeling with local extensive analysis for triangular corrugated channel was carried out. By that, all local pressure drop, wall shear stress, friction factor, static temperature, heat flux, Nusselt number, and surface heat coefficient, were analyzed to interpret the hydrodynamic and thermal phenomena occurred in the flow. Furthermore, in order to facilitate confidence in this model, a comparison between the values predicted, and experimental results taken from literature for almost the same case, was done. Moreover, a holistic numerical study for sinusoidal and square channels together with global comparisons with triangular corrugation under the same condition, were handled. Later, a comparison between electric, and fluid cooling through varying the boundary condition was achieved. The constant wall temperature and constant wall heat flux boundary conditions were employed, and the different resulted Nusselt numbers as a consequence were justified. The results obtained can be used to come up with an optimal design, a 'compromise' between heat transfer and pressure drop.
Abstract: This paper presents an investigation of the power
penalties imposed by four-wave mixing (FWM) on G.652 (Single-
Mode Fiber - SMF), G.653 (Dispersion-Shifted Fiber - DSF), and
G.655 (Non-Zero Dispersion-Shifted Fiber - NZDSF) compliant
fibers, considering the DWDM grids suggested by the ITU-T
Recommendations G.692, and G.694.1, with uniform channel
spacing of 100, 50, 25, and 12.5 GHz. The mathematical/numerical
model assumes undepleted pumping, and shows very clearly the
deleterious effect of FWM on the performance of DWDM systems,
measured by the signal-to-noise ratio (SNR). The results make it
evident that non-uniform channel spacing is practically mandatory
for WDM systems based on DSF fibers.
Abstract: In this paper, we consider the almost periodic solutions of a discrete cooperation system with feedback controls. Assuming that the coefficients in the system are almost periodic sequences, we obtain the existence and uniqueness of the almost periodic solution which is uniformly asymptotically stable.
Abstract: The study of the transport coefficients in electronic
devices is currently carried out by analytical and empirical models.
This study requires several simplifying assumptions, generally
necessary to lead to analytical expressions in order to study the
different characteristics of the electronic silicon-based devices.
Further progress in the development, design and optimization of
Silicon-based devices necessarily requires new theory and modeling
tools. In our study, we use the PSO (Particle Swarm Optimization)
technique as a computational tool to develop analytical approaches in
order to study the transport phenomenon of the electron in crystalline
silicon as function of temperature and doping concentration. Good
agreement between our results and measured data has been found.
The optimized analytical models can also be incorporated into the
circuits simulators to study Si-based devices without impact on the
computational time and data storage.