Abstract: This paper deals with modeling and parameter
identification of nonlinear systems described by Hammerstein model
having Piecewise nonlinear characteristics such as Dead-zone
nonlinearity characteristic. The simultaneous use of both an easy
decomposition technique and the triangular basis functions leads to a
particular form of Hammerstein model. The approximation by using
Triangular basis functions for the description of the static nonlinear
block conducts to a linear regressor model, so that least squares
techniques can be used for the parameter estimation. Singular Values
Decomposition (SVD) technique has been applied to separate the
coupled parameters. The proposed approach has been efficiently
tested on academic examples of simulation.
Abstract: This paper aims to present a framework for the
organizational knowledge management, which seeks to deploy a
standardized structure for the integrated management of knowledge is
a common language based on domains, processes and global
indicators inspired by the COBIT framework 5 (ISACA, 2012),
which supports the integration of three technologies, enterprise
information architecture (EIA), the business process modeling (BPM)
and service-oriented architecture (SOA). The Gomak Framework is a
management platform that seeks to integrate the information
technology infrastructure, the structure of applications, information
infrastructure, and business logic and business model to support a
sound strategy of organizational knowledge management, low
process-based approach and concurrent engineering. Concurrent
engineering (CE) is a systematic approach to integrated product
development that respond to customer expectations, involving all
perspectives in parallel, from the beginning of the product life cycle.
(European Space Agency, 2000).
Abstract: Flow field around hypersonic vehicles is very
complex and difficult to simulate. The boundary layers are squeezed
between shock layer and body surface. Resolution of boundary layer,
shock wave and turbulent regions where the flow field has high
values is difficult of capture. Detached eddy simulation (DES) is a
modification of a RANS model in which the model switches to a
subgrid scale formulation in regions fine enough for LES
calculations. Regions near solid body boundaries and where the
turbulent length scale is less than the maximum grid dimension are
assigned the RANS mode of solution. As the turbulent length scale
exceeds the grid dimension, the regions are solved using the LES
mode. Therefore the grid resolution is not as demanding as pure LES,
thereby considerably cutting down the cost of the computation. In
this research study hypersonic flow is simulated at Mach 8 and
different angle of attacks to resolve the proper boundary layers and
discontinuities. The flow is also simulated in the long wake regions.
Mesh is little different than RANS simulations and it is made dense
near the boundary layers and in the wake regions to resolve it
properly. Hypersonic blunt cone cylinder body with frustrum at angle
5o and 10 o are simulated and there aerodynamics study is performed
to calculate aerodynamics characteristics of different geometries. The
results and then compared with experimental as well as with some
turbulence model (SA Model). The results achieved with DES
simulation have very good resolution as well as have excellent
agreement with experimental and available data. Unsteady
simulations are performed for DES calculations by using duel time
stepping method or implicit time stepping. The simulations are
performed at Mach number 8 and angle of attack from 0o to 10o for
all these cases. The results and resolutions for DES model found
much better than SA turbulence model.
Abstract: Single photon detectors have been fabricated NbN
nano wire. These detectors are fabricated from high quality, ultra
high vacuum sputtered NbN thin films on a sapphire substrate. In this
work a typical schematic of the nanowire Single Photon Detector
structure and then driving and measurement electronic circuit are
shown.
The response of superconducting nanowire single photon detectors
during a photo detection event, is modeled by a special electrical
circuits (two circuit).
Finally, current through the wire is calculated by solving
equations of models.
Abstract: The integration between technology of remote
sensing, information from the data of digital image, and modeling
technology for the simulation of water quality will provide easiness
during the observation on the quality of water changes on the river
surface. For example, Ciliwung River which is contaminated with
non-point source pollutant from household wastes, particularly on its
downstream. This fact informed that the quality of water in this river
is getting worse. The land use for settlements and housing ranges
between 62.84% - 81.26% on the downstream of Ciliwung River,
give a significant picture in seeing factors that affected the water
quality of Ciliwung River.
Abstract: Along with the progress of our information society,
various risks are becoming increasingly common, causing multiple social problems. For this reason, risk communications for
establishing consensus among stakeholders who have different
priorities have become important. However, it is not always easy for the decision makers to agree on measures to reduce risks based on
opposing concepts, such as security, privacy and cost. Therefore, we previously developed and proposed the “Multiple Risk Communicator" (MRC) with the following functions: (1) modeling
the support role of the risk specialist, (2) an optimization engine, and (3) displaying the computed results. In this paper, MRC program
version 1.0 is applied to the personal information leakage problem. The application process and validation of the results are discussed.
Abstract: Most of the Question Answering systems
composed of three main modules: question processing,
document processing and answer processing. Question
processing module plays an important role in QA systems. If
this module doesn't work properly, it will make problems for
other sections. Moreover answer processing module is an
emerging topic in Question Answering, where these systems
are often required to rank and validate candidate answers.
These techniques aiming at finding short and precise answers
are often based on the semantic classification.
This paper discussed about a new model for question
answering which improved two main modules, question
processing and answer processing.
There are two important components which are the bases
of the question processing. First component is question
classification that specifies types of question and answer.
Second one is reformulation which converts the user's
question into an understandable question by QA system in a
specific domain. Answer processing module, consists of
candidate answer filtering, candidate answer ordering
components and also it has a validation section for interacting
with user. This module makes it more suitable to find exact
answer. In this paper we have described question and answer
processing modules with modeling, implementing and
evaluating the system. System implemented in two versions.
Results show that 'Version No.1' gave correct answer to 70%
of questions (30 correct answers to 50 asked questions) and
'version No.2' gave correct answers to 94% of questions (47
correct answers to 50 asked questions).
Abstract: the data of Taiwanese 8th grader in the 4th cycle of
Trends in International Mathematics and Science Study (TIMSS) are
analyzed to examine the influence of the science teachers- preference
in experimental teaching on the relationships between the affective
variables ( the perceived usefulness of science, ease of using science
and science learning interest) and the academic achievement in science.
After dealing with the missing data, 3711 students and 145 science
teacher-s data were analyzed through a Hierarchical Linear Modeling
technique. The major objective of this study was to determine the role
of the experimental teaching moderates the relationship between
perceived usefulness and achievement.
Abstract: We compare three categorical data clustering
algorithms with respect to the problem of classifying cultural data
related to the aesthetic judgment of comics artists. Such a
classification is very important in Comics Art theory since the
determination of any classes of similarities in such kind of data will
provide to art-historians very fruitful information of Comics Art-s
evolution. To establish this, we use a categorical data set and we
study it by employing three categorical data clustering algorithms.
The performances of these algorithms are compared each other,
while interpretations of the clustering results are also given.
Abstract: Accurate modeling of high speed RLC interconnects
has become a necessity to address signal integrity issues in current
VLSI design. To accurately model a dispersive system of interconnects
at higher frequencies; a full-wave analysis is required.
However, conventional circuit simulation of interconnects with full
wave models is extremely CPU expensive. We present an algorithm
for reducing large VLSI circuits to much smaller ones with similar
input-output behavior. A key feature of our method, called Frequency
Shift Technique, is that it is capable of reducing linear time-varying
systems. This enables it to capture frequency-translation and sampling
behavior, important in communication subsystems such as mixers,
RF components and switched-capacitor filters. Reduction is obtained
by projecting the original system described by linear differential
equations into a lower dimension. Experiments have been carried out
using Cadence Design Simulator cwhich indicates that the proposed
technique achieves more % reduction with less CPU time than the
other model order reduction techniques existing in literature. We
also present applications to RF circuit subsystems, obtaining size
reductions and evaluation speedups of orders of magnitude with
insignificant loss of accuracy.
Abstract: A three-dimensional and pulsatile blood flow in the left ventricle of heart model has been studied numerically. The geometry was derived from a simple approximation of the left ventricle model and the numerical simulations were obtained using a formulation of the Navier-Stokes equations. In this study, simulation was used to investigate the pattern of flow velocity in 3D model of heart with consider the left ventricle based on critical parameter of blood under steady condition. Our results demonstrate that flow velocity focused from mitral valve channel and continuous linearly to left ventricle wall but this skewness progresses into outside wall in atrium through aortic valve with random distribution that is irregular due to force subtract from ventricle wall during cardiac cycle. The findings are the prediction of the behavior of the blood flow velocity pattern in steady flow condition which can assist the medical practitioners in their decision on the patients- treatments.
Abstract: The elution process for the removal of Co and Cu from clinoptilolite as an ion-exchanger was investigated using three parameters: bed volume, pH and contact time. The present paper study has shown quantitatively that acid concentration has a significant effect on the elution process. The favorable eluant concentration was found to be 2 M HCl and 2 M H2SO4, respectively. The multi-component equilibrium relationship in the process can be very complex, and perhaps ill-defined. In such circumstances, it is preferable to use a non-parametric technique such as Neural Network to represent such an equilibrium relationship.
Abstract: Occurrence of a multiple-points fault in machine operations could result in exhibiting complex fault signatures, which could result in lowering fault diagnosis accuracy. In this study, a multiple-points defect model (MPDM) is proposed which can simulate fault signature-s dynamics for n-points bearing faults. Furthermore, this study identifies that in case of multiple-points fault in the rotary machine, the location of the dominant component of defect frequency shifts depending upon the relative location of the fault points which could mislead the fault diagnostic model to inaccurate detections. Analytical and experimental results are presented to characterize and validate the variation in the dominant component of defect frequency. Based on envelop detection analysis, a modification is recommended in the existing fault diagnostic models to consider the multiples of defect frequency rather than only considering the frequency spectrum at the defect frequency in order to incorporate the impact of multiple points fault.
Abstract: Automatic reusability appraisal is helpful in
evaluating the quality of developed or developing reusable software
components and in identification of reusable components from
existing legacy systems; that can save cost of developing the
software from scratch. But the issue of how to identify reusable
components from existing systems has remained relatively
unexplored. In this research work, structural attributes of software
components are explored using software metrics and quality of the
software is inferred by different Neural Network based approaches,
taking the metric values as input. The calculated reusability value
enables to identify a good quality code automatically. It is found that
the reusability value determined is close to the manual analysis used
to be performed by the programmers or repository managers. So, the
developed system can be used to enhance the productivity and
quality of software development.
Abstract: This paper presents an analysis result of relationship
between business and information technology (IT) in business process
reengineering (BPR). 258 Japanese firm-level data collected have been
analyzed using structural equation modeling. This analysis was aimed
to illuminating success factors of achieve effective BPR. Analysis was
focused on management factors (including organizational factors) and
implementing management method (e.g. balanced score card, internal
control, etc.).These results would contribute for achieving effective
BPR by showing effective tasks and environment to be focused.
Abstract: This paper features the modeling and design of a
Robust Decentralized Fast Output Sampling (RDFOS) Feedback
control technique for the active vibration control of a smart flexible
multimodel Euler-Bernoulli cantilever beams for a multivariable
(MIMO) case by retaining the first 6 vibratory modes. The beam
structure is modeled in state space form using the concept of
piezoelectric theory, the Euler-Bernoulli beam theory and the Finite
Element Method (FEM) technique by dividing the beam into 4 finite
elements and placing the piezoelectric sensor / actuator at two finite
element locations (positions 2 and 4) as collocated pairs, i.e., as
surface mounted sensor / actuator, thus giving rise to a multivariable
model of the smart structure plant with two inputs and two outputs.
Five such multivariable models are obtained by varying the
dimensions (aspect ratios) of the aluminium beam. Using model
order reduction technique, the reduced order model of the higher
order system is obtained based on dominant Eigen value retention
and the Davison technique. RDFOS feedback controllers are
designed for the above 5 multivariable-multimodel plant. The closed
loop responses with the RDFOS feedback gain and the magnitudes of
the control input are obtained and the performance of the proposed
multimodel smart structure system is evaluated for vibration control.
Abstract: For a given specific problem an efficient algorithm has been the matter of study. However, an alternative approach orthogonal to this approach comes out, which is called a reduction. In general for a given specific problem this reduction approach studies how to convert an original problem into subproblems. This paper proposes a formal modeling language to support this reduction approach in order to make a solver quickly. We show three examples from the wide area of learning problems. The benefit is a fast prototyping of algorithms for a given new problem. It is noted that our formal modeling language is not intend for providing an efficient notation for data mining application, but for facilitating a designer who develops solvers in machine learning.
Abstract: The purpose of this study is to investiagte the use of
the ecommerce website in Indonesia as a developing country. The
ecommerce website has been identified having the significant impact
on business activities in particular solving the geographical problem
for islanded countries likes Indonesia. Again, website is identified as
a crucial marketing tool. This study presents the effect of quality and
features on the use and user satisfaction employing ecommerce
websites. Survey method for 115 undergraduate students of
Management Department in Andalas University who are attending
Management Information Systems (SIM) class have been
undertaken. The data obtained is analyzed using Structural Equation
Modeling (SEM) using SmartPLS program. This result found that
quality of system and information, feature as well satisfaction
influencing the use ecommerce website in Indonesia contexts.
Abstract: Microstrip lines, widely used for good reason, are
broadband in frequency and provide circuits that are compact and
light in weight. They are generally economical to produce since they
are readily adaptable to hybrid and monolithic integrated circuit (IC)
fabrication technologies at RF and microwave frequencies. Although,
the existing EM simulation models used for the synthesis and
analysis of microstrip lines are reasonably accurate, they are
computationally intensive and time consuming. Neural networks
recently gained attention as fast and flexible vehicles to microwave
modeling, simulation and optimization. After learning and
abstracting from microwave data, through a process called training,
neural network models are used during microwave design to provide
instant answers to the task learned.This paper presents simple and
accurate ANN models for the synthesis and analysis of Microstrip
lines to more accurately compute the characteristic parameters and
the physical dimensions respectively for the required design
specifications.
Abstract: One of the essential sectors of Myanmar economy is
agriculture which is sensitive to climate variation. The most
important climatic element which impacts on agriculture sector is
rainfall. Thus rainfall prediction becomes an important issue in
agriculture country. Multi variables polynomial regression (MPR)
provides an effective way to describe complex nonlinear input output
relationships so that an outcome variable can be predicted from the
other or others. In this paper, the modeling of monthly rainfall
prediction over Myanmar is described in detail by applying the
polynomial regression equation. The proposed model results are
compared to the results produced by multiple linear regression model
(MLR). Experiments indicate that the prediction model based on
MPR has higher accuracy than using MLR.