Abstract: The peng-Robinson (PR), a cubic equation of state (EoS), is extended to polymers by using a single set of energy (A1, A2, A3) and co-volume (b) parameters per polymer fitted to experimental volume data. Excellent results for the volumetric behavior of the 11 polymer up to 2000 bar pressure are obtained. The EoS is applied to the correlation and prediction of Henry constants in polymer solutions comprising three polymer and many nonpolar and polar solvents, including supercritical gases. The correlation achieved with two adjustable parameter is satisfactory compared with the experimental data. As a result, the present work provides a simple and useful model for the prediction of Henry's constant for polymer containing systems including those containing polar, nonpolar and supercritical fluids.
Abstract: With the increasing complexity of engineering
problems, the traditional, single-objective and deterministic
optimization method can not meet people-s requirements. A
multi-objective fuzzy optimization model of resource input is built for
M chlor-alkali chemical eco-industrial park in this paper. First, the
model is changed into the form that can be solved by genetic algorithm
using fuzzy theory. And then, a fitness function is constructed for
genetic algorithm. Finally, a numerical example is presented to show
that the method compared with traditional single-objective
optimization method is more practical and efficient.
Abstract: Non-Destructive evaluation of in-service power
transformer condition is necessary for avoiding catastrophic failures.
Dissolved Gas Analysis (DGA) is one of the important methods.
Traditional, statistical and intelligent DGA approaches have been
adopted for accurate classification of incipient fault sources.
Unfortunately, there are not often enough faulty patterns required for
sufficient training of intelligent systems. By bootstrapping the
shortcoming is expected to be alleviated and algorithms with better
classification success rates to be obtained. In this paper the
performance of an artificial neural network, K-Nearest Neighbour
and support vector machine methods using bootstrapped data are
detailed and shown that while the success rate of the ANN algorithms
improves remarkably, the outcome of the others do not benefit so
much from the provided enlarged data space. For assessment, two
databases are employed: IEC TC10 and a dataset collected from
reported data in papers. High average test success rate well exhibits
the remarkable outcome.
Abstract: With the extensive inclusion of document, especially
text, in the business systems, data mining does not cover the full
scope of Business Intelligence. Data mining cannot deliver its impact
on extracting useful details from the large collection of unstructured
and semi-structured written materials based on natural languages.
The most pressing issue is to draw the potential business intelligence
from text. In order to gain competitive advantages for the business, it
is necessary to develop the new powerful tool, text mining, to expand
the scope of business intelligence.
In this paper, we will work out the strong points of text mining in
extracting business intelligence from huge amount of textual
information sources within business systems. We will apply text
mining to each stage of Business Intelligence systems to prove that
text mining is the powerful tool to expand the scope of BI. After
reviewing basic definitions and some related technologies, we will
discuss the relationship and the benefits of these to text mining. Some
examples and applications of text mining will also be given. The
motivation behind is to develop new approach to effective and
efficient textual information analysis. Thus we can expand the scope
of Business Intelligence using the powerful tool, text mining.
Abstract: Owing the fact that optimization of business process
is a crucial requirement to navigate, survive and even thrive in
today-s volatile business environment, this paper presents a
framework for selecting a best-fit optimization package for solving
complex business problems. Complexity level of the problem and/or
using incorrect optimization software can lead to biased solutions of
the optimization problem. Accordingly, the proposed framework
identifies a number of relevant factors (e.g. decision variables,
objective functions, and modeling approach) to be considered during
the evaluation and selection process. Application domain, problem
specifications, and available accredited optimization approaches are
also to be regarded. A recommendation of one or two optimization
software is the output of the framework which is believed to provide
the best results of the underlying problem. In addition to a set of
guidelines and recommendations on how managers can conduct an
effective optimization exercise is discussed.
Abstract: This paper constructs a four factors theoretical model of Chinese small and medium enterprises based on the “cartoon characters- reputation - enterprise marketing and management capabilities – protection of the cartoon image - institutional environment" by literature research, case studies and investigation. The empirical study show that the greatest impact on current merchandising rights income is the institutional environment friendliness, followed by marketing and management capabilities, input of character image protection and Cartoon characters- reputation through the real-time grey relational analysis, and the greatest impact on post-merchandising rights profit is Cartoon characters reputation, followed by the institutional environment friendliness, then marketing and management ability and input of character image protection through the time-delay grey relational analysis.
Abstract: In recent years various types of electric vehicles
has gained again increasing attention as an environmentally
benign technology in transport. Especially for urban areas with
high local pollution this Zero-emission technology (at the point
of use) is considered to provide proper solutions. Yet, the bad
economics and the limited driving ranges are still major barriers
for a broader market penetration of battery electric vehicles
(BEV) and of fuel cell vehicles (FCV). The major result of our
analyses is that the most important precondition for a further
dissemination of BEV in urban areas are emission-free zones.
This is an instrument which allows the promotion of BEV
without providing excessive subsidies. In addition, it is
important to note that the full benefits of EV can only be
harvested if the electricity used is produced from renewable
energy sources. That is to say, it has to be ensured that the use of
BEV in urban areas is clearly linked to a green electricity
purchase model. And moreover, the introduction of a CO2-
emission-based tax system would support this requirement.
Abstract: Thermo-chemical treatment (TCT) such as pyrolysis
is getting recognized as a valid route for (i) materials and valuable
products and petrochemicals recovery; (ii) waste recycling; and (iii)
elemental characterization. Pyrolysis is also receiving renewed
attention for its operational, economical and environmental
advantages. In this study, samples of polyethylene terephthalate
(PET) and polystyrene (PS) were pyrolysed in a microthermobalance
reactor (using a thermogravimetric-TGA setup). Both
polymers were prepared and conditioned prior to experimentation.
The main objective was to determine the kinetic parameters of the
depolymerization reactions that occur within the thermal degradation
process. Overall kinetic rate constants (ko) and activation energies
(Eo) were determined using the general kinetics theory (GKT)
method previously used by a number of authors. Fitted correlations
were found and validated using the GKT, errors were within ± 5%.
This study represents a fundamental step to pave the way towards the
development of scaling relationship for the investigation of larger
scale reactors relevant to industry.
Abstract: An unsupervised classification algorithm is derived
by modeling observed data as a mixture of several mutually
exclusive classes that are each described by linear combinations of
independent non-Gaussian densities. The algorithm estimates the
data density in each class by using parametric nonlinear functions
that fit to the non-Gaussian structure of the data. This improves
classification accuracy compared with standard Gaussian mixture
models. When applied to textures, the algorithm can learn basis
functions for images that capture the statistically significant structure
intrinsic in the images. We apply this technique to the problem of
unsupervised texture classification and segmentation.
Abstract: Fuzzy logic system (FLS) is used in this study to
predict the tractive performance in terms of traction force, and
motion resistance for an intelligent air cushion track vehicle while it
operates in the swamp peat. The system is effective to control the
intelligent air –cushion system with measuring the vehicle traction
force (TF), motion resistance (MR), cushion clearance height (CH)
and cushion pressure (CP). Ultrasonic displacement sensor, pull-in
solenoid electromagnetic switch, pressure control sensor, micro
controller, and battery pH sensor are incorporated with the Fuzzy
logic system to investigate experimentally the TF, MR, CH, and CP.
In this study, a comparison for tractive performance of an intelligent
air cushion track vehicle has been performed with the results obtained
from the predicted values of FLS and experimental actual values. The
mean relative error of actual and predicted values from the FLS
model on traction force, and total motion resistance are found as 5.58
%, and 6.78 % respectively. For all parameters, the relative error of
predicted values are found to be less than the acceptable limits. The
goodness of fit of the prediction values from the FLS model on TF,
and MR are found as 0.90, and 0.98 respectively.
Abstract: Kernel function, which allows the formulation of nonlinear variants of any algorithm that can be cast in terms of dot products, makes the Support Vector Machines (SVM) have been successfully applied in many fields, e.g. classification and regression. The importance of kernel has motivated many studies on its composition. It-s well-known that reproducing kernel (R.K) is a useful kernel function which possesses many properties, e.g. positive definiteness, reproducing property and composing complex R.K by simple operation. There are two popular ways to compute the R.K with explicit form. One is to construct and solve a specific differential equation with boundary value whose handicap is incapable of obtaining a unified form of R.K. The other is using a piecewise integral of the Green function associated with a differential operator L. The latter benefits the computation of a R.K with a unified explicit form and theoretical analysis, whereas there are relatively later studies and fewer practical computations. In this paper, a new algorithm for computing a R.K is presented. It can obtain the unified explicit form of R.K in general reproducing kernel Hilbert space. It avoids constructing and solving the complex differential equations manually and benefits an automatic, flexible and rigorous computation for more general RKHS. In order to validate that the R.K computed by the algorithm can be used in SVM well, some illustrative examples and a comparison between R.K and Gaussian kernel (RBF) in support vector regression are presented. The result shows that the performance of R.K is close or slightly superior to that of RBF.
Abstract: Recent quasi-experimental evaluation of the Canadian Active Labour Market Policies (ALMP) by Human Resources and Skills Development Canada (HRSDC) has provided an opportunity to examine alternative methods to estimating the incremental effects of Employment Benefits and Support Measures (EBSMs) on program participants. The focus of this paper is to assess the efficiency and robustness of inverse probability weighting (IPW) relative to kernel matching (KM) in the estimation of program effects. To accomplish this objective, the authors compare pairs of 1,080 estimates, along with their associated standard errors, to assess which type of estimate is generally more efficient and robust. In the interest of practicality, the authorsalso document the computationaltime it took to produce the IPW and KM estimates, respectively.
Abstract: Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.
Abstract: Computers are increasingly being used as educational
tools in elementary/primary schools worldwide. A specific
application of such computer use, is that of multimedia games, where
the aim is to combine pedagogy and entertainment. This study
reports on a case-study whereby an educational multimedia game has
been developed for use by elementary school children. The stages of
the application-s design, implementation and evaluation are
presented. Strengths of the game are identified and discussed, and its
weaknesses are identified, allowing for suggestions for future redesigns.
The results show that the use of games can engage children
in the learning process for longer periods of time with the added
benefit of the entertainment factor.
Abstract: This paper argues that a product development exercise
involves in addition to the conventional stages, several decisions
regarding other aspects. These aspects should be addressed
simultaneously in order to develop a product that responds to the
customer needs and that helps realize objectives of the stakeholders
in terms of profitability, market share and the like. We present a
framework that encompasses these different development
dimensions. The framework shows that a product development
methodology such as the Quality Function Deployment (QFD) is the
basic tool which allows definition of the target specifications of a
new product. Creativity is the first dimension that enables the
development exercise to live and end successfully. A number of
group processes need to be followed by the development team in
order to ensure enough creativity and innovation. Secondly,
packaging is considered to be an important extension of the product.
Branding strategies, quality and standardization requirements,
identification technologies, design technologies, production
technologies and costing and pricing are also integral parts to the
development exercise. These dimensions constitute the proposed
framework. The paper also presents a mathematical model used to
calculate the design targets based on the target costing principle. The
framework is used to study a case of a new product development in
the telecommunications services sector.
Abstract: Since DVB-RCS has been successively implemented, the mobile communication on the multi-beam satellite communication is attractive attention. And the DVB-RCS standard sets up to support mobility of a RCST. In the case of the spot-beam satellite system, the received signal strength does not differ largely between the center and the boundary of the beam. Thus, the RSS based handoff detection algorithm is not benefit to the satellite system as a terrestrial system. Therefore we propose an Adaptive handoff detection algorithm based on RCST mobility information. Our handoff detection algorithm not only can be used as centralized handoff detection algorithm but also removes uncertainties of handoff due to the variation of RSS. Performances were compared with RSS based handoff algorithm. Simulation results show that the proposed handoff detection algorithm not only achieved better handoff and link degradation rate, but also achieved better forward link spectral efficiency.
Abstract: The purpose of this paper is to develop a typology
based on market orientation (MO) and innovation orientation (IO),
and to illustrate to what extent housing companies in Sweden fit
within this framework. A qualitative study on 11 public housing
companies in the central part of Sweden has been conducted by the
help of open and semi-structured questions for data collection. Four
public housing company types- i.e. reactive prospector, proactive
prospector, reactive defender and proactive defender have been
identified by the combination of MO-IO dimensions. Future research
can include other dimensions like entrepreneurship and network to
observe how it particularly affects MO. An empirical study can
compare public and private housing companies on the basis of MO
and IO dimensions. One major contribution of the paper is the
proposition of typology which can be used to describe public housing
companies and deciding their future course of actions.
Abstract: This paper deals with under actuator dynamic systems such as spring-mass-damper system when the number of control variable is less than the number of state variable. In order to apply optimal control, the controllability must be checked. There are many objective functions to be selected as the goal of the optimal control such as minimum energy, maximum energy and minimum jerk. As the objective function is the first priority, if one like to have the second goal to be applied; however, it could not fit in the objective function format and also avoiding the vector cost for the objective, this paper will illustrate the problem of under actuator dynamic systems with the easiest to deal with comparing between minimum energy and minimum jerk.
Abstract: This research focus on developing a new segmentation method for improving forecasting model which is call trend based segmentation method (TBSM). Generally, the piece-wise linear representation (PLR) can finds some of pair of trading points is well for time series data, but in the complicated stock environment it is not well for stock forecasting because of the stock has more trends of trading. If we consider the trends of trading in stock price for the trading signal which it will improve the precision of forecasting model. Therefore, a TBSM with SVR model used to detect the trading points for various stocks of Taiwanese and America under different trend tendencies. The experimental results show our trading system is more profitable and can be implemented in real time of stock market
Abstract: The objectives of this research are to search the
management pattern of Bang Khonthi lodging entrepreneurs for
sufficient economy ways, to know the threat that affects this sector
and design fit arrangement model to sustain their business with
Samut Songkram style. What will happen if they do not use this
approach? Will they have a financial crisis? The data and information
are collected by informal discussions with 8 managers and 400
questionnaires. A mixed methods of both qualitative research and
quantitative research are used. Bent Flyvbjerg-s phronesis is utilized
for this analysis. Our research will prove that sufficient economy can
help small business firms to solve their problems. We think that the
results of our research will be a financial model to solve many
problems of the entrepreneurs and this way will can be a model for
other provinces of Thailand.