Abstract: With the rapid expansion of city scale and the
excessive concentration of population, achieving relative equality of
extracurricular education resources and improving spatial service
performance of relevant facilities become necessary arduous tasks. In
urban space, extracurricular education facilities should offer better
service to its targeted area and promote the equality and efficiency of
education, which is accomplished by the allocation of facilities. Based
on questionnaire and survey for local students in Hangzhou City in
2009, this study classifies extracurricular education facilities in
meg-city and defines the equalization of these facilities. Then it is
suggested to establish extracurricular education facilities system
according to the development level of city and demands of local
students, and to introduce a spatial analysis method into urban
planning through the aspects of spatial distribution, travel cost and
spatial service scope. Finally, the practice of nine sub-districts of
Hangzhou is studied.
Abstract: In the present research, steam cracking of two types of
feedstocks i.e., naphtha and ethane is simulated for Pyrocrack1-1 and
2/2 coil configurations considering two key parameters of coil outlet
temperature (COT) and coil capacity using a radical based kinetic
model. The computer model is confirmed using the industrial data
obtained from Amirkabir Petrochemical Complex. The results are in
good agreement with performance data for naphtha cracking in a
wide range of severity (0.4-0.7), and for ethane cracking on various
conversions (50-70). It was found that Pyrocrack2-2 coil type is an
appropriate choice for steam cracking of ethane at reasonable
ethylene yield while resulting in much lower tube wall temperature
while Pyrocrack1-1 coil type is a proper selection for liquid
feedstocks i.e. naphtha. It can be used for cracking of liquid
feedstocks at optimal ethylene yield whereas not exceeding the
allowable maximum tube temperature.
Abstract: The present paper considers the steady free
convection boundary layer flow of a viscoelastics fluid with constant
temperature in the presence of heat generation. The boundary layer
equations are an order higher than those for the Newtonian (viscous)
fluid and the adherence boundary conditions are insufficient to
determine the solution of these equations completely. The governing
boundary layer equations are first transformed into non-dimensional
form by using special dimensionless group. Computations are
performed numerically by using Keller-box method by augmenting
an extra boundary condition at infinity and the results are displayed
graphically to illustrate the influence of viscoelastic K, heat
generation γ , and Prandtl Number, Pr parameters on the velocity
and temperature profiles. The results of the surface shear stress in
terms of the local skin friction and the surface rate of heat transfer in
terms of the local Nusselt number for a selection of the heat
generation parameterγ (=0.0, 0.2, 0.5, 0.8, 1.0) are obtained and
presented in both tabular and graphical formats. Without effect of the
internal heat generation inside the fluid domain for which we take
γ = 0.0, the present numerical results show an excellent agreement
with previous publication.
Abstract: This paper explored the use of Importance- Performance Analysis in assessing the competitiveness of China-s Macao Special Administrative Region as a city for international conventions. Determinants of destination choice for convention tourists are grouped under three factors, namely the convention factor, the city factor and the tourism factor. Attributes of these three factors were studied through a survey with the convention participants and exhibitors of Macao SAR. Results indicate that the city boasts of strong traditional tourist attractions and infrastructure, but is deficient in specialized convention experts and promotion mechanisms. A reflection on the findings suggests that an urban city such as the Macao SAR can co-develop its the convention and the traditional tourism for a synergistic effect. With proper planning and co-ordination, both areas of the city-s tourism industry will grow as they feed off each other.
Abstract: Many measures have been proposed for machine
translation evaluation (MTE) while little research has been done on
the performance of MTE methods. This paper is an effort for MTE
performance analysis. A general frame is proposed for the description
of the MTE measure and the test suite, including whether the
automatic measure is consistent with human evaluation, whether
different results from various measures or test suites are consistent,
whether the content of the test suite is suitable for performance
evaluation, the degree of difficulty of the test suite and its influence
on the MTE, the relationship of MTE result significance and the size
of the test suite, etc. For a better clarification of the frame, several
experiment results are analyzed relating human evaluation, BLEU
evaluation, and typological MTE. A visualization method is
introduced for better presentation of the results. The study aims for
aid in construction of test suite and method selection in MTE
practice.
Abstract: In this study, an optimization of supersonic air-to-air ejector is carried out by a recently developed single-objective genetic algorithm based on adaption of sequence of individuals. Adaptation of sequence is based on Shape-based distance of individuals and embedded micro-genetic algorithm. The optimal sequence found defines the succession of CFD-aimed objective calculation within each generation of regular micro-genetic algorithm. A spring-based deformation mutates the computational grid starting the initial individualvia adapted population in the optimized sequence. Selection of a generation initial individual is knowledge-based. A direct comparison of the newly defined and standard micro-genetic algorithm is carried out for supersonic air-to-air ejector. The only objective is to minimize the loose of total stagnation pressure in the ejector. The result is that sequence-adopted micro-genetic algorithm can provide comparative results to standard algorithm but in significantly lower number of overall CFD iteration steps.
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: In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.
Abstract: The research on two-wheeled inverted pendulum (TWIP) mobile robots or commonly known as balancing robots have gained momentum over the last decade in a number of robotic laboratories around the world. This paper describes the hardware design of such a robot. The objective of the design is to develop a TWIP mobile robot as well as MATLAB interfacing configuration to be used as flexible platform comprises of embedded unstable linear plant intended for research and teaching purposes. Issues such as selection of actuators and sensors, signal processing units, MATLAB Real Time Workshop coding, modeling and control scheme will be addressed and discussed. The system is then tested using a wellknown state feedback controller to verify its functionality.
Abstract: The present paper discusses the selection of process
parameters for obtaining optimal nanocrystallites size in the CuOZrO2
catalyst. There are some parameters changing the inorganic
structure which have an influence on the role of hydrolysis and
condensation reaction. A statistical design test method is
implemented in order to optimize the experimental conditions of
CuO-ZrO2 nanoparticles preparation. This method is applied for the
experiments and L16 orthogonal array standard. The crystallites size
is considered as an index. This index will be used for the analysis in
the condition where the parameters vary. The effect of pH, H2O/
precursor molar ratio (R), time and temperature of calcination,
chelating agent and alcohol volume are particularity investigated
among all other parameters. In accordance with the results of
Taguchi, it is found that temperature has the greatest impact on the
particle size. The pH and H2O/ precursor molar ratio have low
influences as compared with temperature. The alcohol volume as
well as the time has almost no effect as compared with all other
parameters. Temperature also has an influence on the morphology
and amorphous structure of zirconia. The optimal conditions are
determined by using Taguchi method. The nanocatalyst is studied by
DTA-TG, XRD, EDS, SEM and TEM. The results of this research
indicate that it is possible to vary the structure, morphology and
properties of the sol-gel by controlling the above-mentioned
parameters.
Abstract: Content-based music retrieval generally involves analyzing, searching and retrieving music based on low or high level features of a song which normally used to represent artists, songs or music genre. Identifying them would normally involve feature extraction and classification tasks. Theoretically the greater features analyzed, the better the classification accuracy can be achieved but with longer execution time. Technique to select significant features is important as it will reduce dimensions of feature used in classification and contributes to the accuracy. Artificial Immune System (AIS) approach will be investigated and applied in the classification task. Bio-inspired audio content-based retrieval framework (B-ACRF) is proposed at the end of this paper where it embraces issues that need further consideration in music retrieval performances.
Abstract: Partitioning is a critical area of VLSI CAD. In order to build complex digital logic circuits its often essential to sub-divide multi -million transistor design into manageable Pieces. This paper looks at the various partitioning techniques aspects of VLSI CAD, targeted at various applications. We proposed an evolutionary time-series model and a statistical glitch prediction system using a neural network with selection of global feature by making use of clustering method model, for partitioning a circuit. For evolutionary time-series model, we made use of genetic, memetic & neuro-memetic techniques. Our work focused in use of clustering methods - K-means & EM methodology. A comparative study is provided for all techniques to solve the problem of circuit partitioning pertaining to VLSI design. The performance of all approaches is compared using benchmark data provided by MCNC standard cell placement benchmark net lists. Analysis of the investigational results proved that the Neuro-memetic model achieves greater performance then other model in recognizing sub-circuits with minimum amount of interconnections between them.
Abstract: This paper presents a method of model selection and
identification of Hammerstein systems by hybridization of the genetic
algorithm (GA) and particle swarm optimization (PSO). An unknown
nonlinear static part to be estimated is approximately represented
by an automatic choosing function (ACF) model. The weighting
parameters of the ACF and the system parameters of the linear
dynamic part are estimated by the linear least-squares method. On
the other hand, the adjusting parameters of the ACF model structure
are properly selected by the hybrid algorithm of the GA and PSO,
where the Akaike information criterion is utilized as the evaluation
value function. Simulation results are shown to demonstrate the
effectiveness of the proposed hybrid algorithm.
Abstract: The network traffic data provided for the design of
intrusion detection always are large with ineffective information and
enclose limited and ambiguous information about users- activities.
We study the problems and propose a two phases approach in our
intrusion detection design. In the first phase, we develop a
correlation-based feature selection algorithm to remove the worthless
information from the original high dimensional database. Next, we
design an intrusion detection method to solve the problems of
uncertainty caused by limited and ambiguous information. In the
experiments, we choose six UCI databases and DARPA KDD99
intrusion detection data set as our evaluation tools. Empirical studies
indicate that our feature selection algorithm is capable of reducing the
size of data set. Our intrusion detection method achieves a better
performance than those of participating intrusion detectors.
Abstract: Wavelet transform has been extensively used in
machine fault diagnosis and prognosis owing to its strength to deal
with non-stationary signals. The existing Wavelet transform based
schemes for fault diagnosis employ wavelet decomposition of the
entire vibration frequency which not only involve huge
computational overhead in extracting the features but also increases
the dimensionality of the feature vector. This increase in the
dimensionality has the tendency to 'over-fit' the training data and
could mislead the fault diagnostic model. In this paper a novel
technique, envelope wavelet packet transform (EWPT) is proposed in
which features are extracted based on wavelet packet transform of the
filtered envelope signal rather than the overall vibration signal. It not
only reduces the computational overhead in terms of reduced number
of wavelet decomposition levels and features but also improves the
fault detection accuracy. Analytical expressions are provided for the
optimal frequency resolution and decomposition level selection in
EWPT. Experimental results with both actual and simulated machine
fault data demonstrate significant gain in fault detection ability by
EWPT at reduced complexity compared to existing techniques.
Abstract: Interactive push VOD system is a new kind of system
that incorporates push technology and interactive technique. It can
push movies to users at high speeds at off-peak hours for optimal
network usage so as to save bandwidth. This paper presents effective
software-based solution for processing mass downstream data at
terminals of interactive push VOD system, where the service can
download movie according to a viewer-s selection. The downstream
data is divided into two catalogs: (1) the carousel data delivered
according to DSM-CC protocol; (2) IP data delivered according to
Euro-DOCSIS protocol. In order to accelerate download speed and
reduce data loss rate at terminals, this software strategy introduces
caching, multi-thread and resuming mechanisms. The experiments
demonstrate advantages of the software-based solution.
Abstract: The paper presents a detailed calculation of characteristic of five different topology permanent magnet machines for high performance traction including hybrid -electric vehicles using finite element analysis (FEA) method. These machines include V-shape single layer interior PM, W-shape single-layer interior PM, Segment interior PM and surface PM on the rotor and with distributed winding on the stator. The performance characteristics which include the back-emf voltage and its harmonic, magnet mass, iron loss and ripple torque are compared and analyzed. One of a 7.5kW IPM prototype was tested and verified finite-element analysis results. The aim of the paper is given some guidance and reference for machine designer which are interested in IPM machine selection for high performance traction application.
Abstract: A genetic algorithm (GA) based feature subset
selection algorithm is proposed in which the correlation structure of
the features is exploited. The subset of features is validated according
to the classification performance. Features derived from the
continuous wavelet transform are potentially strongly correlated.
GA-s that do not take the correlation structure of features into
account are inefficient. The proposed algorithm forms clusters of
correlated features and searches for a good candidate set of clusters.
Secondly a search within the clusters is performed. Different
simulations of the algorithm on a real-case data set with strong
correlations between features show the increased classification
performance. Comparison is performed with a standard GA without
use of the correlation structure.
Abstract: This paper gives a novel method for improving
classification performance for cancer classification with very few
microarray Gene expression data. The method employs classification
with individual gene ranking and gene subset ranking. For selection
and classification, the proposed method uses the same classifier. The
method is applied to three publicly available cancer gene expression
datasets from Lymphoma, Liver and Leukaemia datasets. Three
different classifiers namely Support vector machines-one against all
(SVM-OAA), K nearest neighbour (KNN) and Linear Discriminant
analysis (LDA) were tested and the results indicate the improvement
in performance of SVM-OAA classifier with satisfactory results on
all the three datasets when compared with the other two classifiers.
Abstract: In order to reduce cost, increase quality, and for
timely supplying production systems has considerably taken the
advantages of supply chain management and these advantages are
also competitive. Selection of appropriate supplier has an important
role in improvement and efficiency of systems.
The models of supplier selection which have already been used by
researchers have considered selection one or more suppliers from
potential suppliers but in this paper selecting one supplier as partner
from one supplier that have minimum one period supplying to buyer
is considered.
This paper presents a conceptual model for partner selection and
application of Degree of Adoptive (DOA) model for final selection.
The attributes weight in this model is prepared through AHP
model. After making the descriptive model, determining the
attributes and measuring the parameters of the adaptive is examined
in an auto industry of Iran(Zagross Khodro co.) and results are
presented.