Abstract: Data Warehousing tools have become very popular and currently many of them have moved to Web-based user interfaces to make it easier to access and use the tools. The next step is to enable these tools to be used within a portal framework. The portal framework consists of pages having several small windows that contain individual data warehouse query results. There are several issues that need to be considered when designing the architecture for a portal enabled data warehouse query tool. Some issues need special techniques that can overcome the limitations that are imposed by the nature of data warehouse queries. Issues such as single sign-on, query result caching and sharing, customization, scheduling and authorization need to be considered. This paper discusses such issues and suggests an architecture to support data warehouse queries within Web portal frameworks.
Abstract: In this paper, based on flume experimental data, the velocity distribution in open channel flows is re-investigated. From the analysis, it is proposed that the wake layer in outer region may be divided into two regions, the relatively weak outer region and the relatively strong outer region. Combining the log law for inner region and the parabolic law for relatively strong outer region, an explicit equation for mean velocity distribution of steady and uniform turbulent flow through straight open channels is proposed and verified with the experimental data. It is found that the sediment concentration has significant effect on velocity distribution in the relatively weak outer region.
Abstract: Hysteresis phenomenon has been observed in the
operations of both horizontal-axis and vertical-axis wind turbines
(HAWTs and VAWTs). In this study, wind tunnel experiments were
applied to investigate the characters of hysteresis phenomena between
the angular speed and the external resistance of electrical loading
during the operation of a Darrieus type VAWT. Data of output voltage,
output current, angular speed of wind turbine under different wind
speeds are measured and analyzed. Results show that the range of
external resistance changes with the wind speed. The range decreases
as the wind speed increases following an exponential decay form.
Experiments also indicate that the maximum output power of wind
turbines is always inside the range where hysteresis happened. These
results provide an important reference to the design of output control
system of wind turbines.
Abstract: The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.
Abstract: In this communication a quantitative modeling
approach is applied to construct model for the exchange of gases
from open sewer channel to the atmosphere. The data for the
exchange of gases of the open sewer channel for the year January
1979 to December 2006 is utilized for the construction of the model.
The study reveals that stream flow of the open sewer channel
exchanges the toxic gases continuously with time varying scale. We
find that the quantitative modeling approach is more parsimonious
model for these exchanges. The usual diagnostic tests are applied for
the model adequacy. This model is beneficial for planner and
managerial bodies for the improvement of implemented policies to
overcome future environmental problems.
Abstract: Dynamic of phytoplankton blooms in the Baltic Sea
has been analyzed applying the numerical ecosystem model 3D
CEMBS. The model consists of the hydrodynamic model (POP,
version 2.1) and the ice model (CICE, version 4.0), which are
imposed by the atmospheric data model (DATM7). The 3D
model has an ecosystem module, activated in 2012 in the operational
mode. The ecosystem model consists of 11 main variables: biomass
of small-size phytoplankton and large-size phytoplankton
and cyanobacteria, zooplankton biomass, dissolved and molecular
detritus, dissolved oxygen concentration, as well as concentrations of
nutrients, including: nitrates, ammonia, phosphates and silicates. The
3D-CEMBS model is an effective tool for solving problems related to
phytoplankton blooms dynamic in the Baltic Sea
Abstract: The aim of this paper is to present the kinematic
analysis and mechanism design of an assistive robotic leg for
hemiplegic and hemiparetic patients. In this work, the priority is to
design and develop the lightweight, effective and single driver
mechanism on the basis of experimental hip and knee angles- data for
walking speed of 1 km/h. A mechanism of cam-follower with three
links is suggested for this purpose. The kinematic analysis is carried
out and analysed using commercialized MATLAB software based on
the prototype-s links sizes and kinematic relationships. In order to
verify the kinematic analysis of the prototype, kinematic analysis data
are compared with the experimental data. A good agreement between
them proves that the anthropomorphic design of the lower extremity
exoskeleton follows the human walking gait.
Abstract: Despite the availability of natural disaster related time series data for last 110 years, there is no forecasting tool available to humanitarian relief organizations to determine forecasts for emergency logistics planning. This study develops a forecasting tool based on identifying probability distributions. The estimates of the parameters are used to calculate natural disaster forecasts. Further, the determination of aggregate forecasts leads to efficient pre-disaster planning. Based on the research findings, the relief agencies can optimize the various resources allocation in emergency logistics planning.
Abstract: In this work, a radial basis function (RBF) neural network is developed for the identification of hyperbolic distributed parameter systems (DPSs). This empirical model is based only on process input-output data and used for the estimation of the controlled variables at specific locations, without the need of online solution of partial differential equations (PDEs). The nonlinear model that is obtained is suitably transformed to a nonlinear state space formulation that also takes into account the model mismatch. A stable robust control law is implemented for the attenuation of external disturbances. The proposed identification and control methodology is applied on a long duct, a common component of thermal systems, for a flow based control of temperature distribution. The closed loop performance is significantly improved in comparison to existing control methodologies.
Abstract: The purpose of this research is to study motivation
factors and also to study factors relation to job performance to
compare motivation factors under the personal factor classification
such as gender, age, income, educational level, marital status, and
working duration; and to study the relationship between Motivation
Factors and Job Performance with job satisfactions. The sample
groups utilized in this research were 400 Suan Sunandha Rajabhat
University employees. This research is a quantitative research using
questionnaires as research instrument. The statistics applied for data
analysis including percentage, mean, and standard deviation. In
addition, the difference analysis was conducted by t value computing,
one-way analysis of variance and Pearson’s correlation coefficient
computing. The findings of the study results were as follows the
findings showed that the aspects of job promotion and salary were at
the moderate levels. Additionally, the findings also showed that the
motivations that affected the revenue branch chiefs’ job performance
were job security, job accomplishment, policy and management, job
promotion, and interpersonal relation.
Abstract: Repeated observation of a given area over time yields
potential for many forms of change detection analysis. These
repeated observations are confounded in terms of radiometric
consistency due to changes in sensor calibration over time,
differences in illumination, observation angles and variation in
atmospheric effects.
This paper demonstrates applicability of an empirical relative
radiometric normalization method to a set of multitemporal cloudy
images acquired by Resourcesat1 LISS III sensor. Objective of this
study is to detect and remove cloud cover and normalize an image
radiometrically. Cloud detection is achieved by using Average
Brightness Threshold (ABT) algorithm. The detected cloud is
removed and replaced with data from another images of the same
area. After cloud removal, the proposed normalization method is
applied to reduce the radiometric influence caused by non surface
factors. This process identifies landscape elements whose reflectance
values are nearly constant over time, i.e. the subset of non-changing
pixels are identified using frequency based correlation technique. The
quality of radiometric normalization is statistically assessed by R2
value and mean square error (MSE) between each pair of analogous
band.
Abstract: This paper proposes a method that discovers sequential patterns corresponding to user-s interests from sequential data. This method expresses the interests as constraint patterns. The constraint patterns can define relationships among attributes of the items composing the data. The method recursively decomposes the constraint patterns into constraint subpatterns. The method evaluates the constraint subpatterns in order to efficiently discover sequential patterns satisfying the constraint patterns. Also, this paper applies the method to the sequential data composed of stock price indexes and verifies its effectiveness through comparing it with a method without using the constraint patterns.
Abstract: The inherent flexibilities of XML in both structure
and semantics makes mining from XML data a complex task with
more challenges compared to traditional association rule mining in
relational databases. In this paper, we propose a new model for the
effective extraction of generalized association rules form a XML
document collection. We directly use frequent subtree mining
techniques in the discovery process and do not ignore the tree
structure of data in the final rules. The frequent subtrees based on the
user provided support are split to complement subtrees to form the
rules. We explain our model within multi-steps from data preparation
to rule generation.
Abstract: This paper presents an automatic feature recognition
method based on center-surround difference detecting and fuzzy logic
that can be applied in ground-penetrating radar (GPR) image
processing. Adopted center-surround difference method, the salient
local image regions are extracted from the GPR images as features of
detected objects. And fuzzy logic strategy is used to match the
detected features and features in template database. This way, the
problem of objects detecting, which is the key problem in GPR image
processing, can be converted into two steps, feature extracting and
matching. The contributions of these skills make the system have the
ability to deal with changes in scale, antenna and noises. The results of
experiments also prove that the system has higher ratio of features
sensing in using GPR to image the subsurface structures.
Abstract: Single nucleotide polymorphisms (SNPs) hold much promise as a basis for disease-gene association. However, research is limited by the cost of genotyping the tremendous number of SNPs. Therefore, it is important to identify a small subset of informative SNPs, the so-called tag SNPs. This subset consists of selected SNPs of the genotypes, and accurately represents the rest of the SNPs. Furthermore, an effective evaluation method is needed to evaluate prediction accuracy of a set of tag SNPs. In this paper, a genetic algorithm (GA) is applied to tag SNP problems, and the K-nearest neighbor (K-NN) serves as a prediction method of tag SNP selection. The experimental data used was taken from the HapMap project; it consists of genotype data rather than haplotype data. The proposed method consistently identified tag SNPs with considerably better prediction accuracy than methods from the literature. At the same time, the number of tag SNPs identified was smaller than the number of tag SNPs in the other methods. The run time of the proposed method was much shorter than the run time of the SVM/STSA method when the same accuracy was reached.
Abstract: The potential of economically cheaper cellulose
containing natural materials like rice husk was assessed for nickel
adsorption from aqueous solutions. The effects of pH, contact time,
sorbent dose, initial metal ion concentration and temperature on the
uptake of nickel were studied in batch process. The removal of nickel
was dependent on the physico-chemical characteristics of the
adsorbent, adsorbate concentration and other studied process
parameters. The sorption data has been correlated with Langmuir,
Freundlich and Dubinin-Radush kevich (D-R) adsorption models. It
was found that Freundlich and Langmuir isotherms fitted well to the
data. Maximum nickel removal was observed at pH 6.0. The
efficiency of rice husk for nickel removal was 51.8% for dilute
solutions at 20 g L-1 adsorbent dose. FTIR, SEM and EDAX were
recorded before and after adsorption to explore the number and
position of the functional groups available for nickel binding on to
the studied adsorbent and changes in surface morphology and
elemental constitution of the adsorbent. Pseudo-second order model
explains the nickel kinetics more effectively. Reusability of the
adsorbent was examined by desorption in which HCl eluted 78.93%
nickel. The results revealed that nickel is considerably adsorbed on
rice husk and it could be and economic method for the removal of
nickel from aqueous solutions.
Abstract: The aim of this study is to discuss the relationship between tourist awareness of environmental issues and their own recreational behaviors in the Taipei Guandu Wetland. A total of 392 questionnaires were gathered for data analysis using descriptive statistics, t-testing, one-way analysis of variance (ANOVA) and least significant difference (LSD) post hoc comparisons. The results showed that most of the visitors there enjoying the beautiful scenery are 21 to 30 years old with a college education. The means and standard deviations indicate that tourists express a positive degree of cognition of environmental issues and recreational behaviors. They suggest that polluting the environment is harmful to the natural ecosystem and that the natural resources of ecotourism are fragile, as well as expressing a high degree of recognition of the need to protect wetlands. Most of respondents are cognizant of the regulations proposed by the Guandu Wetland administration which asks that users exercise self-control and follow recommended guidelines when traveling the wetland. There were significant differences in the degree of cognition related to the variables of age, number of visits and reasons for visiting. We found that most respondents with relatively high levels of education would like to learn more about the wetland and are supportive of its conservation.
Abstract: We address the problem of joint beamforming and multipath channel parameters estimation in Wideband Code Division Multiple Access (WCDMA) communication systems that employ Multiple-Access Interference (MAI) suppression techniques in the uplink (from mobile to base station). Most of the existing schemes rely on time multiplex a training sequence with the user data. In WCDMA, the channel parameters can also be estimated from a code multiplexed common pilot channel (CPICH) that could be corrupted by strong interference resulting in a bad estimate. In this paper, we present new methods to combine interference suppression together with channel estimation when using multiple receiving antennas by using adaptive signal processing techniques. Computer simulation is used to compare between the proposed methods and the existing conventional estimation techniques.
Abstract: Serial Analysis of Gene Expression is a powerful
quantification technique for generating cell or tissue gene expression
data. The profile of the gene expression of cell or tissue in several
different states is difficult for biologists to analyze because of the large
number of genes typically involved. However, feature selection in
machine learning can successfully reduce this problem. The method
allows reducing the features (genes) in specific SAGE data, and
determines only relevant genes. In this study, we used a genetic
algorithm to implement feature selection, and evaluate the
classification accuracy of the selected features with the K-nearest
neighbor method. In order to validate the proposed method, we used
two SAGE data sets for testing. The results of this study conclusively
prove that the number of features of the original SAGE data set can be
significantly reduced and higher classification accuracy can be
achieved.
Abstract: Twenty seven tektites from the Wenchang area, Hainan
province (south China) and five tektites from the Khon Kaen area
(northeast Thailand) were analyzed for major and trace element
contents and Rb-Sr isotopic compositions. All the samples studied are
splash-form tektites. Tektites of this study are characterized by high
SiO2 contents ranging from 71.95 to 74.07 wt% which is consistent
with previously published analyses of Australasian tektites. The trace
element ratios Ba/Rb (avg. 3.89), Th/Sm (avg. 2.40), Sm/Sc (avg.
0.45), Th/Sc (avg. 0.99) and the rare earth elements (REE) contents of
tektites of this study are similar to the average upper continental crust.
Based on the chemical composition, it is suggested that tektites in this
study are derived from similar parental material and are similar to the
post-Archean upper crustal rocks. The major and trace element
abundances of tektites analyzed indicate that the parental material of
tektites may be a terrestrial sedimentary deposit. The tektites from the
Wenchang area, Hainan Island have high positive εSr(0)
values-ranging from 184.5~196.5 which indicate that the parental
material for these tektites have similar Sr isotopic compositions to old
terrestrial sedimentary rocks and they were not dominantly derived
from recent young sediments (such as soil or loess). Based on Rb-Sr
isotopic data, it has been suggested by Blum (1992) [1]that the
depositional age of sedimentary target materials is close to 170Ma
(Jurassic). According to the model suggested by Ho and Chen
(1996)[2], mixing calculations for various amounts and combinations
of target rocks have been carried out. We consider that the best fit for
tektites from the Wenchang area is a mixture of 47% shale, 23%
sandstone, 25% greywacke and 5% quartzite, and the other tektites
from Khon Kaen area is a mixture of 46% shale, 2% sandstone, 20%
greywacke and 32% quartzite.