Abstract: We present a low frequency watermarking method
adaptive to image content. The image content is analyzed and
properties of HVS are exploited to generate a visual mask of the
same size as the approximation image. Using this mask we embed the
watermark in the approximation image without degrading the image
quality. Watermark detection is performed without using the original
image. Experimental results show that the proposed watermarking
method is robust against most common image processing operations,
which can be easily implemented and usually do not degrade the
image quality.
Abstract: This study was conducted to evaluate factors
regulating groundwater quality in an area with agriculture as main
use. Under this study twelve groundwater samples have been
collected from Padra taluka, Dabhoi taluka and Savli taluka of
Vadodara district. Groundwater samples were chemically analyzed
for major physicochemical parameter in order to understand the
different geochemical processes affecting the groundwater quality.
The analytical results shows higher concentration of total dissolved
solids (16.67%), electrical conductivity (25%) and magnesium
(8.33%) for pre monsoon and total dissolved solids (16.67%),
electrical conductivity (33.3%) and magnesium (8.33%) for post
monsoon which indicates signs of deterioration as per WHO and BIS
standards. On the other hand, 50% groundwater sample is unsuitable
for irrigation purposes based on irrigation quality parameters. The
study revealed that application of fertilizer for agricultural
contributing the higher concentration of ions in aquifer of Vadodara
district.
Abstract: The aim of the research is to understand whether the accuracy of customer detection of employee emotional labor strategy would influence the overall service satisfaction. From path analysis, it was found that employee-s positive emotions positively influenced service quality. Service quality in turn influenced Customer detection of employee emotional deep action strategy and Customer detection of employee emotional surface action strategy. Lastly, Customer detection of employee emotional deep action strategy and Customer detection of employee emotional surface action strategy positively influenced service satisfaction. Based on the analysis results, suggestions are proposed to provide reference for human resource management and use in relative fields.
Abstract: The customer satisfaction for textile sector carries
great importance like the customer satisfaction for other sectors
carry. Especially, if it is considered that gaining new customers
create four times more costs than protecting existing customers from
leaving, it can be seen that the customer satisfaction plays a great
role for the firms. In this study the affecting independent variables of
customer satisfaction are chosen as brand image, perceived service
quality and perceived product quality. By these independent
variables, it is investigated that if any differences exist in perception
of customer satisfaction according to the Turkish textile consumers in
the view of gender. In data analysis of this research the SPSS
program is used.
Abstract: Support Vector Machine (SVM) is a statistical
learning tool that was initially developed by Vapnik in 1979 and later
developed to a more complex concept of structural risk minimization
(SRM). SVM is playing an increasing role in applications to
detection problems in various engineering problems, notably in
statistical signal processing, pattern recognition, image analysis, and
communication systems. In this paper, SVM was applied to the
detection of SAR (synthetic aperture radar) images in the presence of
partially developed speckle noise. The simulation was done for single
look and multi-look speckle models to give a complete overlook and
insight to the new proposed model of the SVM-based detector. The
structure of the SVM was derived and applied to real SAR images
and its performance in terms of the mean square error (MSE) metric
was calculated. We showed that the SVM-detected SAR images have
a very low MSE and are of good quality. The quality of the
processed speckled images improved for the multi-look model.
Furthermore, the contrast of the SVM detected images was higher
than that of the original non-noisy images, indicating that the SVM
approach increased the distance between the pixel reflectivity levels
(the detection hypotheses) in the original images.
Abstract: Due to the fact that in the new century customers tend
to express globally increasing demands, networks of interconnected
businesses have been established in societies and the management of
such networks seems to be a major key through gaining competitive
advantages. Supply chain management encompasses such managerial
activities. Within a supply chain, a critical role is played by quality.
QFD is a widely-utilized tool which serves the purpose of not only
bringing quality to the ultimate provision of products or service
packages required by the end customer or the retailer, but it can also
initiate us into a satisfactory relationship with our initial customer;
that is the wholesaler. However, the wholesalers- cooperation is
considerably based on the capabilities that are heavily dependent on
their locations and existing circumstances. Therefore, it is undeniable
that for all companies each wholesaler possesses a specific
importance ratio which can heavily influence the figures calculated in
the House of Quality in QFD. Moreover, due to the competitiveness
of the marketplace today, it-s been widely recognized that
consumers- expression of demands has been highly volatile in
periods of production. Apparently, such instability and proneness to
change has been very tangibly noticed and taking it into account
during the analysis of HOQ is widely influential and doubtlessly
required. For a more reliable outcome in such matters, this article
demonstrates the application viability of Analytic Network Process
for considering the wholesalers- reputation and simultaneously
introduces a mortality coefficient for the reliability and stability of
the consumers- expressed demands in course of time. Following to
this, the paper provides further elaboration on the relevant
contributory factors and approaches through the calculation of such
coefficients. In the end, the article concludes that an empirical
application is needed to achieve broader validity.
Abstract: Meshing is the process of discretizing problem
domain into many sub domains before the numerical calculation can
be performed. One of the most popular meshes among many types of meshes is tetrahedral mesh, due to their flexibility to fit into almost
any domain shape. In both 2D and 3D domains, triangular and tetrahedral meshes can be generated by using Delaunay triangulation.
The quality of mesh is an important factor in performing any Computational Fluid Dynamics (CFD) simulations as the results is
highly affected by the mesh quality. Many efforts had been done in
order to improve the quality of the mesh. The paper describes a mesh
generation routine which has been developed capable of generating
high quality tetrahedral cells in arbitrary complex geometry. A few
test cases in CFD problems are used for testing the mesh generator.
The result of the mesh is compared with the one generated by a
commercial software. The results show that no sliver exists for the
meshes generated, and the overall quality is acceptable since the percentage of the bad tetrahedral is relatively small. The boundary
recovery was also successfully done where all the missing faces are
rebuilt.
Abstract: One of the determinants of a firm-s prosperity is the
customers- perceived service quality and satisfaction. While service
quality is wide in scope, and consists of various dimensions, there
may be differences in the relative importance of these dimensions in
affecting customers- overall satisfaction of service quality.
Identifying the relative rank of different dimensions of service quality
is very important in that it can help managers to find out which
service dimensions have a greater effect on customers- overall
satisfaction. Such an insight will consequently lead to more effective
resource allocation which will finally end in higher levels of
customer satisfaction. This issue – despite its criticality- has not
received enough attention so far. Therefore, using a sample of 240
bank customers in Iran, an artificial neural network is developed to
address this gap in the literature. As customers- evaluation of service
quality is a subjective process, artificial neural networks –as a brain
metaphor- may appear to have a potentiality to model such a
complicated process. Proposing a neural network which is able to
predict the customers- overall satisfaction of service quality with a
promising level of accuracy is the first contribution of this study. In
addition, prioritizing the service quality dimensions in affecting
customers- overall satisfaction –by using sensitivity analysis of
neural network- is the second important finding of this paper.
Abstract: This article proposes a new methodology to be used by SMEs (Small and Medium enterprises) to characterize their performance in quality, highlighting weaknesses and area for improvement. The methodology aims to identify the principal causes of quality problems and help to prioritize improvement initiatives. This is a self-assessment methodology that intends to be easy to implement by companies with low maturity level in quality. The methodology is organized in six different steps which includes gathering information about predetermined processes and subprocesses of quality management, defined based on the well-known Juran-s trilogy for quality management (Quality planning, quality control and quality improvement) and, predetermined results categories, defined based on quality concept. A set of tools for data collecting and analysis, such as interviews, flowcharts, process analysis diagrams and Failure Mode and effects Analysis (FMEA) are used. The article also presents the conclusions obtained in the application of the methodology in two cases studies.
Abstract: This paper proposes an innovative methodology for
Acceptance Sampling by Variables, which is a particular category of
Statistical Quality Control dealing with the assurance of products
quality. Our contribution lies in the exploitation of machine learning
techniques to address the complexity and remedy the drawbacks of
existing approaches. More specifically, the proposed methodology
exploits Artificial Neural Networks (ANNs) to aid decision making
about the acceptance or rejection of an inspected sample. For any
type of inspection, ANNs are trained by data from corresponding
tables of a standard-s sampling plan schemes. Once trained, ANNs
can give closed-form solutions for any acceptance quality level and
sample size, thus leading to an automation of the reading of the
sampling plan tables, without any need of compromise with the
values of the specific standard chosen each time. The proposed
methodology provides enough flexibility to quality control engineers
during the inspection of their samples, allowing the consideration of
specific needs, while it also reduces the time and the cost required for
these inspections. Its applicability and advantages are demonstrated
through two numerical examples.
Abstract: The technique of inducing micro ecosystem
restoration is one of aquatic ecology engineering methods used to
retrieve the polluted water. Batch scale study, pilot plant study, and
field study were carried out to observe the eutrophication using the
Inducing Ecology Restorative Symbiosis Agent (IERSA) consisting
mainly degraded products by using lactobacillus, saccharomycete,
and phycomycete. The results obtained from the experiments of the
batch scale and pilot plant study allowed us to development the
parameters for the field study. A pond, 5 m to the outlet of a lake,
with an area of 500 m2 and depth of 0.6-1.2 m containing about 500
tons of water was selected as a model. After the treatment with 10
mg IERSA/L water twice a week for 70 days, the micro restoration
mechanisms consisted of three stages (i.e., restoration, impact
maintenance, and ecology recovery experiment after impact). The
COD, TN, TKN, and chlorophyll a were reduced significantly in the
first week. Although the unexpected heavy rain and contaminate
from sewage system might slow the ecology restoration. However,
the self-cleaning function continued and the chlorophyll a reduced
for 50% in one month. In the 4th week, amoeba, paramecium, rotifer,
and red wriggle worm reappeared, and the number of fish flies
appeared up to1000 fish fries/m3. Those results proved that inducing
restorative mechanism can be applied to improve the eutrophication
and to control the growth of algae in the lakes by gaining the selfcleaning
through inducing and competition of microbes. The
situation for growth of fishes also can reach an excellent result due to
the improvement of water quality.
Abstract: This paper proposes a novel game theoretical
technique to address the problem of data object replication in largescale
distributed computing systems. The proposed technique draws
inspiration from computational economic theory and employs the
extended Vickrey auction. Specifically, players in a non-cooperative
environment compete for server-side scarce memory space to
replicate data objects so as to minimize the total network object
transfer cost, while maintaining object concurrency. Optimization of
such a cost in turn leads to load balancing, fault-tolerance and
reduced user access time. The method is experimentally evaluated
against four well-known techniques from the literature: branch and
bound, greedy, bin-packing and genetic algorithms. The experimental
results reveal that the proposed approach outperforms the four
techniques in both the execution time and solution quality.
Abstract: In this paper, a new encoding algorithm of spectral envelope based on NLMS in G.729.1 for VoIP is proposed. In the TDAC part of G.729.1, the spectral envelope and MDCT coefficients extracted in the weighted CELP coding error (lower-band) and the higher-band input signal are encoded. In order to reduce allocation bits for spectral envelope coding, a new quantization algorithm based on NLMS is proposed. Also, reduced bits are used to enhance sound quality. The performance of the proposed algorithm is evaluated by sound quality and bit reduction rates in clean and frame loss conditions.
Abstract: In text categorization problem the most used method
for documents representation is based on words frequency vectors
called VSM (Vector Space Model). This representation is based only
on words from documents and in this case loses any “word context"
information found in the document. In this article we make a
comparison between the classical method of document representation
and a method called Suffix Tree Document Model (STDM) that is
based on representing documents in the Suffix Tree format. For the
STDM model we proposed a new approach for documents
representation and a new formula for computing the similarity
between two documents. Thus we propose to build the suffix tree
only for any two documents at a time. This approach is faster, it has
lower memory consumption and use entire document representation
without using methods for disposing nodes. Also for this method is
proposed a formula for computing the similarity between documents,
which improves substantially the clustering quality. This
representation method was validated using HAC - Hierarchical
Agglomerative Clustering. In this context we experiment also the
stemming influence in the document preprocessing step and highlight
the difference between similarity or dissimilarity measures to find
“closer" documents.
Abstract: System testing is actually done to the entire system
against the Functional Requirement Specification and/or the System
Requirement Specification. Moreover, it is an investigatory testing
phase, where the focus is to have almost a destructive attitude and
test not only the design, but also the behavior and even the believed
expectations of the customer. It is also intended to test up to and
beyond the bounds defined in the software/hardware requirements
specifications. In Motorola®, Automated Testing is one of the testing
methodologies uses by GSG-iSGT (Global Software Group - iDEN
TM
Subcriber Group-Test) to increase the testing volume, productivity
and reduce test cycle-time in iDEN
TM
phones testing. Testing is able
to produce more robust products before release to the market. In this
paper, iHopper is proposed as a tool to perform stress test on iDEN
TM
phonse. We will discuss the value that automation has brought to
iDEN
TM
Phone testing such as improving software quality in the
iDEN
TM
phone together with some metrics. We will also look into
the advantages of the proposed system and some discussion of the
future work as well.
Abstract: User-based Collaborative filtering (CF), one of the
most prevailing and efficient recommendation techniques, provides
personalized recommendations to users based on the opinions of other
users. Although the CF technique has been successfully applied in
various applications, it suffers from serious sparsity problems. The
cloud-model approach addresses the sparsity problems by
constructing the user-s global preference represented by a cloud
eigenvector. The user-based CF approach works well with dense
datasets while the cloud-model CF approach has a greater
performance when the dataset is sparse. In this paper, we present a
hybrid approach that integrates the predictions from both the
user-based CF and the cloud-model CF approaches. The experimental
results show that the proposed hybrid approach can ameliorate the
sparsity problem and provide an improved prediction quality.
Abstract: Perth will run out of available sustainable natural
water resources by 2015 if nothing is done to slow usage rates,
according to a Western Australian study [1]. Alternative water
technology options need to be considered for the long-term
guaranteed supply of water for agricultural, commercial, domestic
and industrial purposes. Seawater is an alternative source of water for
human consumption, because seawater can be desalinated and
supplied in large quantities to a very high quality.
While seawater desalination is a promising option, the technology
requires a large amount of energy which is typically generated from
fossil fuels. The combustion of fossil fuels emits greenhouse gases
(GHG) and, is implicated in climate change. In addition to
environmental emissions from electricity generation for desalination,
greenhouse gases are emitted in the production of chemicals and
membranes for water treatment. Since Australia is a signatory to the
Kyoto Protocol, it is important to quantify greenhouse gas emissions
from desalinated water production.
A life cycle assessment (LCA) has been carried out to determine
the greenhouse gas emissions from the production of 1 gigalitre (GL)
of water from the new plant. In this LCA analysis, a new desalination
plant that will be installed in Bunbury, Western Australia, and known
as Southern Seawater Desalinization Plant (SSDP), was taken as a
case study. The system boundary of the LCA mainly consists of three
stages: seawater extraction, treatment and delivery. The analysis
found that the equivalent of 3,890 tonnes of CO2 could be emitted
from the production of 1 GL of desalinated water. This LCA analysis
has also identified that the reverse osmosis process would cause the
most significant greenhouse emissions as a result of the electricity
used if this is generated from fossil fuels
Abstract: The algorithm represents the DCT coefficients to concentrate signal energy and proposes combination and dictator to eliminate the correlation in the same level subband for encoding the DCT-based images. This work adopts DCT and modifies the SPIHT algorithm to encode DCT coefficients. The proposed algorithm also provides the enhancement function in low bit rate in order to improve the perceptual quality. Experimental results indicate that the proposed technique improves the quality of the reconstructed image in terms of both PSNR and the perceptual results close to JPEG2000 at the same bit rate.
Abstract: The study was carried out to evaluated effect of S-gridling on fruit growth and quality of wax apple. The study was laid in Random completed block design with four replicated. Four treatment were applied as follows: S-girdling, fruit thinning plus bagging with 2,4-D sprayed, fruit thinning plus bagging and the control treatment. 2,4D was sprayed at the small bud and petal fall stage. Girdling was applied three week before flowering. The effect of all treatments on fruit growth was measured weekly. Number of flower, fruit set, fruit drop, fruit crack, and fruit quality were recorded. The result indicated that S-girdling, 2,4D application produced the lowest bud drop, fruit drop compared to untreated control. S-girdling improved faster fruit growth producing the best final fruit length and diameter compared to untreated control. S-girdling also markedly enhanced fruit set, fruit weight, and total soluble solid, reduced fruit crack, titratable acidity. On the other hand, it was noticed that with 2,4-D application also increased the fruit growth rate, improved physiological and biochemical characters of fruit than control treatment. It was concluded that S-girdling was recommended as the industry norm to increase fruit set, fruit quality in wax apple. 2,4D application had a distinctive and significant effect on most of the fruit quality characteristics assessed.
Abstract: The objective of this research was to study factors,
which were affected on surface roughness in high speed milling of
hardened tool steel. Material used in the experiment was tool steel JIS
SKD 61 that hardened on 60 ±2 HRC. Full factorial experimental
design was conducted on 3 factors and 3 levels (3
3
designs) with 2
replications. Factors were consisted of cutting speed, feed rate, and
depth of cut. The results showed that influenced factor affected to
surface roughness was cutting speed, feed rate and depth of cut which
showed statistical significant. Higher cutting speed would cause on
better surface quality. On the other hand, higher feed rate would cause
on poorer surface quality. Interaction of factor was found that cutting
speed and depth of cut were significantly to surface quality. The
interaction of high cutting speed associated with low depth of cut
affected to better surface quality than low cutting speed and high depth
of cut.