Abstract: Web search engines are designed to retrieve and
extract the information in the web databases and to return dynamic
web pages. The Semantic Web is an extension of the current web in
which it includes semantic content in web pages. The main goal of
semantic web is to promote the quality of the current web by
changing its contents into machine understandable form. Therefore,
the milestone of semantic web is to have semantic level information
in the web. Nowadays, people use different keyword- based search
engines to find the relevant information they need from the web.
But many of the words are polysemous. When these words are
used to query a search engine, it displays the Search Result Records
(SRRs) with different meanings. The SRRs with similar meanings are
grouped together based on Word Sense Disambiguation (WSD). In
addition to that semantic annotation is also performed to improve the
efficiency of search result records. Semantic Annotation is the
process of adding the semantic metadata to web resources. Thus the
grouped SRRs are annotated and generate a summary which
describes the information in SRRs. But the automatic semantic
annotation is a significant challenge in the semantic web. Here
ontology and knowledge based representation are used to annotate
the web pages.
Abstract: Consumer-to-Consumer (C2C) E-commerce has been
growing at a very high speed in recent years. Since identical or
nearly-same kinds of products compete one another by relying on
keyword search in C2C E-commerce, some sellers describe their
products with spam keywords that are popular but are not related to
their products. Though such products get more chances to be retrieved
and selected by consumers than those without spam keywords,
the spam keywords mislead the consumers and waste their time.
This problem has been reported in many commercial services like
ebay and taobao, but there have been little research to solve this
problem. As a solution to this problem, this paper proposes a method
to classify whether keywords of a product are spam or not. The
proposed method assumes that a keyword for a given product is
more reliable if the keyword is observed commonly in specifications
of products which are the same or the same kind as the given
product. This is because that a hierarchical category of a product
in general determined precisely by a seller of the product and so is
the specification of the product. Since higher layers of the hierarchical
category represent more general kinds of products, a reliable degree
is differently determined according to the layers. Hence, reliable
degrees from different layers of a hierarchical category become
features for keywords and they are used together with features only
from specifications for classification of the keywords. Support Vector
Machines are adopted as a basic classifier using the features, since
it is powerful, and widely used in many classification tasks. In
the experiments, the proposed method is evaluated with a golden
standard dataset from Yi-han-wang, a Chinese C2C E-commerce,
and is compared with a baseline method that does not consider
the hierarchical category. The experimental results show that the
proposed method outperforms the baseline in F1-measure, which
proves that spam keywords are effectively identified by a hierarchical
category in C2C E-commerce.
Abstract: The ever increasing amount of solid waste (SW)
generated which is exacerbated by lack of proper waste management
system is of growing concern worldwide and in major cities in
developing countries due to its social, economic and environmental
implications. This study attempts to describe the aspects of solid
waste management (SWM) in Adama, one of the fast urbanizing
cities in Ethiopia, and highlights the challenges thereof. Data were
gathered through interview supplemented by field observation and
self-administered questionnaire. Then, the data were analyzed using
the Statistical Package for Social Science (SPSS) software. In
addition, secondary data were gathered from documents. Findings
revealed that the current SWM practice couldn’t cope with the fast
urbanizing needs and the rapid population growth exhibited by the
city. Besides, major factors contributing to the inefficient system
were identified. The study would provide practical insights to
decision makers in developing a sustainable SWM system leading to
minimized risk in the city.
Abstract: This study models the use of transcutaneous electrical
nerve stimulation on skin with a disk electrode in order to simulate
tissue damage. The current density distribution above a disk electrode
is known to be a dynamic and non-uniform quantity that is intensified
at the edges of the disk. The non-uniformity is subject to change
through using various electrode geometries or stimulation methods.
One of these methods known as edge-retarded stimulation has shown
to reduce this edge enhancement. Though progress has been made in
modeling the behavior of a disk electrode, little has been done to test
the validity of these models in simulating the actual heat transfer
from the electrode. This simulation uses finite element software to
couple the injection of current from a disk electrode to heat transfer
described by the Pennesbioheat transfer equation. An example
application of this model is studying an experimental form of
stimulation, known as edge-retarded stimulation. The edge-retarded
stimulation method will reduce the current density at the edges of the
electrode. It is hypothesized that reducing the current density edge
enhancement effect will, in turn, reduce temperature change and
tissue damage at the edges of these electrodes. This study tests this
hypothesis as a demonstration of the capabilities of this model. The
edge-retarded stimulation proved to be safer after this simulation. It is
shown that temperature change and the fraction of tissue necrosis is
much greater in the square wave stimulation. These results bring
implications for changes of procedures in transcutaneous electrical
nerve stimulation and transcutaneous spinal cord stimulation as well.
Abstract: In this study, six bacterial isolates of a slightly
thermophilic organism from the Sg. Klah hot spring, Malaysia were
successfully isolated and designated as M7T55D1, M7T55D2,
M7T55D3, M7T53D1, M7T53D2 and M7T53D3 respectively. The
bacterial isolates were screened for their cellulose hydrolytic ability
on Carboxymethlycellulose agar medium. The isolated bacterial
strains were identified morphologically, biochemically and
molecularly with the aid of 16S rDNA sequencing. All of the bacteria
showed their optimum growth at a slightly alkaline pH of 7.5 with a
temperature of 55°C. All strains were Gram-negative, non-spore
forming type, strictly aerobic, catalase-positive and oxidase-positive
with the ability to produce thermostable cellulase. Based on BLASTn
results, bacterial isolates of M7T55D2 and M7T53D1 gave the
highest homology (97%) with similarity to Tepidimonas ignava while
isolates M7T55D1, M7T55D3, M7T53D2 and M7T53D3 showed
their closest homology (97%-98%) with Tepidimonas thermarum.
These cellulolytic thermophiles might have a commercial potential to
produce valuable thermostable cellulase.
Abstract: Application of hulls processing technologies, based on high-concentrated energy sources (laser and plasma technologies), allow improve shipbuilding production. It is typical for high-speed vessels construction using steel and aluminum alloys with high precision hulls required. Report describes high-performance technologies for plasma welding (using direct current of reversed polarity), laser, and hybrid laser-arc welding of hulls structures developed by JSC “SSTC”
Abstract: The emergence of the Semantic Web technology
increases day by day due to the rapid growth of multiple web pages.
Many standard formats are available to store the semantic web data.
The most popular format is the Resource Description Framework
(RDF). Querying large RDF graphs becomes a tedious procedure
with a vast increase in the amount of data. The problem of query
optimization becomes an issue in querying large RDF graphs.
Choosing the best query plan reduces the amount of query execution
time. To address this problem, nature inspired algorithms can be used
as an alternative to the traditional query optimization techniques. In
this research, the optimal query plan is generated by the proposed
SAPSO algorithm which is a hybrid of Simulated Annealing (SA)
and Particle Swarm Optimization (PSO) algorithms. The proposed
SAPSO algorithm has the ability to find the local optimistic result
and it avoids the problem of local minimum. Experiments were
performed on different datasets by changing the number of predicates
and the amount of data. The proposed algorithm gives improved
results compared to existing algorithms in terms of query execution
time.
Abstract: Thermal insulation materials based on natural fibers
represent a very promising area of materials based on natural easy
renewable row sources. These materials may be in terms of the
properties of most competing synthetic insulations, but show
somewhat higher moisture sensitivity and thermal insulation
properties are strongly influenced by the density and orientation of
fibers. The paper described the problem of hygrothermal behavior of
thermal insulation materials based on natural plant and animal fibers.
This is especially the dependence of the thermal properties of these
materials on the type of fiber, bulk density, temperature, moisture and
the fiber orientation.
Abstract: Electronic market place plays an important
intermediary role for connecting dealers and retail customers. The
main aim of this paper is to design a value co-creation model in
used-car auctions. More specifically, the study has been designed in
order to describe the process of value co-creation in used-car auctions,
to explore the co-created values in used-car auctions, and finally
conclude the paper indicating the future research directions. Our
analysis shows that economic values as well as non-economic values
are co-created in used-car auctions. In addition, this paper contributes
to the academic society broadening the view of value co-creation in
service science.
Abstract: Because of high thermal efficiency and low CO2
emission, diesel engines are being used widely in many industrial
fields although it makes many PM and NOx which give both human
health and environment a negative effect. NOx regulations for diesel
engines, however, are being strengthened and it is impossible to meet
the emission standard without NOx reduction devices such as SCR
(Selective Catalytic Reduction), LNC (Lean NOx Catalyst), and LNT
(Lean NOx Trap). Among the NOx reduction devices, urea-SCR
system is known as the most stable and efficient method to solve the
problem of NOx emission. But this device has some issues associated
with the ammonia slip phenomenon which is occurred by shortage of
evaporation and thermolysis time, and that makes it difficult to achieve
uniform distribution of the injected urea in front of monolith.
Therefore, this study has focused on the mixing enhancement between
urea and exhaust gases to enhance the efficiency of the SCR catalyst
equipped in catalytic muffler by changing inlet gas temperature and
spray conditions to improve the spray uniformity of the urea water
solution. Finally, it can be found that various parameters such as inlet
gas temperature and injector and injection angles significantly affect
the evaporation and mixing of the urea water solution with exhaust
gases, and therefore, optimization of these parameters are required.
Abstract: An extensive amount of work has been done in data
clustering research under the unsupervised learning technique in Data
Mining during the past two decades. Moreover, several approaches
and methods have been emerged focusing on clustering diverse data
types, features of cluster models and similarity rates of clusters.
However, none of the single clustering algorithm exemplifies its best
nature in extracting efficient clusters. Consequently, in order to
rectify this issue, a new challenging technique called Cluster
Ensemble method was bloomed. This new approach tends to be the
alternative method for the cluster analysis problem. The main
objective of the Cluster Ensemble is to aggregate the diverse
clustering solutions in such a way to attain accuracy and also to
improve the eminence the individual clustering algorithms. Due to
the massive and rapid development of new methods in the globe of
data mining, it is highly mandatory to scrutinize a vital analysis of
existing techniques and the future novelty. This paper shows the
comparative analysis of different cluster ensemble methods along
with their methodologies and salient features. Henceforth this
unambiguous analysis will be very useful for the society of clustering
experts and also helps in deciding the most appropriate one to resolve
the problem in hand.
Abstract: Fluid rheology may have essential impact on sound propagation in a liquid-filled pipe, especially, in a low frequency range. Rheological parameters of liquid are temperature-sensitive, which ultimately results in a temperature dependence of the wave speed and attenuation in the waveguide. The study is devoted to modeling of this effect at sound propagation in an elastic pipe with polymeric liquid, described by generalized Maxwell model with non-zero high-frequency viscosity. It is assumed that relaxation spectrum is distributed according to the Spriggs law; temperature impact on the liquid rheology is described on the basis of the temperature-superposition principle and activation theory. The dispersion equation for the waveguide, considered as a thin-walled tube with polymeric solution, is obtained within a quasi-one-dimensional formulation. Results of the study illustrate the influence of temperature on sound propagation in the system.
Abstract: A theoretical study has been presented to describe the boundary layer flow and heat transfer on an exponentially shrinking sheet with a variable wall temperature and suction, in the presence of magnetic field. The governing nonlinear partial differential equations are converted into ordinary differential equations by similarity transformation, which are then solved numerically using the shooting method. Results for the skin friction coefficient, local Nusselt number, velocity profiles as well as temperature profiles are presented through graphs and tables for several sets of values of the parameters. The effects of the governing parameters on the flow and heat transfer characteristics are thoroughly examined.
Abstract: This paper presents development of the light-weight manipulator with series elastic actuation for medical telediagnostics (USG examination). General structure of realized impedance control algorithm was shown. It was described how to perform force measurements based mainly on elasticity of manipulator links.
Abstract: In this paper, we present a new maintenance model
for a partially observable system subject to two failure modes,
namely a catastrophic failure and a failure due to the system
degradation. The system is subject to condition monitoring and the
degradation process is described by a hidden Markov model. A
cost-optimal Bayesian control policy is developed for maintaining
the system. The control problem is formulated in the semi-Markov
decision process framework. An effective computational algorithm is
developed, illustrated by a numerical example.
Abstract: The aim of this paper is to create a proposal for determining the costs of logistics processes by using process-oriented calculation methods. The traditional approach is that logistics costs are part of manufacturing overhead which is usually calculated as a percentage surcharge. Therefore in the traditional approach it is not obvious where and in which activities costs were incurred. So it is impossible to trace logistics costs to products. Our point of view is trying to fix or at least improve this issue. Another benefit of applying the process approach is identification of logistics processes which are otherwise part of manufacturing overhead. In the first part this paper describes the development of process-oriented methods over time. The next part shows the possibility of implementing the process-oriented method called Prozesskostenrechnung to logistics processes. The conclusion summarizes advantages and disadvantages of using this method in logistics.
Abstract: Analytical expressions of the current and angular errors, as well as the frequency characteristics of an induction converter describing the relation with its structural parameters, the core and winding characteristics are obtained. Based on estimation of the dependences obtained, a mathematical problem of parametric optimization is formulated which can successfully be used for investigating and diagnosing an induction converter.
Abstract: Developing a reliable and sustainable software products is today a big challenge among up–coming software developers in Nigeria. The inability to develop a comprehensive problem statement needed to execute proper requirements engineering process is missing. The need to describe the ‘what’ of a system in one document, written in a natural language is a major step in the overall process of Software Engineering. Requirements Engineering is a process use to discover, analyze and validate system requirements. This process is needed in reducing software errors at the early stage of the development of software. The importance of each of the steps in Requirements Engineering is clearly explained in the context of using detailed problem statement from client/customer to get an overview of an existing system along with expectations from the new system. This paper elicits inadequate Requirements Engineering principle as the major cause of poor software development in developing nations using a case study of final year computer science students of a tertiary-education institution in Nigeria.
Abstract: In recent years in Italy the progress of the automobile industry, in the field of reduction of emissions values, is very remarkable. Nevertheless their evaluation and reduction is a key problem, especially in the cities, that account for more than 50% of world population. In this paper we dealt with the problem of describing a quantitatively approach for the reconstruction of GPS coordinates and altitude, in the context of correlation study between driving cycles / emission / geographical location, during an experimental campaign realized with some instrumented cars.
Abstract: In this paper, the design problem of state estimator for
neural networks with the mixed time-varying delays are investigated
by constructing appropriate Lyapunov-Krasovskii functionals and
using some effective mathematical techniques. In order to derive
several conditions to guarantee the estimation error systems to be
globally exponential stable, we transform the considered systems
into the neural-type time-delay systems. Then with a set of linear
inequalities(LMIs), we can obtain the stable criteria. Finally, three
numerical examples are given to show the effectiveness and less
conservatism of the proposed criterion.