Abstract: Increasing growth of information volume in the
internet causes an increasing need to develop new (semi)automatic
methods for retrieval of documents and ranking them according to
their relevance to the user query. In this paper, after a brief review
on ranking models, a new ontology based approach for ranking
HTML documents is proposed and evaluated in various
circumstances. Our approach is a combination of conceptual,
statistical and linguistic methods. This combination reserves the
precision of ranking without loosing the speed. Our approach
exploits natural language processing techniques to extract phrases
from documents and the query and doing stemming on words. Then
an ontology based conceptual method will be used to annotate
documents and expand the query. To expand a query the spread
activation algorithm is improved so that the expansion can be done
flexible and in various aspects. The annotated documents and the
expanded query will be processed to compute the relevance degree
exploiting statistical methods. The outstanding features of our
approach are (1) combining conceptual, statistical and linguistic
features of documents, (2) expanding the query with its related
concepts before comparing to documents, (3) extracting and using
both words and phrases to compute relevance degree, (4) improving
the spread activation algorithm to do the expansion based on
weighted combination of different conceptual relationships and (5)
allowing variable document vector dimensions. A ranking system
called ORank is developed to implement and test the proposed
model. The test results will be included at the end of the paper.
Abstract: Recently, a growing interest has emerged on the
development of new and efficient energy sources, due to the inevitable extinction of the nonrenewable energy reserves. One of
these alternative sources which has a great potential and sustainability to meet up the energy demand is biomass energy. This
significant energy source can be utilized with various energy
conversion technologies, one of which is biomass gasification in
supercritical water.
Water, being the most important solvent in nature, has very important characteristics as a reaction solvent under supercritical
circumstances. At temperatures above its critical point (374.8oC and
22.1 MPa), water becomes more acidic and its diffusivity increases.
Working with water at high temperatures increases the thermal
reaction rate, which in consequence leads to a better dissolving of the
organic matters and a fast reaction with oxygen. Hence, supercritical water offers a control mechanism depending on solubility, excellent
transport properties based on its high diffusion ability and new reaction possibilities for hydrolysis or oxidation.
In this study the gasification of a real biomass, namely olive mill
wastewater (OMW), in supercritical water is investigated with the
use of Pt/Al2O3 and Ni/Al2O3 catalysts. OMW is a by-product
obtained during olive oil production, which has a complex nature
characterized by a high content of organic compounds and
polyphenols. These properties impose OMW a significant pollution
potential, but at the same time, the high content of organics makes
OMW a desirable biomass candidate for energy production.
All of the catalytic gasification experiments were made with five
different reaction temperatures (400, 450, 500, 550 and 600°C),
under a constant pressure of 25 MPa. For the experiments conducted
with Ni/Al2O3 catalyst, the effect of five reaction times (30, 60, 90,
120 and 150 s) was investigated. However, procuring that similar
gasification efficiencies could be obtained at shorter times, the experiments were made by using different reaction times (10, 15, 20,
25 and 30 s) for the case of Pt/Al2O3 catalyst. Through these experiments, the effects of temperature, time and catalyst type on the
gasification yields and treatment efficiencies were investigated.
Abstract: The increasing industrialization and motorization of the world has led to a steep rise for the demand of petroleum-based fuels. Petroleum-based fuels are obtained from limited reserves. These finite reserves are highly concentrated in certain regions of the world. Therefore, those countries not having these resources are facing energy/foreign exchange crisis, mainly due to the import of crude petroleum. Hence, it is necessary to look for alternative fuels which can be produced from resources available locally within the country such as alcohol, biodiesel, vegetable oils etc. Biodiesel is a renewable, domestically produced fuel that has been shown to reduce particulate, hydrocarbon, and carbon monoxide emissions from combustion. In the present study an experimental investigation on emission characteristic of a liquid burner system operating on several percentage of biodiesel and gas oil is carried out. Samples of exhaust gas are analysed with Testo 350 Xl. The results show that biodiesel can lower some pollutant such as CO, CO2 and particulate matter emissions while NOx emission would increase in comparison with gas oil. The results indicate there may be benefits to using biodiesel in industrial processes.
Abstract: In this paper, the local grid refinement is focused by
using a nested grid technique. The Cartesian grid numerical method is
developed for simulating unsteady, viscous, incompressible flows
with complex immersed boundaries. A finite volume method is used in
conjunction with a two-step fractional-step procedure. The key aspects
that need to be considered in developing such a nested grid solver are
imposition of interface conditions on the inter-block and accurate
discretization of the governing equation in cells that are with the
inter-block as a control surface. A new interpolation procedure is
presented which allows systematic development of a spatial
discretization scheme that preserves the spatial accuracy of the
underlying solver. The present nested grid method has been tested by
two numerical examples to examine its performance in the two
dimensional problems. The numerical examples include flow past a
circular cylinder symmetrically installed in a Channel and flow past
two circular cylinders with different diameters. From the numerical
experiments, the ability of the solver to simulate flows with
complicated immersed boundaries is demonstrated and the nested grid
approach can efficiently speed up the numerical solutions.
Abstract: During more than a decade, many proposals and standards have been designed to deal with the mobility issues; however, there are still some serious limitations in basing solutions on them. In this paper we discuss the possibility of handling mobility at the application layer. We do this while revisiting the conventional implementation of the Two Phase Commit (2PC) protocol which is a fundamental asset of transactional technology for ensuring the consistent commitment of distributed transactions. The solution is based on an execution framework providing an efficient extension that is aware of the mobility and preserves the 2PC principle.
Abstract: The present energy situation and the concerns
about global warming has stimulated active research interest
in non-petroleum, carbon free compounds and non-polluting
fuels, particularly for transportation, power generation, and
agricultural sectors. Environmental concerns and limited
amount of petroleum fuels have caused interests in the
development of alternative fuels for internal combustion (IC)
engines. The petroleum crude reserves however, are declining
and consumption of transport fuels particularly in the
developing countries is increasing at high rates. Severe
shortage of liquid fuels derived from petroleum may be faced
in the second half of this century. Recently more and more
stringent environmental regulations being enacted in the USA
and Europe have led to the research and development
activities on clean alternative fuels. Among the gaseous fuels
hydrogen is considered to be one of the clean alternative fuel.
Hydrogen is an interesting candidate for future internal
combustion engine based power trains. In this experimental
investigation, the performance and combustion analysis were
carried out on a direct injection (DI) diesel engine using
hydrogen with diesel following the TMI(Time Manifold
Injection) technique at different injection timings of 10
degree,45 degree and 80 degree ATDC using an electronic
control unit (ECU) and injection durations were controlled.
Further, the tests have been carried out at a constant speed of
1500rpm at different load conditions and it can be observed
that brake thermal efficiency increases with increase in load
conditions with a maximum gain of 15% at full load
conditions during all injection strategies of hydrogen. It was
also observed that with the increase in hydrogen energy share
BSEC started reducing and it reduced to a maximum of 9% as
compared to baseline diesel at 10deg ATDC injection during
maximum injection proving the exceptional combustion
properties of hydrogen.
Abstract: In this paper we present a technique to speed up
ICA based on the idea of reducing the dimensionality of the data
set preserving the quality of the results. In particular we refer to
FastICA algorithm which uses the Kurtosis as statistical property
to be maximized. By performing a particular Johnson-Lindenstrauss
like projection of the data set, we find the minimum dimensionality
reduction rate ¤ü, defined as the ratio between the size k of the reduced
space and the original one d, which guarantees a narrow confidence
interval of such estimator with high confidence level. The derived
dimensionality reduction rate depends on a system control parameter
β easily computed a priori on the basis of the observations only.
Extensive simulations have been done on different sets of real world
signals. They show that actually the dimensionality reduction is very
high, it preserves the quality of the decomposition and impressively
speeds up FastICA. On the other hand, a set of signals, on which the
estimated reduction rate is greater than 1, exhibits bad decomposition
results if reduced, thus validating the reliability of the parameter β.
We are confident that our method will lead to a better approach to
real time applications.
Abstract: The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computationally expensive or produce disappointing results. In this paper, we propose to incorporate the smoothness of the edge field in an implicit way by means of an additional penalty term defined in the wavelet domain. We also derive an efficient half-quadratic algorithm to solve the resulting optimization problem, including the case when the data fidelity term is non-quadratic and the cost function is nonconvex. Numerical experiments show that our technique preserves edge sharpness while smoothing contour lines; it produces visually pleasing reconstructions which are quantitatively better than those obtained without wavelet-domain constraints.
Abstract: The aim of this article is to assess the existing
business models used by the banks operating in the CEE countries in
the time period from 2006 till 2011.
In order to obtain research results, the authors performed
qualitative analysis of the scientific literature on bank business
models, which have been grouped into clusters that consist of such
components as: 1) capital and reserves; 2) assets; 3) deposits, and 4)
loans.
In their turn, bank business models have been developed based on
the types of core activities of the banks, and have been divided into
four groups: Wholesale, Investment, Retail and Universal Banks.
Descriptive statistics have been used to analyse the models,
determining mean, minimal and maximal values of constituent
cluster components, as well as standard deviation. The analysis of
the data is based on such bank variable indices as Return on Assets
(ROA) and Return on Equity (ROE).
Abstract: A large quantity of world-s oil reserves exists in
carbonate reservoirs. Carbonate reservoirs are very sensitive to
chemical enhanced oil recovery process because of containing large
amount of calcite, dolomite and calcium sulfate minerals. These
minerals cause major obstacles during alkali-surfactant-polymer
(ASP) flooding. Alkali reacts with these minerals and form undesired
precipitations which plug effective porous openings, reduce
permeability and cause scale occurrence at the wellbore. In this
paper, a new chemical combination consists of acrylic acid and alkali
was used to minimize precipitation problem during ASP flooding. A
series of fluid-fluid compatibility tests were performed using acrylic
acid and different concentrations of alkaline. Two types of alkalis
namely; sodium carbonate and sodium metaborate were screened. As
a result, the combination of acrylic acid and sodium carbonate was
not effective in preventing calcium and magnesium precipitations.
However, acrylic acid and sodium metaborate showed promising
results for keeping all solutions without any precipitations. The ratio
of acrylic acid to sodium metaborate of 0.7:1.0 was found to be
optimum for achieving a compatible solution for 30 days at 80oC.
Abstract: Gold passbook is an investing tool that is especially
suitable for investors to do small investment in the solid gold. The gold
passbook has the lower risk than other ways investing in gold, but its
price is still affected by gold price. However, there are many factors
can cause influences on gold price. Therefore, building a model to
predict the price of gold passbook can both reduce the risk of
investment and increase the benefits. This study investigates the
important factors that influence the gold passbook price, and utilize
the Group Method of Data Handling (GMDH) to build the predictive
model. This method can not only obtain the significant variables but
also perform well in prediction. Finally, the significant variables of
gold passbook price, which can be predicted by GMDH, are US dollar
exchange rate, international petroleum price, unemployment rate,
whole sale price index, rediscount rate, foreign exchange reserves,
misery index, prosperity coincident index and industrial index.
Abstract: Design for Disassembly (DfD) aims to reuse the
structural components instead of demolition followed by recycling of
the demolition debris. This concept preserves the invested embodied
energy of materials, thus reducing inputs of new embodied energy
during materials reprocessing or remanufacturing. Both analytical and
experimental research on a proposed DfD beam-column connection
for use in residential apartments is currently investigated at the
National University of Singapore in collaboration with the Housing
and Development Board of Singapore. The present study reports on
the results of a numerical analysis of the proposed connection utilizing
finite element analysis. The numerical model was calibrated and
validated by comparison against experimental results. Results of a
parametric study will also be presented and discussed.