Abstract: The concurrent era is characterised by strengthened interactions among financial markets and increased capital mobility globally. In this frames we examine the effects the international financial integration process has on the European bond markets. We perform a comparative study of the interactions of the European and international bond markets and exploit Cointegration analysis results on the elimination of stochastic trends and the decomposition of the underlying long run equilibria and short run causal relations. Our investigation provides evidence on the relation between the European integration process and that of globalisation, viewed through the bond markets- sector. Additionally the structural formulation applied, offers significant implications of the findings. All in all our analysis offers a number of answers on crucial queries towards the European bond markets integration process.
Abstract: Flows over a harmonically oscillating NACA 0012
airfoil are simulated here using a two-dimensional, unsteady,
incompressibleNavier-Stokes solver.Both pure-plunging and
pitching-plunging combined oscillations are considered at a Reynolds
number of 5000. Special attention is paid to the vortex shedding and
interaction mechanism of the motions. For all the simulations
presented here, the reduced frequency (k) is fixed at a value of 2.5
and plunging amplitude (h) is selected to be in the range of 0.2-0.5.
The simulation results show that the interaction mechanism between
the leading and trailing edge vortices has a decisive effect on the
values of the resulting thrust and propulsive efficiency.
Abstract: Sickness absence represents a major economic and
social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is
often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient
and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using
a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model
selection and a critical analysis of the temporal trends, the occurrence
and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large
sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to
select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model
applicability to complicated longitudinal data.
Abstract: Text categorization (the assignment of texts in natural language into predefined categories) is an important and extensively studied problem in Machine Learning. Currently, popular techniques developed to deal with this task include many preprocessing and learning algorithms, many of which in turn require tuning nontrivial internal parameters. Although partial studies are available, many authors fail to report values of the parameters they use in their experiments, or reasons why these values were used instead of others. The goal of this work then is to create a more thorough comparison of preprocessing parameters and their mutual influence, and report interesting observations and results.
Abstract: In this paper, by utilizing the coincidence degree theorem a predator-prey model with modified Leslie-Gower Hollingtype II schemes and a deviating argument is studied. Some sufficient conditions are obtained for the existence of positive periodic solutions of the model.
Abstract: This paper proposes a smart design strategy for a sequential detector to reliably detect the primary user-s signal, especially in fast fading environments. We study the computation of the log-likelihood ratio for coping with a fast changing received signal and noise sample variances, which are considered random variables. First, we analyze the detectability of the conventional generalized log-likelihood ratio (GLLR) scheme when considering fast changing statistics of unknown parameters caused by fast fading effects. Secondly, we propose an efficient sensing algorithm for performing the sequential probability ratio test in a robust and efficient manner when the channel statistics are unknown. Finally, the proposed scheme is compared to the conventional method with simulation results with respect to the average number of samples required to reach a detection decision.
Abstract: Rule Discovery is an important technique for mining knowledge from large databases. Use of objective measures for discovering interesting rules lead to another data mining problem, although of reduced complexity. Data mining researchers have studied subjective measures of interestingness to reduce the volume of discovered rules to ultimately improve the overall efficiency of KDD process. In this paper we study novelty of the discovered rules as a subjective measure of interestingness. We propose a hybrid approach that uses objective and subjective measures to quantify novelty of the discovered rules in terms of their deviations from the known rules. We analyze the types of deviation that can arise between two rules and categorize the discovered rules according to the user specified threshold. We implement the proposed framework and experiment with some public datasets. The experimental results are quite promising.
Abstract: Metal stamping die design is a complex, experiencebased
and time-consuming task. Various artificial intelligence (AI)
techniques are being used by worldwide researchers for stamping die
design to reduce complexity, dependence on human expertise and
time taken in design process as well as to improve design efficiency.
In this paper a comprehensive review of applications of AI
techniques in manufacturability evaluation of sheet metal parts, die
design and process planning of metal stamping die is presented.
Further the salient features of major research work published in the
area of metal stamping are presented in tabular form and scope of
future research work is identified.
Abstract: An advanced Monte Carlo simulation method, called Subset Simulation (SS) for the time-dependent reliability prediction for underground pipelines has been presented in this paper. The SS can provide better resolution for low failure probability level with efficient investigating of rare failure events which are commonly encountered in pipeline engineering applications. In SS method, random samples leading to progressive failure are generated efficiently and used for computing probabilistic performance by statistical variables. SS gains its efficiency as small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment. It is hoped that the development work can promote the use of SS tools for uncertainty propagation in the decision-making process of underground pipelines network reliability prediction.
Abstract: Transesterification of candlenut (aleurites moluccana)
oil with methanol using potassium hydroxide as catalyst was
studied. The objective of the present investigation was to produce
the methyl ester for use as biodiesel. The operation variables
employed were methanol to oil molar ratio (3:1 – 9:1), catalyst
concentration (0.50 – 1.5 %) and temperature (303 – 343K). Oil
volume of 150 mL, reaction time of 75 min were fixed as common
parameters in all the experiments. The concentration of methyl ester
was evaluated by mass balance of free glycerol formed which was
analyzed by using periodic acid. The optimal triglyceride conversion
was attained by using methanol to oil ratio of 6:1, potassium
hydroxide as catalyst was of 1%, at room temperature. Methyl ester
formed was characterized by its density, viscosity, cloud and pour
points. The biodiesel properties had properties similar to those of
diesel oil, except for the viscosity that was higher.
Abstract: In Peer-to-Peer service networks, where peers offer any kind of publicly available services or applications, intuitive navigation through all services in the network becomes more difficult as the number of services increases. In this article, a concept is discussed that enables users to intuitively browse and use large scale P2P service networks. The concept extends the idea of creating virtual 3D-environments solely based on Peer-to-Peer technologies. Aside from browsing, users shall have the possibility to emphasize services of interest using their own semantic criteria. The appearance of the virtual world shall intuitively reflect network properties that may be of interest for the user. Additionally, the concept comprises options for load- and traffic-balancing. In this article, the requirements concerning the underlying infrastructure and the graphical user interface are defined. First impressions of the appearance of future systems are presented and the next steps towards a prototypical implementation are discussed.
Abstract: Pretreatment of lignocellulosic biomass materials from
poplar, acacia, oak, and fir with different ionic liquids (ILs)
containing 1-alkyl-3-methyl-imidazolium cations and various anions
has been carried out. The dissolved cellulose from biomass was
precipitated by adding anti-solvents into the solution and vigorous
stirring. Commercial cellulases Celluclast 1.5L and Accelerase 1000
have been used for hydrolysis of untreated and pretreated
lignocellulosic biomass. Among the tested ILs, [Emim]COOCH3
showed the best efficiency, resulting in highest amount of liberated
reducing sugars. Pretreatment of lignocellulosic biomass using
glycerol-ionic liquids combined pretreatment and dilute acid-ionic
liquids combined pretreatment were evaluated and compared with
glycerol pretreatment, ionic liquids pretreatment and dilute acid
pretreatment.
Abstract: A large number of chemical, bio-chemical and pollution-control processes use heterogeneous fixed-bed reactors. The use of finite hollow cylindrical catalyst pellets can enhance conversion levels in such reactors. The absence of the pellet core can significantly lower the diffusional resistance associated with the solid phase. This leads to a better utilization of the catalytic material, which is reflected in the higher values for the effectiveness factor, leading ultimately to an enhanced conversion level in the reactor. It is however important to develop a rigorous heterogeneous model for the reactor incorporating the two-dimensional feature of the solid phase owing to the presence of the finite hollow cylindrical catalyst pellet. Presently, heterogeneous models reported in the literature invariably employ one-dimension solid phase models meant for spherical catalyst pellets. The objective of the paper is to present a rigorous model of the fixed-bed reactors containing finite hollow cylindrical catalyst pellets. The reaction kinetics considered here is the widely used Michaelis–Menten kinetics for the liquid-phase bio-chemical reactions. The reaction parameters used here are for the enzymatic degradation of urea. Results indicate that increasing the height to diameter ratio helps to improve the conversion level. On the other hand, decreasing the thickness is apparently not as effective. This could however be explained in terms of the higher void fraction of the bed that causes a smaller amount of the solid phase to be packed in the fixed-bed bio-chemical reactor.
Abstract: The trial in the city, located 170 kilometers from the
Iranian city of Ahvaz was Omidiyeh. The main factor in this project
includes 4 levels in control (without hormones), use of hormones in
the seed, vegetative and flowering stage respectively. And sub-plots
included 3 varieties of vetch in three levels, with local names, was the
jewel in the study of light and Auxin in the vegetative and
reproductive different times in different varieties of vetch was
investigated. This test has been taken in the plots in a randomized
complete block with four replications. In order to study the effects of
the hormone Auxin in the growth stages (seed, vegetative and
flowering) to control (no hormone Auxin) on three local varieties of
vetch, the essence of light and plant height, number of pods per plant,
seed number The pods, seeds per plant, grain weight, grain yield,
plant dry weight and protein content were measured. Among the
vetch varieties for plant height, number of pods per plant, a seed per
plant, grain weight, grain yield, and plant dry weight and protein
levels of 1 percent of plant and seed number per pod per plant at 5%
level of There was no significant difference. Interactions for grain
yield per plant, grain yield and protein levels of 1 percent and the
number of seeds per pod and seed weight are significant differences
in levels 5 and plant height and plant dry weight of the interaction
were INFLUENCE There was no significant difference in them.
Abstract: Resins are used in nuclear power plants for water
ultrapurification. Two approaches are considered in this work:
column experiments and simulations. A software called OPTIPUR
was developed, tested and used. The approach simulates the onedimensional
reactive transport in porous medium with convectivedispersive
transport between particles and diffusive transport within
the boundary layer around the particles. The transfer limitation in the
boundary layer is characterized by the mass transfer coefficient
(MTC). The influences on MTC were measured experimentally. The
variation of the inlet concentration does not influence the MTC; on
the contrary of the Darcy velocity which influences. This is consistent
with results obtained using the correlation of Dwivedi&Upadhyay.
With the MTC, knowing the number of exchange site and the relative
affinity, OPTIPUR can simulate the column outlet concentration
versus time. Then, the duration of use of resins can be predicted in
conditions of a binary exchange.
Abstract: Historical monuments as architectural heritage are,
economically and culturally, considered one of the key aspects for
modern communities. Cultural heritage represents a country-s
national identity and pride and maintains and enriches that country-s
culture. Therefore, conservation of the monuments remained from
our ancestors requires everybody-s serious and unremitting effort.
Conservation, renewal, restoration, and technical study of cultural
and historical matters are issues which have a special status among
various forms of art and science in the present century and this is due
to two reasons: firstly, progress of humankind in this century has
created a factor called environmental pollution which not only has
caused new destructive processes of cultural/historical monuments
but also has accelerated the previous destructive processes by several
times, and secondly, the rapid advance of various sciences, especially
chemistry, has lead to the contribution of new methods and materials
to this significant issue.
Abstract: Since the one-to-one word translator does not have the
facility to translate pragmatic aspects of Javanese, the parallel text
alignment model described uses a phrase pair combination. The
algorithm aligns the parallel text automatically from the beginning to
the end of each sentence. Even though the results of the phrase pair
combination outperform the previous algorithm, it is still inefficient.
Recording all possible combinations consume more space in the
database and time consuming. The original algorithm is modified by
applying the edit distance coefficient to improve the data-storage
efficiency. As a result, the data-storage consumption is 90% reduced
as well as its learning period (42s).
Abstract: Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.
Abstract: Existing literature ondesign reasoning seems to give
either one sided accounts on expert design behaviour based on
internal processing. In the same way ecological theoriesseem to
focus one sidedly on external elementsthat result in a lack of unifying
design cognition theory. Although current extended design cognition
studies acknowledge the intellectual interaction between internal and
external resources, there still seems to be insufficient understanding
of the complexities involved in such interactive processes. As
such,this paper proposes a novelmulti-directional model for design
researchers tomap the complex and dynamic conduct controlling
behaviour in which both the computational and ecological
perspectives are integrated in a vertical manner. A clear distinction
between identified intentional and emerging physical drivers, and
relationships between them during the early phases of experts- design
process, is demonstrated by presenting a case study in which the
model was employed.
Abstract: This paper looks into detailed investigation of
thermal-hydraulic characteristics of the flow field in a fuel rod
model, especially near the spacer. The area investigate represents a
source of information on the velocity flow field, vortex, and on the
amount of heat transfer into the coolant all of which are critical for
the design and improvement of the fuel rod in nuclear power plants.
The flow field investigation uses three-dimensional Computational
Fluid Dynamics (CFD) with the Reynolds stresses turbulence model
(RSM). The fuel rod model incorporates a vertical annular channel
where three different shapes of spacers are used; each spacer shape is
addressed individually. These spacers are mutually compared in
consideration of heat transfer capabilities between the coolant and
the fuel rod model. The results are complemented with the calculated
heat transfer coefficient in the location of the spacer and along the
stainless-steel pipe.