Abstract: Reliability is one of the most important quality attributes of software. Based on the approach of Reussner and the approach of Cheung, we proposed the reliability prediction model of component-based software architectures. Also, the value of the model is shown through the experimental evaluation on a web server system.
Abstract: The bit error rate (BER) performance for ultra-wide
band (UWB) indoor communication with impact of metallic furniture
is investigated. The impulse responses of different indoor
environments for any transmitter and receiver location are computed
by shooting and bouncing ray/image and inverse Fourier transform
techniques. By using the impulse responses of these multipath
channels, the BER performance for binary pulse amplitude
modulation (BPAM) impulse radio UWB communication system are
calculated. Numerical results have shown that the multi-path effect
by the metallic cabinets is an important factor for BER performance.
Also the outage probability for the UWB multipath environment with
metallic cabinets is more serious (about 18%) than with wooden
cabinets. Finally, it is worth noting that in these cases the present
work provides not only comparative information but also quantitative
information on the performance reduction.
Abstract: As in other countries from Central and Eastern Europe,
the economic restructuring occurred in the last decade of the
twentieth century affected the mining industry in Romania, an
oversize and heavily subsidized sector before 1989. After more than
a decade since the beginning of mining restructuring, an evaluation
of current social implications of the process it is required, together
with an efficiency analysis of the adaptation mechanisms developed
at governmental level. This article aims to provide an insight into
these issues through case studies conducted in the most important
coal basin of Romania, Petroşani Depression.
Abstract: In the current research, neuro-fuzzy model and regression model was developed to predict Material Removal Rate in Electrical Discharge Machining process for AISI D2 tool steel with copper electrode. Extensive experiments were conducted with various levels of discharge current, pulse duration and duty cycle. The experimental data are split into two sets, one for training and the other for validation of the model. The training data were used to develop the above models and the test data, which was not used earlier to develop these models were used for validation the models. Subsequently, the models are compared. It was found that the predicted and experimental results were in good agreement and the coefficients of correlation were found to be 0.999 and 0.974 for neuro fuzzy and regression model respectively
Abstract: The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to tumor progression. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.
Abstract: Soil washing process with a surfactant solution is a potential technology for the rapid removal of hydrophobic organic compound (HOC) from soil. However, large amount of washed water would be produced during operation and this should be treated effectively by proper methods. The soil washed water for complex contaminated site with HOC and heavy metals might contain high amount of pollutants such as HOC and heavy metals as well as used surfactant. The heavy metals in the soil washed water have toxic effects on microbial activities thus these should be removed from the washed water before proceeding to a biological waste-water treatment system. Moreover, the used surfactant solutions are necessary to be recovered for reducing the soil washing operation cost. In order to simultaneously remove the heavy metals and HOC from soil-washed water, activated carbon (AC) was used in the present study. In an anionic-nonionic surfactant mixed solution, the Cd(II) and phenanthrene (PHE) were effectively removed by adsorption on activated carbon. The removal efficiency for Cd(II) was increased from 0.027 mmol-Cd/g-AC to 0.142 mmol-Cd/g-AC as the mole ratio of SDS increased in the presence of PHE. The adsorptive capacity of PHE was also increased according to the SDS mole ratio due to the decrement of molar solubilization ratios (MSR) for PHE in an anionic-nonionic surfactant mixture. The simultaneous adsorption of HOC and cationic heavy metals using activated carbon could be a useful method for surfactant recovery and the reduction of heavy metal toxicity in a surfactant-enhanced soil washing process.
Abstract: In order to perform on-line measuring and detection
of PD signals, a total solution composing of an HFCT, A/D
converter and a complete software package is proposed. The
software package includes compensation of HFCT contribution,
filtering and noise reduction using wavelet transform and soft
calibration routines. The results have shown good performance and
high accuracy.
Abstract: A satured liquid is warmed until boiling in a parallelepipedic boiler. The heat is supplied in a liquid through the horizontal bottom of the boiler, the other walls being adiabatic. During the process of boiling, the liquid evaporates through its free surface by deforming it. This surface which subdivides the boiler into two regions occupied on both sides by the boiled liquid (broth) and its vapor which surmounts it. The broth occupying the region and its vapor the superior region. A two- fluids model is used to describe the dynamics of the broth, its vapor and their interface. In this model, the broth is treated as a monophasic fluid (homogeneous model) and form with its vapor adiphasic pseudo fluid (two-fluid model). Furthermore, the interface is treated as a zone of mixture characterized by superficial void fraction noted α* . The aim of this article is to describe the dynamics of the interface between the boiled fluid and its vapor within a boiler. The resolution of the problem allowed us to show the evolution of the broth and the level of the liquid.
Abstract: In a particular case of behavioural model reduction by ANNs, a validity domain shortening has been found. In mechanics, as in other domains, the notion of validity domain allows the engineer to choose a valid model for a particular analysis or simulation. In the study of mechanical behaviour for a cantilever beam (using linear and non-linear models), Multi-Layer Perceptron (MLP) Backpropagation (BP) networks have been applied as model reduction technique. This reduced model is constructed to be more efficient than the non-reduced model. Within a less extended domain, the ANN reduced model estimates correctly the non-linear response, with a lower computational cost. It has been found that the neural network model is not able to approximate the linear behaviour while it does approximate the non-linear behaviour very well. The details of the case are provided with an example of the cantilever beam behaviour modelling.
Abstract: This paper presents the experimental results of silicone rubber polymer insulators for 22 kV systems under salt water dip wheel test based on IEC 62217. Straight shed silicone rubber polymer insulators having leakage distance 685 mm were tested continuously 30,000 cycles. One test cycle includes 4 positions, energized, de-energized, salt water dip and deenergized, respectively. For one test cycle, each test specimen remains stationary for about 40 second in each position and takes 8 second for rotate to next position. By visual observation, sever surface erosion was observed on the trunk near the energized end of tested specimen. Puncture was observed on the upper shed near the energized end. In addition, decreasing in hydrophobicity and increasing in hardness were measured on tested specimen comparing with new specimen. Furthermore, chemical analysis by ATR-FTIR was conducted in order to elucidate the chemical change of tested specimens comparing with new specimen.
Abstract: The main aim of this research is to study the possible
use of recycled fine aggregate made from waste rubble wall to
substitute partially for the natural sand used in the production of
cement and sand bricks. The bricks specimens were prepared by
using 100% natural sand; they were then replaced by recycled fine
aggregate at 25, 50, 75, and 100% by weight of natural sand. A series
of tests was carried out to study the effect of using recycled aggregate
on the physical and mechanical properties of bricks, such as density,
drying shrinkage, water absorption characteristic, compressive and
flexural strength. Test results indicate that it is possible to
manufacture bricks containing recycled fine aggregate with good
characteristics that are similar in physical and mechanical properties
to those of bricks with natural aggregate, provided that the percentage
of recycled fine aggregates is limited up to 50-75%.
Abstract: This paper aims to discuss the influence of resistance
characteristic on the high conductive concrete considering the changes
of voltage and environment. The high conductive concrete with
appropriate proportion is produced to the press-electrode method. The
curve of resistivity with the changes of voltage and environment is
plotted and the changes of resistivity are explored.
Abstract: Basic objective of this study is to create a regression
analysis method that can estimate the length of a plastic hinge which
is an important design parameter, by making use of the outcomes of
(lateral load-lateral displacement hysteretic curves) the experimental
studies conducted for the reinforced square concrete columns. For
this aim, 170 different square reinforced concrete column tests results
have been collected from the existing literature. The parameters
which are thought affecting the plastic hinge length such as crosssection
properties, features of material used, axial loading level,
confinement of the column, longitudinal reinforcement bars in the
columns etc. have been obtained from these 170 different square
reinforced concrete column tests. In the study, when determining the
length of plastic hinge, using the experimental test results, a
regression analysis have been separately tested and compared with
each other. In addition, the outcome of mentioned methods on
determination of plastic hinge length of the reinforced concrete
columns has been compared to other methods available in the
literature.
Abstract: Population diversification phenomena becomes quite common in villages located in China’s developed coastal area. Based on the analysis of the traditional rural society and its landscape characteristics, and in consideration of diversified landscape requirements due to the population diversification, with dual ideas of heritage and innovation, methods for rural landscape design were explored by taking Duxuao Village in Zhejiang Province of China as an example.
Abstract: If price and quantity are the fundamental building
blocks of any theory of market interactions, the importance of trading
volume in understanding the behavior of financial markets is clear.
However, while many economic models of financial markets have
been developed to explain the behavior of prices -predictability,
variability, and information content- far less attention has been
devoted to explaining the behavior of trading volume. In this article,
we hope to expand our understanding of trading volume by
developing a new measure of herding behavior based on a cross
sectional dispersion of volumes betas. We apply our measure to the
Toronto stock exchange using monthly data from January 2000 to
December 2002. Our findings show that the herd phenomenon
consists of three essential components: stationary herding, intentional
herding and the feedback herding.
Abstract: In this paper, we propose an algorithm to compute
initial cluster centers for K-means clustering. Data in a cell is
partitioned using a cutting plane that divides cell in two smaller cells.
The plane is perpendicular to the data axis with the highest variance
and is designed to reduce the sum squared errors of the two cells as
much as possible, while at the same time keep the two cells far apart
as possible. Cells are partitioned one at a time until the number of
cells equals to the predefined number of clusters, K. The centers of
the K cells become the initial cluster centers for K-means. The
experimental results suggest that the proposed algorithm is effective,
converge to better clustering results than those of the random
initialization method. The research also indicated the proposed
algorithm would greatly improve the likelihood of every cluster
containing some data in it.
Abstract: A major requirement for Grid application developers is ensuring performance and scalability of their applications. Predicting the performance of an application demands understanding its specific features. This paper discusses performance modeling and prediction of multi-agent based simulation (MABS) applications on the Grid. An experiment conducted using a synthetic MABS workload explains the key features to be included in the performance model. The results obtained from the experiment show that the prediction model developed for the synthetic workload can be used as a guideline to understand to estimate the performance characteristics of real world simulation applications.
Abstract: The purposes of this paper are to (1) promote excellence in computer science by suggesting a cohesive innovative approach to fill well documented deficiencies in current computer science education, (2) justify (using the authors' and others anecdotal evidence from both the classroom and the real world) why this approach holds great potential to successfully eliminate the deficiencies, (3) invite other professionals to join the authors in proof of concept research. The authors' experiences, though anecdotal, strongly suggest that a new approach involving visual modeling technologies should allow computer science programs to retain a greater percentage of prospective and declared majors as students become more engaged learners, more successful problem-solvers, and better prepared as programmers. In addition, the graduates of such computer science programs will make greater contributions to the profession as skilled problem-solvers. Instead of wearily rememorizing code as they move to the next course, students will have the problem-solving skills to think and work in more sophisticated and creative ways.
Abstract: Using neural network we try to model the unknown function f for given input-output data pairs. The connection strength of each neuron is updated through learning. Repeated simulations of crisp neural network produce different values of weight factors that are directly affected by the change of different parameters. We propose the idea that for each neuron in the network, we can obtain quasi-fuzzy weight sets (QFWS) using repeated simulation of the crisp neural network. Such type of fuzzy weight functions may be applied where we have multivariate crisp input that needs to be adjusted after iterative learning, like claim amount distribution analysis. As real data is subjected to noise and uncertainty, therefore, QFWS may be helpful in the simplification of such complex problems. Secondly, these QFWS provide good initial solution for training of fuzzy neural networks with reduced computational complexity.
Abstract: The distribution, enrichment, and accumulation of zinc
(Zn) in the sediments of Kaohsiung Ocean Disposal Site (KODS),
Taiwan were investigated. Sediment samples from two outer disposal
site stations and nine disposed stations in the KODS were collected per
quarterly in 2009 and characterized for Zn, aluminum, organic matter,
and grain size. Results showed that the mean Zn concentrations varied
from 48 mg/kg to 456 mg/kg. Results from the enrichment factor (EF)
and geo-accumulation index (Igeo) analyses imply that the sediments
collected from the KODS can be characterized between moderate and
moderately severe degree enrichment and between none and none to
medium accumulation of Zn, respectively. However, results of
potential ecological risk index indicate that the sediment has low
ecological potential risk. The EF, Igeo, and Zn concentrations at the
disposed stations were slightly higher than those at outer disposal site.
This indicated that the disposed area centers may be subjected to the
disposal impaction of harbor dredged sediments.