Abstract: Building condition assessment is a critical activity in Malaysia-s Comprehensive Asset Management Model. It is closely related to building performance that impact user-s life and decision making. This study focuses on public primary school, one of the most valuable assets for the country. The assessment was carried out based on CSP1 Matrix in Kuching Division of Sarawak, Malaysia. Based on the matrix used, three main criteria of the buildings has successfully evaluate: the number of defects; schools rating; and total schools rating. The analysis carried out on 24 schools found that the overall 4, 725 defects has been identified. Meanwhile, the overall score obtained was 45, 868 and the overall rating is 9.71, which is at the fair condition. This result has been associated with building age to evaluate its impacts on school buildings condition. The findings proved that building condition is closely related to building age and its support the theory that 'the ageing building has more defect than the new one'.
Abstract: This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions- affectation of each considered class on the other hand. Satellite image exploitation requires the use of different approaches, especially those founded on the unsupervised statistical segmentation principle. Such approaches necessitate definition of several parameters like image class number, class variables- estimation and generalised mixture distributions. Use of statistical images- attributes assured convincing and promoting results under the condition of having an optimal initialisation step with appropriated statistical distributions- affectation. Pearson system associated with a k-means clustering algorithm and Stochastic Expectation-Maximization 'SEM' algorithm could be adapted to such problem. For each image-s class, Pearson system attributes one distribution type according to different parameters and especially the Skewness 'β1' and the kurtosis 'β2'. The different adapted algorithms, K-Means clustering algorithm, SEM algorithm and Pearson system algorithm, are then applied to satellite image segmentation problem. Efficiency of those combined algorithms was firstly validated with the Mean Quadratic Error 'MQE' evaluation, and secondly with visual inspection along several comparisons of these unsupervised images- segmentation.
Abstract: In this paper we introduce some subspaces of fuzzy entire sequence space. Some general properties of these sequence spaces are discussed. Also some inclusion relation involving the spaces are obtained. Mathematics Subject Classification: 40A05, 40D25.
Abstract: In this paper, we have presented a new multivariate fuzzy time series forecasting method. This method assumes mfactors with one main factor of interest. History of past three years is used for making new forecasts. This new method is applied in forecasting total number of car accidents in Belgium using four secondary factors. We also make comparison of our proposed method with existing methods of fuzzy time series forecasting. Experimentally, it is shown that our proposed method perform better than existing fuzzy time series forecasting methods. Practically, actuaries are interested in analysis of the patterns of causalities in road accidents. Thus using fuzzy time series, actuaries can define fuzzy premium and fuzzy underwriting of car insurance and life insurance for car insurance. National Institute of Statistics, Belgium provides region of risk classification for each road. Thus using this risk classification, we can predict premium rate and underwriting of insurance policy holders.
Abstract: We used mathematical model to study the
transmission of dengue disease. The model is developed in which
the human population is separated into two populations, pregnant and
non-pregnant humans. The dynamical analysis method is used for
analyzing this modified model. Two equilibrium states are found and
the conditions for stability of theses two equilibrium states are
established. Numerical results are shown for each equilibrium state.
The basic reproduction numbers are found and they are compared by
using numerical simulations.
Abstract: Measuring the effect of perinatal lead exposure on learning ability of offspring is considered as a sensitive and selective index for providing an early marker for central nervous system damage produced by this toxic metal. A total of 35 Sprague-Dawley adult rats were used to investigate the effect of lead acetate toxicity on behavioral patterns of adult female rats and learning ability of offspring. Rats were allotted into 4 groups, group one received 1g/l lead acetate (n=10), group two received 1.5g/l lead acetate (n=10), group three received 2g/l lead acetate in drinking water (n=10) and control group did not receive lead acetate (n=5) from 8th day of pregnancy till weaning of pups.
The obtained results revealed a dose dependent increase in the feeding time, drinking frequency, licking frequency, scratching frequency, licking litters, nest building and retrieving frequencies, while standing time increased significantly in rats treated with 1.5g/l lead acetate than other treated groups and control, on contrary lying time decreased gradually in a dose dependent manner. Moreover, movement activities were higher in rats treated with 1g/l lead acetate than other treated groups and control. Furthermore, time spent in closed arms was significantly lower in rats given 2g/l lead acetate than other treated groups, while, they spent significantly much time spent in open arms than other treated groups which could be attributed to occurrence of adaptation. Furthermore, number of entries in open arms was dose dependent. However, the ratio between open/closed arms revealed a significant decrease in rats treated with 2g/l lead acetate than control group.
Abstract: Adsorption of proteins onto a solid surface is believed to be the initial and controlling step in biofouling. A better knowledge of the fouling process can be obtained by controlling the formation of the first protein layer at a solid surface. A number of methods have been investigated to inhibit adsorption of proteins. In this study, the adsorption kinetics of
Abstract: The migration of a deformable drop in simple shear
flow at finite Reynolds numbers is investigated numerically by
solving the full Navier-Stokes equations using a finite
difference/front tracking method. The objectives of this study are to
examine the effectiveness of the present approach to predict the
migration of a drop in a shear flow and to investigate the behavior of
the drop migration with different drop sizes and non-unity viscosity
ratios. It is shown that the drop deformation depends strongly on the
capillary number, so that; the proper non-dimensional number for the
interfacial tension is the capillary number. The rate of migration
increased with increasing the drop radius. In other words, the
required time for drop migration to the centreline decreases. As the
viscosity ratio increases, the drop rotates more slowly and the
lubrication force becomes stronger. The increased lubrication force
makes it easier for the drop to migrate to the centre of the channel.
The migration velocity of the drop vanishes as the drop reaches the
centreline under viscosity ratio of one and non-unity viscosity ratios.
To validate the present calculations, some typical results are
compared with available experimental and theoretical data.
Abstract: Dissolved gas analysis has been accepted as a sensitive, informative and reliable technique for incipient faults detection in power transformers and is widely used. In the last few years this method, which has been recommended by IEEE Power & Energy society, has been applied for fault detection in load tap changers. Regarding the critical role of load tap changers in electrical network and essential of catastrophic failures prevention, it is necessary to choose "condition based preventative maintenance strategy" which leads to reduction in costs, the number of unnecessary visits as well as the probability of interruptions and also increment in equipment reliability. In current work, considering the condition based preventative maintenance strategy, condition assessment of an Elin tap changer was carried out using dissolved gas analysis.
Abstract: This work is devoted to the calculation of the
undulatory parameters and the study of the influence of te number
parallel path of a winding on overvoltage compared to the frame and
between turns (sections) in a multiturn random winding of an
asynchronous motors supplied with PWM- converters.
Abstract: The technique of k-anonymization has been proposed to obfuscate private data through associating it with at least k identities. This paper investigates the basic tabular structures that
underline the notion of k-anonymization using cell suppression.
These structures are studied under idealized conditions to identify the
essential features of the k-anonymization notion. We optimize data kanonymization
through requiring a minimum number of anonymized
values that are balanced over all columns and rows. We study the
relationship between the sizes of the anonymized tables, the value k, and the number of attributes. This study has a theoretical value through contributing to develop a mathematical foundation of the kanonymization
concept. Its practical significance is still to be
investigated.
Abstract: The medical data statistical analysis often requires the
using of some special techniques, because of the particularities of
these data. The principal components analysis and the data clustering
are two statistical methods for data mining very useful in the medical
field, the first one as a method to decrease the number of studied
parameters, and the second one as a method to analyze the
connections between diagnosis and the data about the patient-s
condition. In this paper we investigate the implications obtained from
a specific data analysis technique: the data clustering preceded by a
selection of the most relevant parameters, made using the principal
components analysis. Our assumption was that, using the principal
components analysis before data clustering - in order to select and to
classify only the most relevant parameters – the accuracy of
clustering is improved, but the practical results showed the opposite
fact: the clustering accuracy decreases, with a percentage
approximately equal with the percentage of information loss reported
by the principal components analysis.
Abstract: This work concerns on experimentally investigation
of surfactant flooding in fractured porous media. In this study a series
of water and surfactant injection processes were performed on
micromodels initially saturated with a heavy crude oil. Eight
fractured glass micromodels were used to illustrate effects of
surfactant types and concentrations on oil recovery efficiency in
presence of fractures with different properties i.e. fracture
orientation, length and number of fractures. Two different
surfactants with different concentrations were tested. The results
showed that surfactant flooding would be more efficient by using
SDS surfactant aqueous solution and also by locating injection well
in a proper position respect to fracture properties. This study
demonstrates different physical and chemical conditions that affect
the efficiency of this method of enhanced oil recovery.
Abstract: This paper proposed classification models that would
be used as a proxy for hard disk drive (HDD) functional test equitant
which required approximately more than two weeks to perform the
HDD status classification in either “Pass" or “Fail". These models
were constructed by using committee network which consisted of a
number of single neural networks. This paper also included the
method to solve the problem of sparseness data in failed part, which
was called “enforce learning method". Our results reveal that the
constructed classification models with the proposed method could
perform well in the sparse data conditions and thus the models,
which used a few seconds for HDD classification, could be used to
substitute the HDD functional tests.
Abstract: A trustworthy voting process in democratic is
important that each vote is recorded with accuracy and impartiality.
The accuracy and impartiality are tallied in high rate with biometric
system. One of the sign is a fingerprint. Fingerprint recognition is
still a challenging problem, because of the distortions among the
different impression of the same finger. Because of the trustworthy of
biometric voting technologies, it may give a great effect on numbers
of voter-s participation and outcomes of the democratic process.
Hence in this study, the authors are interested in designing and
analyzing the Electronic Voting System and the participation of the
users. The system is based on the fingerprint minutiae with the
addition of person ID number. This is in order to enhance the
accuracy and speed of the voting process. The new design is analyzed
by conducting pilot election among a class of students for selecting
their representative.
Abstract: Given bipartite graphs H1 and H2, the bipartite Ramsey number b(H1;H2) is the smallest integer b such that any subgraph G of the complete bipartite graph Kb,b, either G contains a copy of H1 or its complement relative to Kb,b contains a copy of H2. It is known that b(K2,2;K2,2) = 5, b(K2,3;K2,3) = 9, b(K2,4;K2,4) = 14 and b(K3,3;K3,3) = 17. In this paper we study the case that both H1 and H2 are even cycles, prove that b(C2m;C2n) ≥ m + n - 1 for m = n, and b(C2m;C6) = m + 2 for m ≥ 4.
Abstract: This paper deals with infinite time horizon fuzzy Economic Order Quantity (EOQ) models for deteriorating items with
stock dependent demand rate and nonlinear holding costs by taking deterioration rate θ0 as a triangular fuzzy number (θ0 −δ 1, θ0, θ0 +δ 2), where 1 2 0 0
Abstract: Increasing attention has been given in academia to the concept of corporate social responsibility. Also, the number of companies that undertake social responsibility initiatives has been boosting day by day since behaving in a socially responsible manner brings a lot to the companies. Literature provides various benefits of social responsibility and under which situations these benefits could be realized. However, most of these studies focus on one aspect of the consequences of behaving in a socially responsible manner and there is no study that unifies the conditions that a company should fulfill to make customers prefer its brand. This study aims to fill this gap. More specifically, the purpose of this study is to identify the conditions that a socially responsible company should fulfill in order to attract customers. To this end, a scale is developed and its reliability and validity is assessed through the method of Multitrait- Multimethod Matrix.
Abstract: In this paper effects of inclination angle on natural
convection flow in an open cavity has been analyzed with Lattice
Boltzmann Method (LBM).The angle of inclination varied from θ= -
45° to 45° with 15° intervals. Study has been conducted for Rayleigh
numbers (Ra) 104 to 106. The comparisons show that the average
Nusselt number increases with growth of Rayleigh number and the
average Nusselt number increase as inclination angles increases at
Ra=104.At Ra=105 and Ra=106 the average Nusselt number enhance
as inclination angels varied from θ= -45° to θ= 0° and decrease as
inclination angels increase in θ= 0° to θ= 45°.
Abstract: Diesel Engines emit complex mixtures of inorganic
and organic compounds in the form of both solid and vapour phase
particles. Most of the particulates released are ultrafine nanoparticles
which are detrimental to human health and can easily enter the body
by respiration. The emissions standards on particulate matter release
from diesel engines are constantly upgraded within the European
Union and with future regulations based on the particles numbers
released instead of merely mass, the need for effective aftertreatment
devices will increase. Standard particulate filters in the form of wall
flow filters can have problems with high soot accumulation,
producing a large exhaust backpressure. A potential solution would
be to combine the standard filter with a flow through filter to reduce
the load on the wall flow filter. In this paper soot particle trapping has
been simulated in different continuous flow filters of monolithic
structure including the use of promoters, at laminar flow conditions.
An Euler Lagrange model, the discrete phase model in Ansys used
with user defined functions for forces acting on particles. A method
to quickly screen trapping of 5 nm and 10 nm particles in different
catalysts designs with tracers was also developed.
Simulations of square duct monoliths with promoters show that the
strength of the vortices produced are not enough to give a high
amount of particle deposition on the catalyst walls. The smallest
particles in the simulations, 5 and 10 nm particles were trapped to a
higher extent, than larger particles up to 1000 nm, in all studied
geometries with the predominant deposition mechanism being
Brownian diffusion. The comparison of the different filters designed
with a wall flow filter does show that the options for altering a design
of a flow through filter, without imposing a too large pressure drop
penalty are good.