Abstract: Organizational tendencies towards computer-based
information processing have been observed noticeably in the
third-world countries. Many enterprises are taking major initiatives
towards computerized working environment because of massive
benefits of computer-based information processing. However,
designing and developing information resource management software
for small and mid-size enterprises under budget costs and strict
deadline is always challenging for software engineers. Therefore, we
introduced an approach to design mid-size enterprise software by
using the Waterfall model, which is one of the SDLC (Software
Development Life Cycles), in a cost effective way. To fulfill research
objectives, in this study, we developed mid-sized enterprise software
named “BSK Management System” that assists enterprise software
clients with information resource management and perform complex
organizational tasks. Waterfall model phases have been applied to
ensure that all functions, user requirements, strategic goals, and
objectives are met. In addition, Rich Picture, Structured English, and
Data Dictionary have been implemented and investigated properly in
engineering manner. Furthermore, an assessment survey with 20
participants has been conducted to investigate the usability and
performance of the proposed software. The survey results indicated
that our system featured simple interfaces, easy operation and
maintenance, quick processing, and reliable and accurate transactions.
Abstract: ABC classification is widely used by managers for
inventory control. The classical ABC classification is based on Pareto
principle and according to the criterion of the annual use value only.
Single criterion classification is often insufficient for a closely
inventory control. Multi-criteria inventory classification models have
been proposed by researchers in order to consider other important
criteria. From these models, we will consider a specific model in
order to make a sensitive analysis on the composite score calculated
for each item. In fact, this score, based on a normalized average
between a good and a bad optimized index, can affect the ABC-item
classification. We will focus on items differently assigned to classes
and then propose a classification compromise.
Abstract: Image compression based on fractal coding is a lossy
compression method and normally used for gray level images range
and domain blocks in rectangular shape. Fractal based digital image
compression technique provide a large compression ratio and in this
paper, it is proposed using YUV colour space and the fractal theory
which is based on iterated transformation. Fractal geometry is mainly
applied in the current study towards colour image compression
coding. These colour images possesses correlations among the colour
components and hence high compression ratio can be achieved by
exploiting all these redundancies. The proposed method utilises the
self-similarity in the colour image as well as the cross-correlations
between them. Experimental results show that the greater
compression ratio can be achieved with large domain blocks but more
trade off in image quality is good to acceptable at less than 1 bit per
pixel.
Abstract: Behavioral aspects of experience such as will power
are rarely subjected to quantitative study owing to the numerous
complexities involved. Will is a phenomenon that has puzzled
humanity for a long time. It is a belief that will power of an individual
affects the success achieved by them in life. It is also thought that a
person endowed with great will power can overcome even the most
crippling setbacks in life while a person with a weak will cannot make
the most of life even the greatest assets. This study is an attempt
to subject the phenomena of will to the test of an artificial neural
network through a computational model. The claim being tested is
that will power of an individual largely determines success achieved
in life. It is proposed that data pertaining to success of individuals
be obtained from an experiment and the phenomenon of will be
incorporated into the model, through data generated recursively using
a relation between will and success characteristic to the model.
An artificial neural network trained using part of the data, could
subsequently be used to make predictions regarding data points in
the rest of the model. The procedure would be tried for different
models and the model where the networks predictions are found to
be in greatest agreement with the data would be selected; and used
for studying the relation between success and will.
Abstract: Breast cancer is considered as a substantial health
concern and practicing mammography screening [MS] is important in
minimizing its related morbidity. So it is essential to have a better
understanding of breast cancer screening behaviors of women and
factors that influence utilization of them. The aim of this study is to
identify the factors that are linked to MS behaviors among the
Egyptian women. A cross-sectional descriptive design was carried
out to provide a snapshot of the factors that are linked to MS
behaviors. A convenience sample of 311 women was utilized and all
eligible participants admitted to the Women Imaging Unit who are 40
years of age or above, coming for mammography assessment, not
pregnant or breast feeding and who accepted to participate in the
study were included. A structured questionnaire was developed by
the researchers and contains three parts; Socio-demographic data;
Motivating factors associated with MS; and association between MS
and model of behavior change. The analyzed data indicated that most
of the participated women (66.6%) belonged to the age group of 40-
49.A high proportion of participants (58.1%) of group having
previous MS influenced by their neighbors to practice MS, whereas
32.7 % in group not having previous MS were influenced by family
members which indicated significant differences (P
Abstract: This paper proposes techniques like MT CMOS,
POWER GATING, DUAL STACK, GALEOR and LECTOR to
reduce the leakage power. A Full Adder has been designed using
these techniques and power dissipation is calculated and is compared
with general CMOS logic of Full Adder.
Simulation results show the validity of the proposed techniques is
effective to save power dissipation and to increase the speed of
operation of the circuits to a large extent.
Abstract: The exponential growth of social media arouses much
attention on public opinion information. The online forums, blogs,
micro blogs are proving to be extremely valuable resources and are
having bulk volume of information. However, most of the social
media data is unstructured and semi structured form. So that it is
more difficult to decipher automatically. Therefore, it is very much
essential to understand and analyze those data for making a right
decision. The online forums hotspot detection is a promising research
field in the web mining and it guides to motivate the user to take right
decision in right time. The proposed system consist of a novel
approach to detect a hotspot forum for any given time period. It uses
aging theory to find the hot terms and E-K-means for detecting the
hotspot forum. Experimental results demonstrate that the proposed
approach outperforms k-means for detecting the hotspot forums with
the improved accuracy.
Abstract: The authors propose the identification, analysis and
prognosis of the quantitative and qualitative evolution of the elderly
population in the functional urban areas. The present paper takes into
account the analysis of some representative indicators (the weight of
the elderly population, ageing index, dynamic index of economic
ageing of productive population etc.) and the elaboration of an
integrated indicator that would help differentiate the population
ageing forms in the 48 functional urban areas that were defined based
on demographic and social-economic criteria for all large and
medium cities in Romania.
Abstract: This paper proposes the application of the Smart
Security Concept in the East Mediterranean. Smart Security aims to
secure critical infrastructure, such as hydrocarbon platforms, against
asymmetrical threats. The concept is based on Anti Asymmetrical
Area Denial (A3D) which necessitates limiting freedom of action of
maritime terrorists and piracy by founding safe and secure maritime
areas through sea lines of communication using short range
capabilities.
Abstract: DC motors have been widely used in the past
centuries which are proudly known as the workhorse of industrial
systems until the invention of the AC induction motors which makes
a huge revolution in industries. Since then, the use of DC machines
has been decreased due to enormous factors such as reliability,
robustness and complexity but it lost its fame due to the losses. In this
paper a new methodology is proposed to construct a DC motor
through the simulation in LabVIEW to get an idea about its real time
performances, if a change in parameter might have bigger
improvement in losses and reliability.
Abstract: Proposed paper dealt with the modelling and analysis of induction motor based on the mathematical expression using the graphical programming environment of Laboratory Virtual Instrument Engineering Workbench (LabVIEW). Induction motor modelling with the mathematical expression enables the motor to be simulated with the various required parameters. Owing to the invention of variable speed drives study about the induction motor characteristics became complex. In this simulation motor internal parameter such as stator resistance and reactance, rotor resistance and reactance, phase voltage, frequency and losses will be given as input. By varying the speed of motor corresponding parameters can be obtained they are input power, output power, efficiency, torque induced, slip and current.
Abstract: We proposed a Hyperbolic Gompertz Growth Model
(HGGM), which was developed by introducing a shape parameter
(allometric). This was achieved by convoluting hyperbolic sine
function on the intrinsic rate of growth in the classical gompertz
growth equation. The resulting integral solution obtained
deterministically was reprogrammed into a statistical model and used
in modeling the height and diameter of Pines (Pinus caribaea). Its
ability in model prediction was compared with the classical gompertz
growth model, an approach which mimicked the natural variability of
height/diameter increment with respect to age and therefore provides
a more realistic height/diameter predictions using goodness of fit
tests and model selection criteria. The Kolmogorov Smirnov test and
Shapiro-Wilk test was also used to test the compliance of the error
term to normality assumptions while the independence of the error
term was confirmed using the runs test. The mean function of top
height/Dbh over age using the two models under study predicted
closely the observed values of top height/Dbh in the hyperbolic
gompertz growth models better than the source model (classical
gompertz growth model) while the results of R2, Adj. R2, MSE and
AIC confirmed the predictive power of the Hyperbolic Gompertz
growth models over its source model.
Abstract: Fly ash (FA) thanks to the significant presence of SiO2
and Al2O3 as the main components is a potential raw material for
geopolymers production. Mechanical activation is a method for
improving FA reactivity and also the porosity of final mixture; those
parameters can be analysed through sorption properties. They have
direct impact on the durability of fly ash based geopolymer mortars.
In the paper, effect of FA fineness on sorption properties of
geopolymers based on sodium silicate, as well as relationship
between fly ash fineness and apparent density, compressive and
flexural strength of geopolymers are presented. The best results in the
evaluated area reached the sample H1, which contents the highest
portion of particle under 20μm (100% of GFA). The interdependence
of individual tested properties was confirmed for geopolymer
mixtures corresponding to those in the cement based mixtures: higher
is portion of fine particles < 20μm, higher is strength, density and
lower are sorption properties. The compressive strength as well as
sorption parameters of the geopolymer can be reasonably controlled
by grinding process and also ensured by the higher share of fine
particle (to 20μm) in total mass of the material.
Abstract: The purpose of the paper is to examine the most
critical and important factor which will affect the implementation of
Total Quality Management (TQM) in the construction industry in the
United Arab Emirates. It also examines the most effected Project
outcome from implementing TQM. A framework was also proposed
depending on the literature studies. The method used in this paper is a
quantitative study. A survey with a sample of 60 respondents was
created and distributed in a construction company in Abu Dhabi,
which includes 15 questions to examine the most critical factor that
will affect the implementation of TQM in addition to the most
effected project outcome from implementing TQM. The survey
showed that management commitment is the most important factor in
implementing TQM in a construction company. Also it showed that
Project cost is most effected outcome from the implementation of
TQM.
Management commitment is very important for implementing
TQM in any company. If the management loose interest in quality
then everyone in the organization will do so. The success of TQM
will depend mostly on the top of the pyramid. Also cost is reduced
and money is saved when the project team implement TQM. While if
no quality measures are present within the team, the project will
suffer a commercial failure.
Based on literature, more factors can be examined and added to
the model. In addition, more construction companies could be
surveyed in order to obtain more accurate results. Also this study
could be conducted outside the United Arab Emirates for further
enchantment.
Abstract: Grid is an environment with millions of resources
which are dynamic and heterogeneous in nature. A computational
grid is one in which the resources are computing nodes and is meant
for applications that involves larger computations. A scheduling
algorithm is said to be efficient if and only if it performs better
resource allocation even in case of resource failure. Resource
allocation is a tedious issue since it has to consider several
requirements such as system load, processing cost and time, user’s
deadline and resource failure. This work attempts in designing a
resource allocation algorithm which is cost-effective and also targets
at load balancing, fault tolerance and user satisfaction by considering
the above requirements. The proposed Budget Constrained Load
Balancing Fault Tolerant algorithm with user satisfaction (BLBFT)
reduces the schedule makespan, schedule cost and task failure rate
and improves resource utilization. Evaluation of the proposed
BLBFT algorithm is done using Gridsim toolkit and the results are
compared with the algorithms which separately concentrates on all
these factors. The comparison results ensure that the proposed
algorithm works better than its counterparts.
Abstract: The effects of the pumping wavelength and their power
on the gain flattening of a fiber Raman amplifier (FRA) are
investigated. The multi-wavelength pumping scheme is utilized to
achieve gain flatness in FRA. It is proposed that gain flatness
becomes better with increase in number of pumping wavelengths
applied. We have achieved flat gain with 0.27 dB fluctuation in a
spectral range of 1475-1600 nm for a Raman fiber length of 10 km by
using six pumps with wavelengths with in the 1385-1495 nm interval.
The effect of multi-wavelength pumping scheme on gain saturation in
FRA is also studied. It is proposed that gain saturation condition gets
improved by using this scheme and this scheme is more useful for
higher spans of Raman fiber length.
Abstract: Pipa is one of the most important Chinese traditional
plucked instruments, but its directivity has never been measured
systematically. In western, directivity of loudness for western
instruments is deeply researched through analysis of sound pressure
level, whereas the directivity of timbre is seldom studied. In this paper,
a new method for directivity of timbre was proposed, and horizontal
directivity patterns of loudness and timbre of Pipa were measured.
Directivity of Pipa radiation was measured in an anechoic room. The
sound of Pipa played by a musician was recorded simultaneously by
32 microphones with Pipa in the center. The measuring results were
examined through listening test. According to the measurement of
Pipa directivity radiation, we put forward the best localization of Pipa
in the Chinese traditional orchestra and the optimal recording region.
Abstract: In this paper, we will analyze the relationship between the neo-liberal concept of property rights and redistribution policy. This issue is back in the focus of interest due to the crisis 2008. The crisis has reaffirmed the influence of the state on the free-market processes. The interference of the state with property relations reopened a classical question: is it legitimate to redistribute resources of a man in favor of another man with taxes? The dominant view is that the neoliberal philosophy of natural rights is incompatible with redistributive measures. In principle, this view can be accepted. However, when we look into the details of the theory of natural rights proposed by some coryphaei of neoliberal philosophy, such as Hayek, Nozick, Buchanan and Rothbard, we can see that it is not such an unequivocal view.
Abstract: Image enhancement is a challenging issue in many applications. In the last two decades, there are various filters developed. This paper proposes a novel method which removes Gaussian noise from the gray scale images. The proposed technique is compared with Enhanced Fuzzy Peer Group Filter (EFPGF) for various noise levels. Experimental results proved that the proposed filter achieves better Peak-Signal-to-Noise-Ratio PSNR than the existing techniques. The proposed technique achieves 1.736dB gain in PSNR than the EFPGF technique.
Abstract: Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FPgrowth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.