Abstract: This paper introduces new algorithms (Fuzzy relative
of the CLARANS algorithm FCLARANS and Fuzzy c Medoids
based on randomized search FCMRANS) for fuzzy clustering of
relational data. Unlike existing fuzzy c-medoids algorithm (FCMdd)
in which the within cluster dissimilarity of each cluster is minimized
in each iteration by recomputing new medoids given current
memberships, FCLARANS minimizes the same objective function
minimized by FCMdd by changing current medoids in such away
that that the sum of the within cluster dissimilarities is minimized.
Computing new medoids may be effected by noise because outliers
may join the computation of medoids while the choice of medoids in
FCLARANS is dictated by the location of a predominant fraction of
points inside a cluster and, therefore, it is less sensitive to the
presence of outliers. In FCMRANS the step of computing new
medoids in FCMdd is modified to be based on randomized search.
Furthermore, a new initialization procedure is developed that add
randomness to the initialization procedure used with FCMdd. Both
FCLARANS and FCMRANS are compared with the robust and
linearized version of fuzzy c-medoids (RFCMdd). Experimental
results with different samples of the Reuter-21578, Newsgroups
(20NG) and generated datasets with noise show that FCLARANS is
more robust than both RFCMdd and FCMRANS. Finally, both
FCMRANS and FCLARANS are more efficient and their outputs
are almost the same as that of RFCMdd in terms of classification
rate.
Abstract: Dengue fever is an important human arboviral disease. Outbreaks are now reported quite often from many parts of the world. The number of cases involving pregnant women and infant cases are increasing every year. The illness is often severe and complications may occur. Deaths often occur because of the difficulties in early diagnosis and in the improper management of the diseases. Dengue antibodies from pregnant women are passed on to infants and this protects the infants from dengue infections. Antibodies from the mother are transferred to the fetus when it is still in the womb. In this study, we formulate a mathematical model to describe the transmission of this disease in pregnant women. The model is formulated by dividing the human population into pregnant women and non-pregnant human (men and non-pregnant women). Each class is subdivided into susceptible (S), infectious (I) and recovered (R) subclasses. We apply standard dynamical analysis to our model. Conditions for the local stability of the equilibrium points are given. The numerical simulations are shown. The bifurcation diagrams of our model are discussed. The control of this disease in pregnant women is discussed in terms of the threshold conditions.
Abstract: Motivated by Berman et al. [Sign patterns that allow eventual positivity, ELA, 19(2010): 108-120], we concentrate on the potential eventual positivity of irreducible tridiagonal sign patterns. The minimal potential eventual positivity of irreducible tridiagonal sign patterns of order less than six is established, and all the minimal potentially eventually positive tridiagonal sign patterns of order · 5 are identified. Our results indicate that if an irreducible tridiagonal sign pattern of order less than six A is minimal potentially eventually positive, then A requires the eventual positivity.
Abstract: Concerning the inpatient care the present situation is
characterized by intense charges of medical technology into the
clinical daily routine and an ever stronger integration of special
techniques into the clinical workflow. Medical technology is by now
an integral part of health care according to consisting general
accepted standards. Purchase and operation thereby represent an
important economic position and both are subject of everyday
optimisation attempts. For this purpose by now exists a huge number
of tools which conduce more likely to a complexness of the problem
by a comprehensive implementation. In this paper the advantages of
an integrative information-workflow on the life-cycle-management in
the region of medical technology are shown.
Abstract: In this article, a method has been offered to classify
normal and defective tiles using wavelet transform and artificial
neural networks. The proposed algorithm calculates max and min
medians as well as the standard deviation and average of detail
images obtained from wavelet filters, then comes by feature vectors
and attempts to classify the given tile using a Perceptron neural
network with a single hidden layer. In this study along with the
proposal of using median of optimum points as the basic feature and
its comparison with the rest of the statistical features in the wavelet
field, the relational advantages of Haar wavelet is investigated. This
method has been experimented on a number of various tile designs
and in average, it has been valid for over 90% of the cases. Amongst
the other advantages, high speed and low calculating load are
prominent.
Abstract: Fuzzy logic control (FLC) systems have been tested in
many technical and industrial applications as a useful modeling tool
that can handle the uncertainties and nonlinearities of modern control
systems. The main drawback of the FLC methodologies in the
industrial environment is challenging for selecting the number of
optimum tuning parameters.
In this paper, a method has been proposed for finding the optimum
membership functions of a fuzzy system using particle swarm
optimization (PSO) algorithm. A synthetic algorithm combined from
fuzzy logic control and PSO algorithm is used to design a controller
for a continuous stirred tank reactor (CSTR) with the aim of
achieving the accurate and acceptable desired results. To exhibit the
effectiveness of proposed algorithm, it is used to optimize the
Gaussian membership functions of the fuzzy model of a nonlinear
CSTR system as a case study. It is clearly proved that the optimized
membership functions (MFs) provided better performance than a
fuzzy model for the same system, when the MFs were heuristically
defined.
Abstract: This study investigated the number of Aedes larvae,
the key breeding sites of Aedes sp., and the relationship between
climatic factors and the incidence of DHF in Samui Islands. We
conducted our questionnaire and larval surveys from randomly
selected 105 households in Samui Islands in July-September 2006.
Pearson-s correlation coefficient was used to explore the primary
association between the DHF incidence and all climatic factors.
Multiple stepwise regression technique was then used to fit the
statistical model. The results showed that the positive indoor
containers were small jars, cement tanks, and plastic tanks. The
positive outdoor containers were small jars, cement tanks, plastic
tanks, used cans, tires, plastic bottles, discarded objects, pot saucers,
plant pots, and areca husks. All Ae. albopictus larval indices (i.e., CI,
HI, and BI) were higher than Ae. aegypti larval indices in this area.
These larval indices were higher than WHO standard. This indicated
a high risk of DHF transmission at Samui Islands. The multiple
stepwise regression model was y = –288.80 + 11.024xmean temp. The
mean temperature was positively associated with the DHF incidence
in this area.
Abstract: The study explored the question of who am I? As a (re)construction of cultural identity by delving into globalization, communication, and social change in Malta during a historical moment when Malta became a European Union Member State. Three objectives guided this qualitative study. Firstly the study reviewed European Union (EU) policies that regulate broadcasting and their implementation in Member States, whilst meeting the challenges of globalization and new media technology. Secondly the research investigated the changes of the media landscape via organizational structures, programs and television (TV) content. Finally the study explored the impact of these transformations taking place in the way Maltese live as they (re)construct their cultural identity. Despite the choices available to the Maltese audience, old local traditions and new foreign customs coexist as informants continue to (re)construct their cultural identity and define who they are.
Abstract: Decentralized eco-sanitation system is a promising and sustainable mode comparing to the century-old centralized conventional sanitation system. The decentralized concept relies on an environmentally and economically sound management of water, nutrient and energy fluxes. Source-separation systems for urban waste management collect different solid waste and wastewater streams separately to facilitate the recovery of valuable resources from wastewater (energy, nutrients). A resource recovery centre constituted for 20,000 people will act as the functional unit for the treatment of urban waste of a high-density population community, like Singapore. The decentralized system includes urine treatment, faeces and food waste co-digestion, and horticultural waste and organic fraction of municipal solid waste treatment in composting plants. A design model is developed to estimate the input and output in terms of materials and energy. The inputs of urine (yellow water, YW) and faeces (brown water, BW) are calculated by considering the daily mean production of urine and faeces by humans and the water consumption of no-mix vacuum toilet (0.2 and 1 L flushing water for urine and faeces, respectively). The food waste (FW) production is estimated to be 150 g wet weight/person/day. The YW is collected and discharged by gravity into tank. It was found that two days are required for urine hydrolysis and struvite precipitation. The maximum nitrogen (N) and phosphorus (P) recovery are 150-266 kg/day and 20-70 kg/day, respectively. In contrast, BW and FW are mixed for co-digestion in a thermophilic acidification tank and later a decentralized/centralized methanogenic reactor is used for biogas production. It is determined that 6.16-15.67 m3/h methane is produced which is equivalent to 0.07-0.19 kWh/ca/day. The digestion residues are treated with horticultural waste and organic fraction of municipal waste in co-composting plants.
Abstract: This paper provides an analysis of corporate income
tax (CIT) incentives in the Western Balkan countries: Slovenia,
Croatia, Serbia, Montenegro, Macedonia and Albania. Western
Balkan countries, as other transition and developing countries, use
large number of the corporate income tax incentives (CIT) to attract
foreign investments and to stimulate economic activity. The main
goal of this paper is to investigate how often these countries use CIT
incentives and provide review of existing tax incentives in Western
Balkan countries. Paper will focus on reduced CIT rates, tax
holidays, and other investment incentives which imply incentives
like accelerated depreciation, tax allowances and tax credits.
Abstract: This paper presents a generalized formulation for the
problem of buckling optimization of anisotropic, radially graded,
thin-walled, long cylinders subject to external hydrostatic pressure.
The main structure to be analyzed is built of multi-angle fibrous
laminated composite lay-ups having different volume fractions of the
constituent materials within the individual plies. This yield to a
piecewise grading of the material in the radial direction; that is the
physical and mechanical properties of the composite material are
allowed to vary radially. The objective function is measured by
maximizing the critical buckling pressure while preserving the total
structural mass at a constant value equals to that of a baseline
reference design. In the selection of the significant optimization
variables, the fiber volume fractions adjoin the standard design
variables including fiber orientation angles and ply thicknesses. The
mathematical formulation employs the classical lamination theory,
where an analytical solution that accounts for the effective axial and
flexural stiffness separately as well as the inclusion of the coupling
stiffness terms is presented. The proposed model deals with
dimensionless quantities in order to be valid for thin shells having
arbitrary thickness-to-radius ratios. The critical buckling pressure
level curves augmented with the mass equality constraint are given
for several types of cylinders showing the functional dependence of
the constrained objective function on the selected design variables. It
was shown that material grading can have significant contribution to
the whole optimization process in achieving the required structural
designs with enhanced stability limits.
Abstract: This paper presents a new approach for image
segmentation by applying Pillar-Kmeans algorithm. This
segmentation process includes a new mechanism for clustering the
elements of high-resolution images in order to improve precision and
reduce computation time. The system applies K-means clustering to
the image segmentation after optimized by Pillar Algorithm. The
Pillar algorithm considers the pillars- placement which should be
located as far as possible from each other to withstand against the
pressure distribution of a roof, as identical to the number of centroids
amongst the data distribution. This algorithm is able to optimize the
K-means clustering for image segmentation in aspects of precision
and computation time. It designates the initial centroids- positions
by calculating the accumulated distance metric between each data
point and all previous centroids, and then selects data points which
have the maximum distance as new initial centroids. This algorithm
distributes all initial centroids according to the maximum
accumulated distance metric. This paper evaluates the proposed
approach for image segmentation by comparing with K-means and
Gaussian Mixture Model algorithm and involving RGB, HSV, HSL
and CIELAB color spaces. The experimental results clarify the
effectiveness of our approach to improve the segmentation quality in
aspects of precision and computational time.
Abstract: A concrete structure is designed and constructed for its
purpose of use, and is expected to maintain its function for the target
durable years from when it was planned. Nevertheless, as time elapses
the structure gradually deteriorates and then eventually degrades to the
point where the structure cannot exert the function for which it was
planned. The performance of concrete that is able to maintain the level
of the performance required over the designed period of use as it has
less deterioration caused by the elapse of time under the designed
condition is referred to as Durability. There are a number of causes of
durability degradation, but especially chloride damage, carbonation,
freeze-thaw, etc are the main causes. In this study, carbonation, one of
the main causes of deterioration of the durability of a concrete
structure, was investigated via a microstructure analysis technique.
The method for the measurement of carbonation was studied using the
existing indicator method, and the method of measuring the progress
of carbonation in a quantitative manner was simultaneously studied
using a FT-IR (Fourier-Transform Infrared) Spectrometer along with
the microstructure analysis technique.
Abstract: The Taiwan government has started to promote the “Plain Landscape Afforestation and Greening Program" since 2002. A key task of the program was the payment for environmental services (PES), entitled the “Plain Landscape Afforestation Policy" (PLAP), which was certificated by the Executive Yuan on August 31, 2001 and enacted on January 1, 2002. According to the policy, it is estimated that the total area of afforestation will be 25,100 hectares by December 31, 2007. Until the end of 2007, the policy had been enacted for six years in total and the actual area of afforestation was 8,919.18 hectares. Among them, Taiwan Sugar Corporation (TSC) was accounted for 7,960 hectares (with 2,450.83 hectares as public service area) which occupied 86.22% of the total afforestation area; the private farmland promoted by local governments was accounted for 869.18 hectares which occupied 9.75% of the total afforestation area. Based on the above, we observe that most of the afforestation area in this policy is executed by TSC, and the achievement ratio by TSC is better than by others. It implies that the success of the PLAP is seriously related to the execution of TSC. The objective of this study is to analyze the relevant policy planning of TSC-s participation in the PLAP, suggest complementary measures, and draw up effective adjustment mechanisms, so as to improve the effectiveness of executing the policy. Our main conclusions and suggestions are summarized as follows: 1. The main reason for TSC-s participation in the PLAP is based on their passive cooperation with the central government or company policy. Prior to TSC-s participation in the PLAP, their lands were mainly used for growing sugarcane. 2. The main factors of TSC-s consideration on the selection of tree species are based on the suitability of land and species. The largest proportion of tree species is allocated to economic forests, and the lack of technical instruction was the main problem during afforestation. Moreover, the method of improving TSC-s future development in leisure agriculture and landscape business becomes a key topic. 3. TSC has developed short and long-term plans on participating in the PLAP for the future. However, there is no great willingness or incentive on budgeting for such detailed planning. 4. Most people from TSC interviewed consider the requirements on PLAP unreasonable. Among them, an unreasonable requirement on the number of trees accounted for the greatest proportion; furthermore, most interviewees suggested that the government should continue to provide incentives even after 20 years. 5. Since the government shares the same goals as TSC, there should be sufficient cooperation and communication that support the technical instruction and reduction of afforestation cost, which will also help to improve effectiveness of the policy.
Abstract: Financial literacy is one of the key factors needed in making informed financial decisions. As businesses continue to be more profit driven, more financial and economic intrigues arise that continue to put individuals at the risk of spending more and more without considering the short term and long term effects. We conducted a study to assess financial literacy and financial decision making among Emiratis. Our results show that financial literacy is lacking among Emiratis. Also, almost half of respondents owe loans to other peoples and 1/5 of them have bank loans. We expect that the outcome of this research will be useful for designing educational programs and policies to promote financial planning and security among Emiratis. We also posit that deeper and more informed understanding of this problem is a precursor for developing effective financial education programs with the aim of improving financial decision- making among Emiratis.
Abstract: The purpose of this study was to investigate the impact of the development of Szuchung Creek take for the cause of the critical success factors, This research is to use the depth interviews, document analysis and Modified-Delphi technique survey of nine depth interviews with experts and 14 experts of Modified-Delphi technique questionnaire and inviting as the research object, Szuchung Creek Hot Springs for the scope of the study. The results show, Szuchung Creek Hot Springs development take for career success factors for the following reasons: 1. Government. 2. Opportunities. 3. Factors of production. 4. Demand conditions. 5. Corporate structure and the degree of competition. 6. Related and supporting industries. Furthermore, Szuchung Creek hot springs, itself already has a number of critical success factors. Contingent less than or inadequacies by Szuchung Creek take for the enterprise development to take for the cause of the critical success factors as the basis for correcting, planning out for local use improvement strategies to achieve the objective of sustainable management.
Abstract: The production of a plant can be measured in terms of
seeds. The generation of seeds plays a critical role in our social and
daily life. The fruit production which generates seeds, depends on the
various parameters of the plant, such as shoot length, leaf number,
root length, root number, etc When the plant is growing, some leaves
may be lost and some new leaves may appear. It is very difficult to
use the number of leaves of the tree to calculate the growth of the
plant.. It is also cumbersome to measure the number of roots and
length of growth of root in several time instances continuously after
certain initial period of time, because roots grow deeper and deeper
under ground in course of time. On the contrary, the shoot length of
the tree grows in course of time which can be measured in different
time instances. So the growth of the plant can be measured using the
data of shoot length which are measured at different time instances
after plantation. The environmental parameters like temperature, rain
fall, humidity and pollution are also play some role in production of
yield. The soil, crop and distance management are taken care to
produce maximum amount of yields of plant. The data of the growth
of shoot length of some mustard plant at the initial stage (7,14,21 &
28 days after plantation) is available from the statistical survey by a
group of scientists under the supervision of Prof. Dilip De. In this
paper, initial shoot length of Ken( one type of mustard plant) has
been used as an initial data. The statistical models, the methods of
fuzzy logic and neural network have been tested on this mustard
plant and based on error analysis (calculation of average error) that
model with minimum error has been selected and can be used for the
assessment of shoot length at maturity. Finally, all these methods
have been tested with other type of mustard plants and the particular
soft computing model with the minimum error of all types has been
selected for calculating the predicted data of growth of shoot length.
The shoot length at the stage of maturity of all types of mustard
plants has been calculated using the statistical method on the
predicted data of shoot length.
Abstract: The present study presents a new approach to automatic
data clustering and classification problems in large and complex
databases and, at the same time, derives specific types of explicit rules
describing each cluster. The method works well in both sparse and
dense multidimensional data spaces. The members of the data space
can be of the same nature or represent different classes. A number
of N-dimensional ellipsoids are used for enclosing the data clouds.
Due to the geometry of an ellipsoid and its free rotation in space
the detection of clusters becomes very efficient. The method is based
on genetic algorithms that are used for the optimization of location,
orientation and geometric characteristics of the hyper-ellipsoids. The
proposed approach can serve as a basis for the development of
general knowledge systems for discovering hidden knowledge and
unexpected patterns and rules in various large databases.
Abstract: An alarming emergence of multidrug-resistant strains
of the tuberculosis pathogen Mycobacterium tuberculosis and
continuing high worldwide incidence of tuberculosis has invigorated
the search for novel drug targets. The enzyme glutamate racemase
(MurI) in bacteria catalyzes the stereoconversion of L-glutamate to
D-glutamate which is a component of the peptidoglycan cell wall of
the bacterium. The inhibitors targeted against MurI from several
bacterial species have been patented and are advocated as promising
antibacterial agents. However there are none available against MurI
from Mycobacterium tuberculosis, due to the lack of its threedimensional
structure. This work accomplished two major objectives.
First, the tertiary structure of MtMurI was deduced computationally
through homology modeling using the templates from bacterial
homologues. It is speculated that like in other Gram-positive bacteria,
MtMurI exists as a dimer and many of the protein interactions at the
dimer interface are also conserved. Second, potent candidate
inhibitors against MtMurI were identified through docking against
already known inhibitors in other organisms.
Abstract: The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.