Abstract: River Hindon is an important river catering the
demand of highly populated rural and industrial cluster of western
Uttar Pradesh, India. Water quality of river Hindon is deteriorating at
an alarming rate due to various industrial, municipal and agricultural
activities. The present study aimed at identifying the pollution
sources and quantifying the degree to which these sources are
responsible for the deteriorating water quality of the river. Various
water quality parameters, like pH, temperature, electrical
conductivity, total dissolved solids, total hardness, calcium, chloride,
nitrate, sulphate, biological oxygen demand, chemical oxygen
demand, and total alkalinity were assessed. Water quality data
obtained from eight study sites for one year has been subjected to the
two multivariate techniques, namely, principal component analysis
and cluster analysis. Principal component analysis was applied with
the aim to find out spatial variability and to identify the sources
responsible for the water quality of the river. Three Varifactors were
obtained after varimax rotation of initial principal components using
principal component analysis. Cluster analysis was carried out to
classify sampling stations of certain similarity, which grouped eight
different sites into two clusters. The study reveals that the
anthropogenic influence (municipal, industrial, waste water and
agricultural runoff) was the major source of river water pollution.
Thus, this study illustrates the utility of multivariate statistical
techniques for analysis and elucidation of multifaceted data sets,
recognition of pollution sources/factors and understanding
temporal/spatial variations in water quality for effective river water
quality management.
Abstract: In this paper, we calculate the two-photon ionization
(TPI) cross-section for pump-probe scheme in Ag neutral cluster. The
pump photon energy is assumed to be close to the surface plasmon
(SP) energy of cluster in dielectric media. Due to this choice, the
pump wave excites collective oscillations of electrons-SP and the
probe wave causes ionization of the cluster. Since the interband
transition energy in Ag exceeds the SP resonance energy, the main
contribution into the TPI comes from the latter. The advantage of Ag
clusters as compared to the other noble metals is that the SP
resonance in silver cluster is much sharper because of peculiarities of
its dielectric function. The calculations are performed by separating
the coordinates of electrons corresponding to the collective
oscillations and the individual motion that allows taking into account
the resonance contribution of excited SP oscillations. It is shown that
the ionization cross section increases by two orders of magnitude if
the energy of the pump photon matches the surface plasmon energy
in the cluster.
Abstract: Given the increase in the number of e-commerce sites,
the number of competitors has become very important. This means
that companies have to take appropriate decisions in order to meet the
expectations of their customers and satisfy their needs. In this paper,
we present a case study of applying LRFM (length, recency,
frequency and monetary) model and clustering techniques in the
sector of electronic commerce with a view to evaluating customers’
values of the Moroccan e-commerce websites and then developing
effective marketing strategies. To achieve these objectives, we adopt
LRFM model by applying a two-stage clustering method. In the first
stage, the self-organizing maps method is used to determine the best
number of clusters and the initial centroid. In the second stage, kmeans
method is applied to segment 730 customers into nine clusters
according to their L, R, F and M values. The results show that the
cluster 6 is the most important cluster because the average values of
L, R, F and M are higher than the overall average value. In addition,
this study has considered another variable that describes the mode of
payment used by customers to improve and strengthen clusters’
analysis. The clusters’ analysis demonstrates that the payment method is
one of the key indicators of a new index which allows to assess the
level of customers’ confidence in the company's Website.
Abstract: The fundamental issue in understanding the origin and
growth mechanism of nanomaterials, from a fundamental unit is a big
challenging problem to the scientists. Recently, an immense attention
is generated to the researchers for prediction of exceptionally stable
atomic cluster units as the building units for future smart materials.
The present study is a systematic investigation on the stability and
electronic properties of a series of bimetallic (semiconductor-alkaline
earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for
exceptional and/ or unusual stable motifs. A very popular hybrid
exchange-correlation functional, B3LYP along with a higher basis
set, viz., 6-31+G[d,p] is employed for this purpose under the density
functional formalism. The magic stability among the concerned
clusters is explained using the jellium model. It is evident from the
present study that the magic stability of B4Mg3
cluster arises due to
the jellium shell closure.
Abstract: In this paper a very simple and effective user
administration view of computing clusters systems is implemented in
order of friendly provide the configuration and monitoring of
distributed application executions. The user view, the administrator
view, and an internal control module create an illusionary
management environment for better system usability. The
architecture, properties, performance, and the comparison with others
software for cluster management are briefly commented.
Abstract: Clustering is a process of grouping objects and data
into groups of clusters to ensure that data objects from the same
cluster are identical to each other. Clustering algorithms in one of the
area in data mining and it can be classified into partition, hierarchical,
density based and grid based. Therefore, in this paper we do survey
and review four major hierarchical clustering algorithms called
CURE, ROCK, CHAMELEON and BIRCH. The obtained state of
the art of these algorithms will help in eliminating the current
problems as well as deriving more robust and scalable algorithms for
clustering.
Abstract: The main issue in designing a wireless sensor network
(WSN) is the finding of a proper routing protocol that complies with
the several requirements of high reliability, short latency, scalability,
low power consumption, and many others. This paper proposes a
novel routing algorithm that complies with these design
requirements. The new routing protocol divides the WSN into several subnetworks
and each sub-network is divided into several clusters. This
division is designed to reduce the number of radio transmission and
hence decreases the power consumption. The network division may
be changed dynamically to adapt with the network changes and
allows the realization of the design requirements.
Abstract: This paper discusses micrometeorological aspects of the urban climate in three cities in Western São Paulo State: Presidente Prudente, Assis and Iepê. Particular attention is paid to the method used to estimate the components of the energy balance at the surface. Estimates of convective fluxes showed that the Bowen ratio was an indicator of the local climate and that its magnitude varied between 0.3 and 0.7. Maximum values for the Bowen ratio occurred earlier in Iepê (11:00 am) than in Presidente Prudente (4:00 pm). The results indicate that the Bowen ratio is modulated by the radiation balance at the surface and by different clusters of vegetation.
Abstract: Low Temperature Matrix Isolation - Electron
Paramagnetic Resonance (LTMI-EPR) Spectroscopy was utilized to
identify the species of iron oxide nanoparticles generated during the
oxidative pyrolysis of 1-methylnaphthalene (1-MN). The otherwise
gas-phase reactions of 1--MN were impacted by a polypropylenimine
tetra-hexacontaamine dendrimer complexed with iron (III) nitrate
nonahydrate diluted in air under atmospheric conditions. The EPR
fine structure of Fe (III)2O3 nanoparticles clusters, characterized by gfactors
of 2.00, 2.28, 3.76 and 4.37 were detected on a cold finger
maintained at 77 K after accumulation over a multitude of
experiments. Additionally, a high valence Fe (IV) paramagnetic
intermediate and superoxide anion-radicals, O2•- adsorbed on
nanoparticle surfaces in the form of Fe (IV) --- O2•- were detected
from the quenching area of Zone 1 in the gas-phase.
Abstract: This study focuses on a novel method for dispersion
and distribution of reinforcement under high intensive shear stress to
produce metal composites. The polyacrylonitrile (PAN)-based short
carbon fiber (Csf) and Nextel 610 alumina fiber were dispersed under
high intensive shearing at mushy zone in semi-solid of A356 by a
novel method. The bundles and clusters were embedded by
infiltration of slurry into the clusters, thus leading to a uniform
microstructure. The fibers were embedded homogenously into the
aluminum around 576-580°C with around 46% of solid fraction.
Other experiments at 615°C and 568°C which are contained 0% and
90% solid respectively were not successful for dispersion and
infiltration of aluminum into bundles of Csf. The alumina fiber has
been cracked by high shearing load. The morphologies and
crystalline phase were evaluated by SEM and XRD. The adopted
thixo-process effectively improved the adherence and distribution of
Csf into Al that can be developed to produce various composites by
thixomixing.
Abstract: During the post-Civil War era, the city of Nashville,
Tennessee, had the highest mortality rate in the United States. The
elevated death and disease rates among former slaves were
attributable to lack of quality healthcare. To address the paucity of
healthcare services, Meharry Medical College, an institution with the
mission of educating minority professionals and serving the
underserved population, was established in 1876.
Purpose: The social ecological framework and partial least squares
(PLS) path modeling were used to quantify the impact of
socioeconomic status and adverse health outcome on primary care
professionals serving the disadvantaged community. Thus, the study
results could demonstrate the accomplishment of the College’s
mission of training primary care professionals to serve in underserved
areas.
Methods: Various statistical methods were used to analyze alumni
data from 1975 – 2013. K-means cluster analysis was utilized to
identify individual medical and dental graduates in the cluster groups
of the practice communities (Disadvantaged or Non-disadvantaged
Communities). Discriminant analysis was implemented to verify the
classification accuracy of cluster analysis. The independent t-test was
performed to detect the significant mean differences of respective
clustering and criterion variables. Chi-square test was used to test if
the proportions of primary care and non-primary care specialists are
consistent with those of medical and dental graduates practicing in
the designated community clusters. Finally, the PLS path model was
constructed to explore the construct validity of analytic model by
providing the magnitude effects of socioeconomic status and adverse
health outcome on primary care professionals serving the
disadvantaged community.
Results: Approximately 83% (3,192/3,864) of Meharry Medical
College’s medical and dental graduates from 1975 to 2013 were
practicing in disadvantaged communities. Independent t-test confirmed the content validity of the cluster analysis model. Also, the
PLS path modeling demonstrated that alumni served as primary care
professionals in communities with significantly lower socioeconomic
status and higher adverse health outcome (p < .001). The PLS path
modeling exhibited the meaningful interrelation between primary
care professionals practicing communities and surrounding
environments (socioeconomic statues and adverse health outcome),
which yielded model reliability, validity, and applicability.
Conclusion: This study applied social ecological theory and
analytic modeling approaches to assess the attainment of Meharry
Medical College’s mission of training primary care professionals to
serve in underserved areas, particularly in communities with low
socioeconomic status and high rates of adverse health outcomes. In
summary, the majority of medical and dental graduates from Meharry
Medical College provided primary care services to disadvantaged
communities with low socioeconomic status and high adverse health
outcome, which demonstrated that Meharry Medical College has
fulfilled its mission. The high reliability, validity, and applicability of
this model imply that it could be replicated for comparable
universities and colleges elsewhere.
Abstract: Dengue outbreaks are affected by biological,
ecological, socio-economic and demographic factors that vary over
time and space. These factors have been examined separately and still
require systematic clarification. The present study aimed to investigate
the spatial-temporal clustering relationships between these factors and
dengue outbreaks in the northern region of Sri Lanka. Remote sensing
(RS) data gathered from a plurality of satellites were used to develop
an index comprising rainfall, humidity and temperature data. RS data
gathered by ALOS/AVNIR-2 were used to detect urbanization, and a
digital land cover map was used to extract land cover information.
Other data on relevant factors and dengue outbreaks were collected
through institutions and extant databases. The analyzed RS data and
databases were integrated into geographic information systems,
enabling temporal analysis, spatial statistical analysis and space-time
clustering analysis. Our present results showed that increases in the
number of the combination of ecological factor and socio-economic
and demographic factors with above the average or the presence
contribute to significantly high rates of space-time dengue clusters.
Abstract: Neurons in the nervous system communicate with
each other by producing electrical signals called spikes. To
investigate the physiological function of nervous system it is essential
to study the activity of neurons by detecting and sorting spikes in the
recorded signal. In this paper a method is proposed for considering
the spike sorting problem which is based on the nonlinear modeling
of spikes using exponential autoregressive model. The genetic
algorithm is utilized for model parameter estimation. In this regard
some selected model coefficients are used as features for sorting
purposes. For optimal selection of model coefficients, self-organizing
feature map is used. The results show that modeling of spikes with
nonlinear autoregressive model outperforms its linear counterpart.
Also the extracted features based on the coefficients of exponential
autoregressive model are better than wavelet based extracted features
and get more compact and well-separated clusters. In the case of
spikes different in small-scale structures where principal component
analysis fails to get separated clouds in the feature space, the
proposed method can obtain well-separated cluster which removes
the necessity of applying complex classifiers.
Abstract: Clustering involves the partitioning of n objects into k
clusters. Many clustering algorithms use hard-partitioning techniques
where each object is assigned to one cluster. In this paper we propose
an overlapping algorithm MCOKE which allows objects to belong to
one or more clusters. The algorithm is different from fuzzy clustering
techniques because objects that overlap are assigned a membership
value of 1 (one) as opposed to a fuzzy membership degree. The
algorithm is also different from other overlapping algorithms that
require a similarity threshold be defined a priori which can be
difficult to determine by novice users.
Abstract: Many of the ever-growing elderly population require
exercise, such as running, for health management. One important
element of a runner’s training is the choice of shoes for exercise; shoes
are important because they provide the interface between the feet and
road. When we purchase shoes, we may instinctively choose a pair
after trying on many different pairs of shoes. Selecting the shoes
instinctively may work, but it does not guarantee a suitable fit for
running activities. Therefore, if we could select suitable shoes for each
runner from the viewpoint of brain activities, it would be helpful for
validating shoe selection. In this paper, we describe how brain
activities show different characteristics during particular task,
corresponding to different properties of shoes. Using five subjects, we
performed a verification experiment, applying weight, softness, and
flexibility as shoe properties. In order to affect the shoe property’s
differences to the brain, subjects run for 10 min. Before and after
running, subjects conducted a paced auditory serial addition task
(PASAT) as the particular task; and the subjects’ brain activities
during the PASAT are evaluated based on oxyhemoglobin and
deoxyhemoglobin relative concentration changes, measured by
near-infrared spectroscopy (NIRS). When the brain works actively,
oxihemoglobin and deoxyhemoglobin concentration drastically
changes; therefore, we calculate the maximum values of concentration
changes. In order to normalize relative concentration changes after
running, the maximum value are divided by before running maximum
value as evaluation parameters. The classification of the groups of
shoes is expressed on a self-organizing map (SOM). As a result,
deoxyhemoglobin can make clusters for two of the three types of
shoes.
Abstract: The hydrogenated amorphous carbon films (α-C:H)
were deposited on p-type Si (100) substrates at different thicknesses by
radio frequency plasma enhanced chemical vapor deposition
technique (rf-PECVD). Raman spectra display asymmetric
diamond-like carbon (DLC) peaks, representative of the α-C:H films.
The decrease of intensity ID/IG ratios revealed the sp3 content arise at
different thicknesses of the α-C:H films. In terms of mechanical
properties, the high hardness and elastic modulus values showed the
elastic and plastic deformation behaviors related to sp3 content in
amorphous carbon films. Electrochemical properties showed that the
α-C:H films exhibited excellent corrosion resistance in air-saturated
3.5 wt.% NaCl solution for pH 2 at room temperature. Thickness
increasing affected the small sp2 clusters in matrix, restricting the
velocity transfer and exchange of electrons. The deposited α-C:H films
exhibited excellent mechanical properties and corrosion resistance.
Abstract: The North-eastern part of India, which receives
heavier rainfall than other parts of the subcontinent, is of great
concern now-a-days with regard to climate change. High intensity
rainfall for short duration and longer dry spell, occurring due to
impact of climate change, affects river morphology too. In the present
study, an attempt is made to delineate the North-eastern region of
India into some homogeneous clusters based on the Fuzzy Clustering
concept and to compare the resulting clusters obtained by using
conventional methods and nonconventional methods of clustering.
The concept of clustering is adapted in view of the fact that, impact
of climate change can be studied in a homogeneous region without
much variation, which can be helpful in studies related to water
resources planning and management. 10 IMD (Indian Meteorological
Department) stations, situated in various regions of the North-east,
have been selected for making the clusters. The results of the Fuzzy
C-Means (FCM) analysis show different clustering patterns for
different conditions. From the analysis and comparison it can be
concluded that nonconventional method of using GCM data is
somehow giving better results than the others. However, further
analysis can be done by taking daily data instead of monthly means to
reduce the effect of standardization.
Abstract: Online forum is part of a Learning Management
System (LMS) environment in which students share their opinions.
This study attempts to investigate the perceptions of students towards
online forum and their patterns of listening behavior during the forum
interaction. The students’ perceptions were measured using a
questionnaire, in which seven dimensions were used involving online
experience, benefits of forum participation, cost of participation,
perceived ease of use, usefulness, attitude, and intention. Meanwhile,
their patterns of listening behaviors were obtained using the log file
extracted from the LMS. A total of 25 postgraduate students
undertaking a course were involved in this study, and their activities
in the forum session were recorded by the LMS and used as a log file.
The results from the questionnaire analysis indicated that the students
perceived that the forum is easy to use, useful, and bring benefits to
them. Also, they showed positive attitude towards online forum, and
they have the intention to use it in future. Based on the log data, the
participants were also divided into six clusters of listening behavior,
in which they are different in terms of temporality, breadth, depth and
speaking level. The findings were compared to previous clusters
grouping and future recommendations are also discussed.
Abstract: The theoretical approach is developed to describe the
change of drops in the atmosphere of own steam and buffer gas under
irradiation. It is shown that the irradiation influences on size of stable
droplet and on the conditions under which the droplet exists. Under
irradiation the change of drop becomes more complex: the not
monotone and periodical change of size of drop becomes possible.
All possible solutions are represented by means of phase portrait. It is
found all qualitatively different phase portraits as function of critical
parameters: rate generation of clusters and substance density.
Abstract: An extensive amount of work has been done in data
clustering research under the unsupervised learning technique in Data
Mining during the past two decades. Moreover, several approaches
and methods have been emerged focusing on clustering diverse data
types, features of cluster models and similarity rates of clusters.
However, none of the single clustering algorithm exemplifies its best
nature in extracting efficient clusters. Consequently, in order to
rectify this issue, a new challenging technique called Cluster
Ensemble method was bloomed. This new approach tends to be the
alternative method for the cluster analysis problem. The main
objective of the Cluster Ensemble is to aggregate the diverse
clustering solutions in such a way to attain accuracy and also to
improve the eminence the individual clustering algorithms. Due to
the massive and rapid development of new methods in the globe of
data mining, it is highly mandatory to scrutinize a vital analysis of
existing techniques and the future novelty. This paper shows the
comparative analysis of different cluster ensemble methods along
with their methodologies and salient features. Henceforth this
unambiguous analysis will be very useful for the society of clustering
experts and also helps in deciding the most appropriate one to resolve
the problem in hand.