Abstract: Data stream analysis is the process of computing
various summaries and derived values from large amounts of data
which are continuously generated at a rapid rate. The nature of a
stream does not allow a revisit on each data element. Furthermore,
data processing must be fast to produce timely analysis results. These
requirements impose constraints on the design of the algorithms to
balance correctness against timely responses. Several techniques
have been proposed over the past few years to address these
challenges. These techniques can be categorized as either dataoriented
or task-oriented. The data-oriented approach analyzes a
subset of data or a smaller transformed representation, whereas taskoriented
scheme solves the problem directly via approximation
techniques. We propose a hybrid approach to tackle the data stream
analysis problem. The data stream has been both statistically
transformed to a smaller size and computationally approximated its
characteristics. We adopt a Monte Carlo method in the approximation
step. The data reduction has been performed horizontally and
vertically through our EMR sampling method. The proposed method
is analyzed by a series of experiments. We apply our algorithm on
clustering and classification tasks to evaluate the utility of our
approach.
Abstract: The main mission of Ezilla is to provide a friendly
interface to access the virtual machine and quickly deploy the high
performance computing environment. Ezilla has been developed by
Pervasive Computing Team at National Center for High-performance
Computing (NCHC). Ezilla integrates the Cloud middleware,
virtualization technology, and Web-based Operating System (WebOS)
to form a virtual computer in distributed computing environment. In
order to upgrade the dataset and speedup, we proposed the sensor
observation system to deal with a huge amount of data in the
Cassandra database. The sensor observation system is based on the
Ezilla to store sensor raw data into distributed database. We adopt the
Ezilla Cloud service to create virtual machines and login into virtual
machine to deploy the sensor observation system. Integrating the
sensor observation system with Ezilla is to quickly deploy experiment
environment and access a huge amount of data with distributed
database that support the replication mechanism to protect the data
security.
Abstract: This paper aims to argue that religion and Faith-based
Organizations (FBOs) contribute to building democratic process
through the provision of education in Sierra Leone. Sierra Leone
experienced a civil war from 1991 to 2002 and about 70 percent of the
population lives in poverty. While the government has been in the
process of rebuilding the nation, many forms of Civil Society
Organizations (CSOs), including FBOs, have played a significant role
in promoting social development. Education plays an important role in
supporting people-s democratic movements through knowledge
acquisition, spiritual enlightenment and empowerment. This paper
discusses religious tolerance in Sierra Leone and how FBOs have
contributed to the provision of primary education in Sierra Leone. This
study is based on the author-s field research, which involved
interviews with teachers and development stakeholders, notably
government officials, Non-governmental Organizations (NGOs) and
FBOs, as well as questionnaires completed by pupils, parents and
teachers.
Abstract: The paper presents a part of the results obtained in a
complex research project on Romanian Grey Steppe breed, owner of
some remarkable qualities such as hardiness, longevity, adaptability,
special resistance to ban weather and diseases and included in the
genetic fund (G.D. no. 822/2008.) from Romania.
Following the researches effectuated, we identified alleles of six
loci, codifying the six types of major milk proteins: alpha-casein S1
(α S1-cz); beta-casein (β-cz); kappa-casein (K-cz); beta-lactoglobulin
(β-lg); alpha-lactalbumin (α-la) and alpha-casein S2 (α S2-cz). In
system αS1-cz allele αs1-Cn B has the highest frequency (0.700), in
system β-cz allele β-Cn A2 ( 0.550 ), in system K-cz allele k-CnA2 (
0.583 ) and heterozygote genotype AB ( 0.416 ) and BB (0.375), in
system β-lg allele β-lgA1 has the highest frequency (0.542 ) and
heterozygote genotype AB ( 0.500 ), in system α-la there is
monomorphism for allele α-la B and similarly in system αS2-cz for
allele αs2-Cn A.
The milk analysis by the isoelectric focalization technique (I.E.F.)
allowed the identification of a new allele for locus αS1-casein, for two
of the individuals under analysis, namely allele called αS1-casein
IRV. When experiments were repeated, we noticed that this is not a
proteolysis band and it really was a new allele that has not been
registered in the specialized literature so far. We identified two
heterozygote individuals, carriers of this allele, namely: BIRV and
CIRV. This discovery is extremely important if focus is laid on the
national genetic patrimony.
Abstract: The draw solute separation process in Forward
Osmosis desalination was simulated in Aspen Plus chemical process
modeling software, to estimate the energy consumption and compare
it with other desalination processes, mainly the Reverse Osmosis
process which is currently most prevalent. The electrolytic chemistry
for the system was retrieved using the Elec – NRTL property method
in the Aspen Plus database. Electrical equivalent of energy required
in the Forward Osmosis desalination technique was estimated and
compared with the prevalent desalination techniques.
Abstract: This paper deals with the design, development & implementation of a temperature sensor using zigbee. The main aim of the work undertaken in this paper is to sense the temperature and to display the result on the LCD using the zigbee technology. ZigBee operates in the industrial, scientific and medical (ISM) radio bands; 868 MHz in Europe, 915 MHz in the USA and 2.4 GHz in most jurisdictions worldwide. The technology is intended to be simpler and cheaper than other WPANs such as Bluetooth. The most capable ZigBee node type is said to require only about 10 % of the software of a typical Bluetooth or Wireless Internet node, while the simplest nodes are about 2 %. However, actual code sizes are much higher, more like 50 % of the Bluetooth code size. ZigBee chip vendors have announced 128-kilobyte devices. In this work undertaken in the design & development of the temperature sensor, it senses the temperature and after amplification is then fed to the micro controller, this is then connected to the zigbee module, which transmits the data and at the other end the zigbee reads the data and displays on to the LCD. The software developed is highly accurate and works at a very high speed. The method developed shows the effectiveness of the scheme employed.
Abstract: In wireless sensor network (WSN) the use of mobile
sink has been attracting more attention in recent times. Mobile sinks
are more effective means of balancing load, reducing hotspot
problem and elongating network lifetime. The sensor nodes in WSN
have limited power supply, computational capability and storage and
therefore for continuous data delivery reliability becomes high
priority in these networks. In this paper, we propose a Reliable
Energy-efficient Data Dissemination (REDD) scheme for WSNs with
multiple mobile sinks. In this strategy, sink first determines the
location of source and then directly communicates with the source
using geographical forwarding. Every forwarding node (FN) creates a
local zone comprising some sensor nodes that can act as
representative of FN when it fails. Analytical and simulation study
reveals significant improvement in energy conservation and reliable
data delivery in comparison to existing schemes.
Abstract: This paper presents a new spread-spectrum
watermarking algorithm for digital images in discrete wavelet
transform (DWT) domain. The algorithm is applied for embedding
watermarks like patient identification /source identification or
doctors signature in binary image format into host digital
radiological image for potential telemedicine applications.
Performance of the algorithm is analysed by varying the gain factor,
subband decomposition levels, and size of watermark. Simulation
results show that the proposed method achieves higher watermarking
capacity.
Abstract: The authors present a mixed method for reducing the order of the large-scale dynamic systems. In this method, the denominator polynomial of the reduced order model is obtained by using the modified pole clustering technique while the coefficients of the numerator are obtained by Pade approximations. This method is conceptually simple and always generates stable reduced models if the original high-order system is stable. The proposed method is illustrated with the help of the numerical examples taken from the literature.
Abstract: After allowing direct flights from Mainland China to
Taiwan, Chinese tourists increased according to Tourism
Bureaustatistics. There are from 0.19 to 2 million tourists from 2008 to
2011. Mainland China has become the main source of Taiwan
developing tourism industry. Taiwanese government should know
more about comments from Chinese tourists to Taiwan in order
toproperly market Taiwan tourism and enhance the overall quality of
tourism. In order to understand Chinese visitors’ comments, this study
adopts content analysis to analyze electronic word-of-mouth on Web.
This study collects 375 blog articles of Chinese tourists from
Ctrip.com as a database during 2009 to 2011. Through the qualitative
data analysis the traveling destination imagesis divided into seven
dimensions, such as senic spots, shopping, food and beverages,
accommodations, transportation, festivals and recreation activities.
Finally, this study proposes some practical managerial implication to
know both positive and negative images of the seven dimensions from
Chinese tourists, providing marketing strategies and suggestions to
traveling agency industry.
Abstract: In this paper, the modelling and design of artificial neural network architecture for load forecasting purposes is investigated. The primary pre-requisite for power system planning is to arrive at realistic estimates of future demand of power, which is known as Load Forecasting. Short Term Load Forecasting (STLF) helps in determining the economic, reliable and secure operating strategies for power system. The dependence of load on several factors makes the load forecasting a very challenging job. An over estimation of the load may cause premature investment and unnecessary blocking of the capital where as under estimation of load may result in shortage of equipment and circuits. It is always better to plan the system for the load slightly higher than expected one so that no exigency may arise. In this paper, a load-forecasting model is proposed using a multilayer neural network with an appropriately modified back propagation learning algorithm. Once the neural network model is designed and trained, it can forecast the load of the power system 24 hours ahead on daily basis and can also forecast the cumulative load on daily basis. The real load data that is used for the Artificial Neural Network training was taken from LDC, Gujarat Electricity Board, Jambuva, Gujarat, India. The results show that the load forecasting of the ANN model follows the actual load pattern more accurately throughout the forecasted period.
Abstract: In this paper, we propose a novel adaptive voltage control strategy for boost converter via Inverse LQ Servo-Control. Our presented strategy is based on an analytical formula of Inverse Linear Quadratic (ILQ) design method, which is not necessary to solve Riccati’s equation directly. The optimal and adaptive controller of the voltage control system is designed. The stability and the robust control are analyzed. Whereas, we can get the analytical solution for the optimal and robust voltage control is achieved through the natural angular velocity within a single parameter and we can change the responses easily via the ILQ control theory. Our method provides effective results as the stable responses and the response times are not drifted even if the condition is changed widely.
Abstract: The evaluation of non-conventional water resources
on seed germination and seedling growth performance at early
growth stages is still in progress especially in forage crops. This
study was designed to test the effect of four types of water qualities
(treated wastewater (TWW), industrial water (IW), grey water (GW),
and Distilled water (DW)) on germination and early seedling vigor of
Leucaena leucocephala. The results showed that the germination
was not significantly affected by the different water qualities. Seed
germination reached maximum after 17, 14, 14, and 21 days under
GW, IW, TWW, and DW treatments, respectively. The highest mean
of shoot length was scored under the GW treatment. And, the highest
mean of root length was scored under DW which was not significant
from GW treatment. The means of shoot fresh was the highest under
the TWW. The means of root fresh weight was not significantly
different from each other's under different treatments. The growth
performance was in progress with no mortality during 21 days of
growth. Thus, the best non-conventional water qualities alternatives
based on the cleanness, nutrients, and toxicity are the GW, TWW and
IW, respectively.
Abstract: Proteins levels produced by bacteria may be increased
in stressful surroundings, such as in the presence of antibiotics. It
appears that many antimicrobial agents or antibiotics, when used at
low concentrations, have in common the ability to activate or repress
gene transcription, which is distinct from their inhibitory effect.
There have been comparatively few studies on the potential of
antibiotics or natural compounds in nature as a specific chemical
signal that can trigger a variety of biological functions. Therefore,
this study was focusing on the effect of essential oils from
Cymbopogon flexuosus and C. nardus in regulating proteins
production by Bacillus subtilis ATCC 21332. The Minimum
Inhibition Concentrations (MICs) of both essential oils on B. subtilis
were determined by using microdilution assay, resulting 0.2% and
1.56% for each C. flexuosus and C. nardus subsequently. The
bacteria were further exposed to each essential oils at concentration
of 0.01XMIC for 2 days. The proteins were then isolated and
analyzed by sodium dodecyl sulfate polyacrylamide gel
electrophoresis (SDS-PAGE). Protein profile showed that a band
with approximate size of 250 kD was appeared for the treated
bacteria with essential oils. Thus, Bacillus subtilis ATCC 21332 in
stressful condition with the presence of essential oils at low
concentration could induce the protein production.
Abstract: Environmental awareness and depletion of the
petroleum resources are among vital factors that motivate a number
of researchers to explore the potential of reusing natural fiber as an
alternative composite material in industries such as packaging,
automotive and building constructions. Natural fibers are available in
abundance, low cost, lightweight polymer composite and most
importance its biodegradability features, which often called “ecofriendly"
materials. However, their applications are still limited due
to several factors like moisture absorption, poor wettability and large
scattering in mechanical properties. Among the main challenges on
natural fibers reinforced matrices composite is their inclination to
entangle and form fibers agglomerates during processing due to
fiber-fiber interaction. This tends to prevent better dispersion of the
fibers into the matrix, resulting in poor interfacial adhesion between
the hydrophobic matrix and the hydrophilic reinforced natural fiber.
Therefore, to overcome this challenge, fiber treatment process is one
common alternative that can be use to modify the fiber surface
topology by chemically, physically or mechanically technique.
Nevertheless, this paper attempt to focus on the effect of
mercerization treatment on mechanical properties enhancement of
natural fiber reinforced composite or so-called bio composite. It
specifically discussed on mercerization parameters, and natural fiber
reinforced composite mechanical properties enhancement.
Abstract: The article deals with development, design and
implementation of a mathematical model of the human respiratory
system. The model is designed in order to simulate distribution of
important intrapulmonary parameters along the bronchial tree such as
pressure amplitude, tidal volume and effect of regional mechanical
lung properties upon the efficiency of various ventilatory techniques.
Therefore exact agreement of the model structure with the lung
anatomical structure is required. The model is based on the lung
morphology and electro-acoustic analogy is used to design the
model.
Abstract: We report the results of an lattice Boltzmann
simulation of magnetohydrodynamic damping of sidewall convection
in a rectangular enclosure filled with a porous medium. In particular
we investigate the suppression of convection when a steady magnetic
field is applied in the vertical direction. The left and right vertical
walls of the cavity are kept at constant but different temperatures
while both the top and bottom horizontal walls are insulated. The
effects of the controlling parameters involved in the heat transfer and
hydrodynamic characteristics are studied in detail. The heat and mass
transfer mechanisms and the flow characteristics inside the enclosure
depended strongly on the strength of the magnetic field and Darcy
number. The average Nusselt number decreases with rising values of
the Hartmann number while this increases with increasing values of
the Darcy number.
Abstract: We present analysis of spatial patterns of generic
disease spread simulated by a stochastic long-range correlation SIR
model, where individuals can be infected at long distance in a power
law distribution. We integrated various tools, namely perimeter,
circularity, fractal dimension, and aggregation index to characterize
and investigate spatial pattern formations. Our primary goal was to
understand for a given model of interest which tool has an advantage
over the other and to what extent. We found that perimeter and
circularity give information only for a case of strong correlation–
while the fractal dimension and aggregation index exhibit the growth
rule of pattern formation, depending on the degree of the correlation
exponent (β). The aggregation index method used as an alternative
method to describe the degree of pathogenic ratio (α). This study may
provide a useful approach to characterize and analyze the pattern
formation of epidemic spreading
Abstract: The spectral action balance equation is an equation that
used to simulate short-crested wind-generated waves in shallow water
areas such as coastal regions and inland waters. This equation consists
of two spatial dimensions, wave direction, and wave frequency which
can be solved by finite difference method. When this equation with
dominating propagation velocity terms are discretized using central
differences, stability problems occur when the grid spacing is chosen
too coarse. In this paper, we introduce the splitting modified donorcell
scheme for avoiding stability problems and prove that it is
consistent to the modified donor-cell scheme with same accuracy. The
splitting modified donor-cell scheme was adopted to split the wave
spectral action balance equation into four one-dimensional problems,
which for each small problem obtains the independently tridiagonal
linear systems. For each smaller system can be solved by direct or
iterative methods at the same time which is very fast when performed
by a multi-cores computer.
Abstract: Highly ordered arrays of TiO2 nanotubes (TiNTs) were grown vertically on Ti foil by electrochemical anodization. We controlled the lengths of these TiNTs from 2.4 to 26.8 ¶üÇóμm while varying the water contents (1, 3, and 6 wt%) of the electrolyte in ethylene glycol in the presence of 0.5 wt% NH4F with anodization for various applied voltages (20–80 V), periods (10–240 min) and temperatures (10–30 oC). For vertically aligned TiNT arrays, not only the increase in their tube lengths, but also their geometric (wall thickness and surface roughness) and crystalline structure lead to a significant influence on photocatalytic activity. The length optimization for methylene blue (MB) photodegradation was 18 μm. Further extending the TiNT length yielded lower photocatalytic activity presumably related to the limited MB diffusion and light-penetration depth into the TiNT arrays. The results indicated that a maximum MB photodegradation rate was obtained for the discrete anatase TiO2 nanotubes with thick and rough walls.