Abstract: This paper presents an optimal broadcast algorithm
for the hypercube networks. The main focus of the paper is the
effectiveness of the algorithm in the presence of many node faults.
For the optimal solution, our algorithm builds with spanning tree
connecting the all nodes of the networks, through which messages
are propagated from source node to remaining nodes. At any given
time, maximum n − 1 nodes may fail due to crashing. We show
that the hypercube networks are strongly fault-tolerant. Simulation
results analyze to accomplish algorithm characteristics under many
node faults. We have compared our simulation results between our
proposed method and the Fu’s method. Fu’s approach cannot tolerate
n − 1 faulty nodes in the worst case, but our approach can tolerate
n − 1 faulty nodes.
Abstract: The research of juice flavor forecasting has become
more important in China. Due to the fast economic growth in China,
many different kinds of juices have been introduced to the market. If a
beverage company can understand their customers’ preference well,
the juice can be served more attractive. Thus, this study intends to
introducing the basic theory and computing process of grapes juice
flavor forecasting based on support vector regression (SVR). Applying
SVR, BPN, and LR to forecast the flavor of grapes juice in real data
shows that SVR is more suitable and effective at predicting
performance.
Abstract: Taiwan is a hyper endemic area for the Hepatitis B
virus (HBV). The estimated total number of HBsAg carriers in the
general population who are more than 20 years old is more than 3
million. Therefore, a case record review is conducted from January
2003 to June 2007 for all patients with a diagnosis of acute hepatitis
who were admitted to the Emergency Department (ED) of a
well-known teaching hospital. The cost for the use of medical
resources is defined as the total medical fee. In this study, principal
component analysis (PCA) is firstly employed to reduce the number of
dimensions. Support vector regression (SVR) and artificial neural
network (ANN) are then used to develop the forecasting model. A total
of 117 patients meet the inclusion criteria. 61% patients involved in
this study are hepatitis B related. The computational result shows that
the proposed PCA-SVR model has superior performance than other
compared algorithms. In conclusion, the Child-Pugh score and
echogram can both be used to predict the cost of medical resources for
patients with acute hepatitis in the ED.
Abstract: A model was constructed to predict the amount of
solar radiation that will make contact with the surface of the earth in
a given location an hour into the future. This project was supported
by the Southern Company to determine at what specific times during
a given day of the year solar panels could be relied upon to produce
energy in sufficient quantities. Due to their ability as universal
function approximators, an artificial neural network was used to
estimate the nonlinear pattern of solar radiation, which utilized
measurements of weather conditions collected at the Griffin, Georgia
weather station as inputs. A number of network configurations and
training strategies were utilized, though a multilayer perceptron with
a variety of hidden nodes trained with the resilient propagation
algorithm consistently yielded the most accurate predictions. In
addition, a modeled direct normal irradiance field and adjacent
weather station data were used to bolster prediction accuracy. In later
trials, the solar radiation field was preprocessed with a discrete
wavelet transform with the aim of removing noise from the
measurements. The current model provides predictions of solar
radiation with a mean square error of 0.0042, though ongoing efforts
are being made to further improve the model’s accuracy.
Abstract: Traditional document representation for classification
follows Bag of Words (BoW) approach to represent the term weights.
The conventional method uses the Vector Space Model (VSM) to
exploit the statistical information of terms in the documents and they
fail to address the semantic information as well as order of the terms
present in the documents. Although, the phrase based approach
follows the order of the terms present in the documents rather than
semantics behind the word. Therefore, a semantic concept based
approach is used in this paper for enhancing the semantics by
incorporating the ontology information. In this paper a novel method
is proposed to forecast the intraday stock market price directional
movement based on the sentiments from Twitter and money control
news articles. The stock market forecasting is a very difficult and
highly complicated task because it is affected by many factors such
as economic conditions, political events and investor’s sentiment etc.
The stock market series are generally dynamic, nonparametric, noisy
and chaotic by nature. The sentiment analysis along with wisdom of
crowds can automatically compute the collective intelligence of
future performance in many areas like stock market, box office sales
and election outcomes. The proposed method utilizes collective
sentiments for stock market to predict the stock price directional
movements. The collective sentiments in the above social media have
powerful prediction on the stock price directional movements as
up/down by using Granger Causality test.
Abstract: Modeling and forecasting dynamics of rainfall
occurrences constitute one of the major topics, which have been
largely treated by statisticians, hydrologists, climatologists and many
other groups of scientists. In the same issue, we propose, in the
present paper, a new hybrid method, which combines Extreme
Values and fractal theories. We illustrate the use of our methodology
for transformed Emberger Index series, constructed basing on data
recorded in Oujda (Morocco).
The index is treated at first by Peaks Over Threshold (POT)
approach, to identify excess observations over an optimal threshold u.
In the second step, we consider the resulting excess as a fractal object
included in one dimensional space of time. We identify fractal
dimension by the box counting. We discuss the prospect descriptions
of rainfall data sets under Generalized Pareto Distribution, assured by
Extreme Values Theory (EVT). We show that, despite of the
appropriateness of return periods given by POT approach, the
introduction of fractal dimension provides accurate interpretation
results, which can ameliorate apprehension of rainfall occurrences.
Abstract: The effects of hypertension are often lethal thus its
early detection and prevention is very important for everybody. In
this paper, a neural network (NN) model was developed and trained
based on a dataset of hypertension causative parameters in order to
forecast the likelihood of occurrence of hypertension in patients. Our
research goal was to analyze the potential of the presented NN to
predict, for a period of time, the risk of hypertension or the risk of
developing this disease for patients that are or not currently
hypertensive. The results of the analysis for a given patient can
support doctors in taking pro-active measures for averting the
occurrence of hypertension such as recommendations regarding the
patient behavior in order to lower his hypertension risk. Moreover,
the paper envisages a set of three example scenarios in order to
determine the age when the patient becomes hypertensive, i.e.
determine the threshold for hypertensive age, to analyze what
happens if the threshold hypertensive age is set to a certain age and
the weight of the patient if being varied, and, to set the ideal weight
for the patient and analyze what happens with the threshold of
hypertensive age.
Abstract: In this work, we report, a systematic study on the
structural and optical properties of Pr-doped ZnO nanostructures and
PVA:Zn98Pr2O polymer matrix nanocomposites free standing films.
These particles are synthesized through simple wet chemical route
and solution casting technique at room temperature, respectively.
Structural studies carried out by X-ray diffraction method confirm
that the prepared pure ZnO and Pr doped ZnO nanostructures are in
hexagonal wurtzite structure and the microstrain is increased upon
doping. TEM analysis reveals that the prepared materials are in sheet
like nature. Absorption spectra show free excitonic absorption band
at 370 nm and red shift for the Pr doped ZnO nanostructures. The
PVA:Zn98Pr2O composite film exhibits both free excitonic and PVA
absorption bands at 282 nm. Fourier transform infrared spectral
studies confirm the presence of A1 (TO) and E1 (TO) modes of Zn-O
bond vibration and the formation of polymer composite materials.
Abstract: The aim of this paper is to select the most accurate
forecasting method for predicting the future values of the
unemployment rate in selected European countries. In order to do so,
several forecasting techniques adequate for forecasting time series
with trend component, were selected, namely: double exponential
smoothing (also known as Holt`s method) and Holt-Winters` method
which accounts for trend and seasonality. The results of the empirical
analysis showed that the optimal model for forecasting
unemployment rate in Greece was Holt-Winters` additive method. In
the case of Spain, according to MAPE, the optimal model was double
exponential smoothing model. Furthermore, for Croatia and Italy the
best forecasting model for unemployment rate was Holt-Winters`
multiplicative model, whereas in the case of Portugal the best model
to forecast unemployment rate was Double exponential smoothing
model. Our findings are in line with European Commission
unemployment rate estimates.
Abstract: This research was conducted in the Mae Sot
Watershed where located in the Moei River Basin at the Upper
Salween River Basin in Tak Province, Thailand. The Mae Sot
Municipality is the largest urban area in Tak Province and situated in
the midstream of the Mae Sot Watershed. It usually faces flash flood
problem after heavy rain due to poor flood management has been
reported since economic rapidly bloom up in recent years. Its
catchment can be classified as ungauged basin with lack of rainfall
data and no any stream gaging station was reported. It was attached
by most severely flood events in 2013 as the worst studied case for
all those communities in this municipality. Moreover, other problems
are also faced in this watershed, such shortage water supply for
domestic consumption and agriculture utilizations including a
deterioration of water quality and landslide as well. The research
aimed to increase capability building and strengthening the
participation of those local community leaders and related agencies to
conduct better water management in urban area was started by mean
of the data collection and illustration of the appropriated application
of some short period rainfall forecasting model as they aim for better
flood relief plan and management through the hydrologic model
system and river analysis system programs. The authors intended to
apply the global rainfall data via the integrated data viewer (IDV)
program from the Unidata with the aim for rainfall forecasting in a
short period of 7-10 days in advance during rainy season instead of
real time record. The IDV product can be present in an advance
period of rainfall with time step of 3-6 hours was introduced to the
communities. The result can be used as input data to the hydrologic
modeling system model (HEC-HMS) for synthesizing flood
hydrographs and use for flood forecasting as well. The authors
applied the river analysis system model (HEC-RAS) to present flood
flow behaviors in the reach of the Mae Sot stream via the downtown
of the Mae Sot City as flood extents as the water surface level at
every cross-sectional profiles of the stream. Both models of HMS and
RAS were tested in 2013 with observed rainfall and inflow-outflow
data from the Mae Sot Dam. The result of HMS showed fit to the
observed data at the dam and applied at upstream boundary discharge
to RAS in order to simulate flood extents and tested in the field, and
the result found satisfying. The product of rainfall from IDV was fair
while compared with observed data. However, it is an appropriate
tool to use in the ungauged catchment to use with flood hydrograph
and river analysis models for future efficient flood relief plan and
management.
Abstract: Sound exposure effects have been investigated by
broadcasting a group of broilers with sound of Quran verses (Group
B) whereas the other group is the control broilers (Group C). The
growth rate comparisons in terms of weight and raw meat texture
measured by shear force have been investigated. Twenty-seven
broilers were randomly selected from each group on Day 24 and
weight measurement was carried out every week till the harvest day
(Day 39).Group B showed a higher mean weight on Day 24 (1.441 ±
0.013 kg) than Group C. Significant difference in the weight on Day
39 existed for Group B compared to Group C (p < 0.05). However,
there was no significant (p >0.05) difference of shear force in the
same muscles (breast and drumstick raw meat) of both groups but the
shear force of the breast meat for Group B and C broilers was lower
(p < 0.05) than that of their drumstick meat. Thus, broadcasting the
sound of Quran verses in the coop can be applied to improve the
growth rate of broilers for producing better quality poultry.
Abstract: Many aluminum motorcycle parts produced by a high
pressure die casting. Some parts such as fuel caps were a thin and
complex shape. This part risked for porosities and blisters on surface
if it only depended on an experience of mold makers for mold design.
This research attempted to use CAST-DESIGNER software
simulated the high pressure die casting process with the same process
parameters of a motorcycle fuel cap production. The simulated results
were compared with fuel cap products and expressed the same
porosity and blister locations on cap surface. An average of absolute
difference of simulated results was obtained 0.094 mm when
compared the simulated porosity and blister defect sizes on the fuel
cap surfaces with the experimental micro photography. This
comparison confirmed an accuracy of software and will use the
setting parameters to improve fuel cap molds in the further work.
Abstract: Load modeling is one of the central functions in
power systems operations. Electricity cannot be stored, which means
that for electric utility, the estimate of the future demand is necessary
in managing the production and purchasing in an economically
reasonable way. A majority of the recently reported approaches are
based on neural network. The attraction of the methods lies in the
assumption that neural networks are able to learn properties of the
load. However, the development of the methods is not finished, and
the lack of comparative results on different model variations is a
problem. This paper presents a new approach in order to predict the
Tunisia daily peak load. The proposed method employs a
computational intelligence scheme based on the Fuzzy neural
network (FNN) and support vector regression (SVR). Experimental
results obtained indicate that our proposed FNN-SVR technique gives
significantly good prediction accuracy compared to some classical
techniques.
Abstract: The present study was undertaken to investigate the
effect of aging parameters (time and temperature) on the mechanical
properties of Be-and/or Zr- treated Al-Mg-Zn (7075) alloys. Ultimate
tensile strength, 0.5% offset yield strength and % elongation
measurements were carried out on specimens prepared from cast and
heat treated 7075 alloys containing Be and/or Zr. Different aging
treatment were carried out for the as solution treated (SHT)
specimens (after quenching in warm water). The specimens were
aged at different conditions; Natural and artificial aging was carried
out at room temperature, 120C, 150C, 180C and 220C for different
periods of time. Duplex aging was performed for SHT conditions
(pre-aged at different time and temperature followed by high
temperature aging). Ultimate tensile strength, yield strength and %
elongation data results as a function of different aging parameters are
analysed. A statistical design of experiments (DOE) approach using
fractional factorial design is applied to acquire an understanding of
the effects of these variables and their interactions on the mechanical
properties of Be- and/or Zr- treated 7075 alloys. Mathematical
models are developed to relate the alloy mechanical properties with
the different aging parameters.
Abstract: The purpose of this study is to forecast the influences
of information and communication technology (ICT) on the structural
changes of Japanese economies. In this study, input-output (IO) and
statistical approaches are used as analysis instruments. More
specifically, this study employs Leontief IO coefficients and
constrained multivariate regression (CMR) model in order to achieve
the purpose. The periods of initial and forecast in this study are 2005
and 2015, respectively. In this study, ICT is represented by ICT capital
stocks. This study conducts two levels of analysis, namely macro and
micro. The results of macro level analysis show that the dynamics of
Japanese economies on the forecast period, relative to the initial period,
are not so high. We focus on (1) commerce, (2) business services and
office supplies, and (3) personal services sectors when conducting the
analysis of the micro level. Further, we analyze its specific IO
coefficients when doing this analysis. The results of the analysis
explain that ICT gives a strong influence on the changes of these
coefficients from initial to forecast periods.
Abstract: The rate of natural gas dissociation from the Coal
Matrix depends on depressurization of reservoir through removing of
the cleat water from the coal seam. These waters are similar to brine
and aged of very long years. For improving the connectivity through
fracking /fracturing, high pressure liquids are pumped off inside the
coal body. A significant quantity of accumulated water, a combined
mixture of cleat water and fracking fluids (back flow water) is
pumped out through gas well. In Queensland, Australia Coal Seam
Gas (CSG) industry is in booming state and estimated of 30,000 wells
would be active for CSG production forecasting life span of 30 years.
Integrated water management along with water softening programs is
practiced for subsequent treatment and later on discharge to nearby
surface water catchment. Water treatment is an important part of the
CSG industry. A case study on a CSG site and review on the test
results are discussed for assessing the Standards & Practices for
management of CSG by-product water and their subsequent disposal
activities. This study was directed toward (i) water management and
softening process in Spring Gully CSG field, (ii) Comparative
analysis on experimental study and standards and (iii) Disposal of the
treated water. This study also aimed for alternative usages and their
impact on vegetation, living species as well as long term effects.
Abstract: Replacement of plastics used in the food industry
seems to be a serious issue to overcome mainly the environmental
problems in recent years. This study investigates the hydrophilicity
and permeability properties of starch biopolymer which ethylene
vinyl alcohol (EVOH) (0-10%) and nanocrystalline cellulose (NCC)
(1-15%) were used to enhance its properties. Starch -EVOH
nanocomposites were prepared by casting method in different
formulations. NCC production by acid hydrolysis was confirmed by
scanning electron microscopy. Solubility, water vapor permeability,
water vapor transmission rate and moisture absorbance were
measured on each of the nanocomposites. The results were analyzed
by SAS software. The lowest moisture absorbance was measured in
pure starch nanocomposite containing 8% NCC. The lowest
permeability to water vapor belongs to starch nanocomposite
containing 8% NCC and the sample containing 7.8% EVOH and 13%
NCC. Also the lowest solubility was observed in the composite
contains the highest amount of EVOH. Applied Process resulted in
production of bio films which have good resistance to water vapor
permeability and solubility in water. The use of NCC and EVOH
leads to reduced moisture absorbance property of the biofilms.
Abstract: Proof of controlling crack width is a basic condition
for securing suitable performance in serviceability limit state. The
cracking in concrete can occur at any time from the casting of time to
the years after the concrete has been set in place. Most codes struggle
with offering procedure for crack width calculation. There is lack in
availability of design charts for designers to compute crack width
with ease. The focus of the study is to utilize design charts and
parametric equations in calculating crack width with minimum error.
The paper contains a simplified procedure to calculate crack width
for reinforced concrete (RC) sections subjected to bending with axial
tensile force following the guidelines of Euro code [DS EN-1992-1-1
& DS EN-1992-1-2]. Numerical examples demonstrate the
application of the suggested procedure. Comparison with parallel
analytical tools supports the validity of result and show the
percentage deviation of crack width in both the procedures. The
technique is simple, user friendly and ready to evolve for a greater
spectrum of section sizes and materials.
Abstract: The IEEE 802.22 working group aims to drive the
Digital Video Broadcasting-Terrestrial (DVB-T) bands for data
communication to the rural area without interfering the TV broadcast.
In this paper, we arrive at a closed-form expression for average
detection probability of Fusion center (FC) with multiple antenna
over the κ − μ fading channel model. We consider a centralized
cooperative multiple antenna network for reporting. The DVB-T
samples forwarded by the secondary user (SU) were combined using
Maximum ratio combiner at FC, an energy detection is performed
to make the decision. The fading effects of the channel degrades
the detection probability of the FC, a generalized independent and
identically distributed (IID) κ − μ and an additive white Gaussian
noise (AWGN) channel is considered for reporting and sensing
respectively. The proposed system performance is verified through
simulation results.
Abstract: At present, the evaluation of voltage stability
assessment experiences sizeable anxiety in the safe operation of
power systems. This is due to the complications of a strain power
system. With the snowballing of power demand by the consumers
and also the restricted amount of power sources, therefore, the system
has to perform at its maximum proficiency. Consequently, the
noteworthy to discover the maximum ability boundary prior to
voltage collapse should be undertaken. A preliminary warning can be
perceived to evade the interruption of power system’s capacity. The
effectiveness of line voltage stability indices (LVSI) is differentiated
in this paper. The main purpose of the indices used is to predict the
proximity of voltage instability of the electric power system. On the
other hand, the indices are also able to decide the weakest load buses
which are close to voltage collapse in the power system. The line
stability indices are assessed using the IEEE 14 bus test system to
validate its practicability. Results demonstrated that the implemented
indices are practically relevant in predicting the manifestation of
voltage collapse in the system. Therefore, essential actions can be
taken to dodge the incident from arising.