Abstract: In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.
Abstract: An accuracy nonlinear analysis of a deep beam resting on elastic perfectly plastic soil is carried out in this study. In fact, a nonlinear finite element modeling for large deflection and moderate rotation of Euler-Bernoulli beam resting on linear and nonlinear random soil is investigated. The geometric nonlinear analysis of the beam is based on the theory of von Kàrmàn, where the Newton-Raphson incremental iteration method is implemented in a Matlab code to solve the nonlinear equation of the soil-beam interaction system. However, two analyses (deterministic and probabilistic) are proposed to verify the accuracy and the efficiency of the proposed model where the theory of the local average based on the Monte Carlo approach is used to analyze the effect of the spatial variability of the soil properties on the nonlinear beam response. The effect of six main parameters are investigated: the external load, the length of a beam, the coefficient of subgrade reaction of the soil, the Young’s modulus of the beam, the coefficient of variation and the correlation length of the soil’s coefficient of subgrade reaction. A comparison between the beam resting on linear and nonlinear soil models is presented for different beam’s length and external load. Numerical results have been obtained for the combination of the geometric nonlinearity of beam and material nonlinearity of random soil. This comparison highlighted the need of including the material nonlinearity and spatial variability of the soil in the geometric nonlinear analysis, when the beam undergoes large deflections.
Abstract: Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.
Abstract: Microstructure and fabric of soils play an important
role on structural properties e.g. stiffness and strength of compacted
earthwork. Traditional quality control monitoring based on moisturedensity
tests neither reflects the variability of soil microstructure nor
provides a direct assessment of structural property, which is the
ultimate objective of the earthwork quality control. Since stiffness
and strength are sensitive to soil microstructure and fabric, any
independent test methods that provide simple, rapid, and direct
measurement of stiffness and strength are anticipated to provide an
effective assessment of compacted earthen materials’ uniformity. In
this study, the soil stiffness gauge (SSG) and the dynamic cone
penetrometer (DCP) were respectively utilized to measure and
monitor the stiffness and strength in companion with traditional
moisture-density measurements of various earthen materials used in
Thailand road construction projects. The practical earthwork quality
control criteria are presented herein in order to assure proper
earthwork quality control and uniform structural property of
compacted earthworks.
Abstract: The early-stage damage detection in offshore
structures requires continuous structural health monitoring and for the
large area the position of sensors will also plays an important role in
the efficient damage detection. Determining the dynamic behavior of
offshore structures requires dense deployment of sensors. The wired
Structural Health Monitoring (SHM) systems are highly expensive
and always needs larger installation space to deploy. Wireless sensor
networks can enhance the SHM system by deployment of scalable
sensor network, which consumes lesser space. This paper presents the
results of wireless sensor network based Structural Health Monitoring
method applied to a scaled experimental model of offshore structure
that underwent wave loading. This method determines the
serviceability of the offshore structure which is subjected to various
environment loads. Wired and wireless sensors were installed in the
model and the response of the scaled BLSRP model under wave
loading was recorded. The wireless system discussed in this study is
the Raspberry pi board with Arm V6 processor which is programmed
to transmit the data acquired by the sensor to the server using Wi-Fi
adapter, the data is then hosted in the webpage. The data acquired
from the wireless and wired SHM systems were compared and the
design of the wireless system is verified.
Abstract: The purpose of this study is to analyze the temporal
and spatial variability of thermal conditions in the Republic of
Armenia. The paper describes annual fluctuations in air temperature.
Research has been focused on case study region of Armenia and
surrounding areas, where long–term measurements and observations
of weather conditions have been performed within the National
Meteorological Service of Armenia and its surrounding areas. The
study contains yearly air temperature data recorded between 1961-
2012. Mann-Kendal test and the autocorrelation function were
applied to detect the change trend of annual mean temperature, as
well as other parametric and non-parametric tests searching to find
the presence of some breaks in the long term evolution of
temperature. The analysis of all records reveals a tendency mostly
towards warmer years, with increased temperatures especially in
valleys and inner basins. The maximum temperature increase is up to
1,5°C. Negative results have not been observed in Armenia. The
patterns of temperature change have been observed since the 1990’s
over much of the Armenian territory. The climate in Armenia was
influenced by global change in the last 2 decades, as results from the
methods employed within the study.
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: Construction industry plays a vital role in the
economy of the world. However, due to high uncertainty and
variability in the industry, its performance is not as efficient in terms
of quality, lead times, productivity and costs as of other industries.
Moreover, there are continuous conflicts among the different actors
in the construction supply chains in terms of profit sharing. Previous
studies suggested partnership as an important approach to promote
cooperation among the different actors in the construction supply
chains and thereby it improves the overall performance. Construction
practitioners tried to focus on partnership which can enhance the
performance of construction supply chains but they are not fully
aware of different approaches and techniques for improving
partnership. In this research, a systematic review on partnership in
relation to construction supply chains is carried out to understand
different elements influencing the partnership. The research
development of this domain is analyzed by reviewing selected
articles published from 1996 to 2015. Based on the papers, three
major elements influencing partnership in construction supply chains
are identified: ‘Lean approach’, ‘Relationship building’ and ‘E-commerce
applications’. This study analyses the contributions in the
areas within each element and provides suggestions for future
developments of partnership in construction supply chains.
Abstract: The knitted fabric suffers a deformation in its
dimensions due to stretching and tension factors, transverse and
longitudinal respectively, during the process in rectilinear knitting
machines so it performs a dry relaxation shrinkage procedure and
thermal action of prefixed to obtain stable conditions in the knitting.
This paper presents a dry relaxation shrinkage prediction of Bordeaux
fiber using a feed forward neural network and linear regression
models. Six operational alternatives of shrinkage were predicted. A
comparison of the results was performed finding neural network
models with higher levels of explanation of the variability and
prediction. The presence of different reposes is included. The models
were obtained through a neural toolbox of Matlab and Minitab
software with real data in a knitting company of Southern
Guanajuato. The results allow predicting dry relaxation shrinkage of
each alternative operation.
Abstract: Heart is the most important part in the body of living
organisms. It affects and is affected by any factor in the body.
Therefore, it is a good detector for all conditions in the body. Heart
signal is a non-stationary signal; thus, it is utmost important to study
the variability of heart signal. The Heart Rate Variability (HRV) has
attracted considerable attention in psychology, medicine and has
become important dependent measure in psychophysiology and
behavioral medicine. The standards of measurements, physiological
interpretation and clinical use for HRV that are most often used were
described in many researcher papers, however, remain complex
issues are fraught with pitfalls. This paper presents one of the nonlinear
techniques to analyze HRV. It discusses many points like, what
Poincaré plot is and how Poincaré plot works; also, Poincaré plot's
merits especially in HRV. Besides, it discusses the limitation of
Poincaré cause of standard deviation SD1, SD2 and how to overcome
this limitation by using complex correlation measure (CCM). The
CCM is most sensitive to changes in temporal structure of the
Poincaré plot as compared toSD1 and SD2.
Abstract: This paper aims to determine Fundamental Natural
Frequency (FNF) of a structural composite floor system known as
Chromite. To achieve this purpose, FNFs of studied panels are
determined by development of Finite Element Models (FEMs) in
ABAQUS program. American Institute of Steel Construction (AISC)
code in Steel Design Guide Series 11 presents a fundamental formula
to calculate FNF of a steel framed floor system. This formula has
been used to verify results of the FEMs. The variability in the FNF of
the studied system under various parameters such as dimensions of
floor, boundary conditions, rigidity of main and secondary beams
around the floor, thickness of concrete slab, height of composite
joists, distance between composite joists, thickness of top and bottom
flanges of the open web steel joists, and adding tie beam
perpendicular on the composite joists, is determined. The results
show that changing in dimensions of the system, its boundary
conditions, rigidity of main beam, and also adding tie beam,
significant changes the FNF of the system up to 452.9%, 50.8%, -
52.2%, %52.6%, respectively. In addition, increasing thickness of
concrete slab increases the FNF of the system up to 10.8%.
Furthermore, the results demonstrate that variation in rigidity of
secondary beam, height of composite joist, and distance between
composite joists, and thickness of top and bottom flanges of open
web steel joists insignificant changes the FNF of the studied system
up to -0.02%, -3%, -6.1%, and 0.96%, respectively. Finally, the
results of this study help designer predict occurrence of resonance,
comfortableness, and design criteria of the studied system.
Abstract: Work presented is interested in the characterization of
the quasistatic mechanical properties and in fatigue of a composite
laminated in jute/epoxy. The natural fibers offer promising prospects
thanks to their interesting specific properties, because of their low
density, but also with their bio-deterioration. Several scientific
studies highlighted the good mechanical resistance of the vegetable
fiber composites reinforced, even after several recycling. Because of
the environmental standards that become increasingly severe, one
attends the emergence of eco-materials at the base of natural fibers
such as flax, bamboo, hemp, sisal, jute. The fatigue tests on
elementary vegetable fibers show an increase of about 60% of the
rigidity of elementary fibers of hemp subjected to cyclic loadings. In
this study, the test-tubes manufactured by the method infusion have
sequences of stacking of 0/90° and ± 45° for the shearing and tensile
tests. The quasistatic tests reveal a variability of the mechanical
properties of about 8%. The tensile fatigue tests were carried out for
levels of constraints equivalent to half of the ultimate values of the
composite. Once the fatigue tests carried out for well-defined values
of cycles, a series of static tests of traction type highlights the
influence of the number of cycles on the quasi-static mechanical
behavior of the laminate jute/epoxy.
Abstract: This paper presents a methodology for probabilistic
assessment of bearing capacity and prediction of failure mechanism
of masonry vaults at the ultimate state with consideration of the
natural variability of Young’s modulus of stones. First, the
computation model is explained. The failure mode corresponds to the
four-hinge mechanism. Based on this consideration, the study of a
vault composed of 16 segments is presented. The Young’s modulus of
the segments is considered as random variable defined by a mean
value and a coefficient of variation. A relationship linking the vault
bearing capacity to the voussoirs modulus variation is proposed. The
most probable failure mechanisms, in addition to that observed in the
deterministic case, are identified for each variability level as well as
their probability of occurrence. The results show that the mechanism
observed in the deterministic case has decreasing probability of
occurrence in terms of variability, while the number of other
mechanisms and their probability of occurrence increases with the
coefficient of variation of Young’s modulus. This means that if a
significant change in the Young’s modulus of the segments is proven,
taking it into account in computations becomes mandatory, both for
determining the vault bearing capacity and for predicting its failure
mechanism.
Abstract: The Northeast China (NEC) was the most important
agriculture areas and known as the Golden-Maize-Belt. Based on
observed crop data and crop model, we design four simulating
experiments and separate relative impacts and contribution under
climate change, planting date shift, and varieties change as well
change of varieties and planting date. Without planting date and
varieties change, maize yields had no significant change trend at
Hailun station located in the north of NEC, and presented significant
decrease by 0.2 - 0.4 t/10a at two stations, which located in the middle
and the south of NEC. With planting date change, yields showed a
significant increase by 0.09 - 0.47 t/10a. With varieties change, maize
yields had significant increase by 1.8~ 1.9 t/10a at Hailun and Huadian
stations, but a non-significant and low increase by 0.2t /10a at Benxi
located in the south of NEC. With change of varieties and planting
date, yields presented a significant increasing by 0.53- 2.0 t/10a. Their
contribution to yields was -25% ~ -55% for climate change, 15% ~
35% for planting date change, and 20% ~110% for varieties change as
well 30% ~135% for varieties with planting date shift. It found that
change in varieties and planting date were highest yields and were
responsible for significant increases in maize yields, varieties was
secondly, and planting date was thirdly. It found that adaptation in
varieties and planting date greatly improved maize yields, and
increased yields annual variability. The increase of contribution with
planting date and varieties change in 2000s was lower than in 1990s.
Yields with the varieties change and yields with planting date and
varieties change all showed a decreasing trend at Huadian and Benxi
since 2002 or so. It indicated that maize yields increasing trend
stagnated in the middle and south of NEC, and continued in the north
of NEC.
Abstract: Accurate forecasting of fresh produce demand is one
the challenges faced by Small Medium Enterprise (SME)
wholesalers. This paper is an attempt to understand the cause for the
high level of variability such as weather, holidays etc., in demand of
SME wholesalers. Therefore, understanding the significance of
unidentified factors may improve the forecasting accuracy. This
paper presents the current literature on the factors used to predict
demand and the existing forecasting techniques of short shelf life
products. It then investigates a variety of internal and external
possible factors, some of which is not used by other researchers in the
demand prediction process. The results presented in this paper are
further analysed using a number of techniques to minimize noise in
the data. For the analysis past sales data (January 2009 to May 2014)
from a UK based SME wholesaler is used and the results presented
are limited to product ‘Milk’ focused on café’s in derby. The
correlation analysis is done to check the dependencies of variability
factor on the actual demand. Further PCA analysis is done to
understand the significance of factors identified using correlation.
The PCA results suggest that the cloud cover, weather summary and
temperature are the most significant factors that can be used in
forecasting the demand. The correlation of the above three factors
increased relative to monthly and becomes more stable compared to
the weekly and daily demand.
Abstract: It is necessary to predict a fatigue crack propagation
life for estimation of structural integrity. Because of an uncertainty
and a randomness of a structural behavior, it is also required to
analyze stochastic characteristics of the fatigue crack propagation life
at a specified fatigue crack size. The essential purpose of this study is to find the effect of load ratio
on probability distribution of the fatigue crack propagation life at a
specified grown crack size and to confirm the good probability
distribution in magnesium alloys under various fatigue load ratio
conditions. To investigate a stochastic crack growth behavior, fatigue
crack propagation experiments are performed in laboratory air under
several conditions of fatigue load ratio using AZ31. By Anderson-Darling test, a goodness-of-fit test for probability
distribution of the fatigue crack propagation life is performed. The
effect of load ratio on variability of fatigue crack propagation life is
also investigated.
Abstract: We used live E. coli containing synthetic genetic
oscillators to study how the degree of synchrony between the genetic
circuits of sister cells changes with temperature. We found that both
the mean and the variability of the degree of synchrony between the
fluorescence signals from sister cells are affected by temperature.
Also, while most pairs of sister cells were found to be highly
synchronous in each condition, the number of asynchronous pairs
increased with increasing temperature, which was found to be due to
disruptions in the oscillations. Finally we provide evidence that these
disruptions tend to affect multiple generations as opposed to
individual cells. These findings provide insight in how to design
more robust synthetic circuits and in how cell division can affect their
dynamics.
Abstract: The paper is focused on monitoring of dependencies
of different composition concretes on elastic modulus values.
To obtain a summary of elastic modulus development in dependence
of concrete composition design variability was the objective
of the experiment. Essential part of this work was initiated
as a reaction to building practice when questions of elastic moduli
arose at the same time and which mostly did not obtain the required
and expected values from concrete constructions.
Abstract: Some plants of genus Schinus have been used in the
folk medicine as topical antiseptic, digestive, purgative, diuretic,
analgesic or antidepressant, and also for respiratory and urinary
infections. Chemical composition of essential oils of S. molle and S.
terebinthifolius had been evaluated and presented high variability
according with the part of the plant studied and with the geographic
and climatic regions. The pharmacological properties, namely
antimicrobial, anti-tumoural and anti-inflammatory activities are
conditioned by chemical composition of essential oils. Taking into
account the difficulty to infer the pharmacological properties of
Schinus essential oils without hard experimental approach, this work
will focus on the development of a decision support system, in terms
of its knowledge representation and reasoning procedures, under a
formal framework based on Logic Programming, complemented with
an approach to computing centered on Artificial Neural Networks
and the respective Degree-of-Confidence that one has on such an
occurrence.
Abstract: We proposed a Hyperbolic Gompertz Growth Model
(HGGM), which was developed by introducing a shape parameter
(allometric). This was achieved by convoluting hyperbolic sine
function on the intrinsic rate of growth in the classical gompertz
growth equation. The resulting integral solution obtained
deterministically was reprogrammed into a statistical model and used
in modeling the height and diameter of Pines (Pinus caribaea). Its
ability in model prediction was compared with the classical gompertz
growth model, an approach which mimicked the natural variability of
height/diameter increment with respect to age and therefore provides
a more realistic height/diameter predictions using goodness of fit
tests and model selection criteria. The Kolmogorov Smirnov test and
Shapiro-Wilk test was also used to test the compliance of the error
term to normality assumptions while the independence of the error
term was confirmed using the runs test. The mean function of top
height/Dbh over age using the two models under study predicted
closely the observed values of top height/Dbh in the hyperbolic
gompertz growth models better than the source model (classical
gompertz growth model) while the results of R2, Adj. R2, MSE and
AIC confirmed the predictive power of the Hyperbolic Gompertz
growth models over its source model.