Abstract: We present probabilistic multinomial Dirichlet
classification model for multidimensional data and Gaussian process
priors. Here, we have considered efficient computational method that
can be used to obtain the approximate posteriors for latent variables
and parameters needed to define the multiclass Gaussian process
classification model. We first investigated the process of inducing a
posterior distribution for various parameters and latent function by
using the variational Bayesian approximations and important sampling
method, and next we derived a predictive distribution of latent
function needed to classify new samples. The proposed model is
applied to classify the synthetic multivariate dataset in order to verify
the performance of our model. Experiment result shows that our model
is more accurate than the other approximation methods.
Abstract: Project Portfolio Management (PPM) is an essential
component of an organisation’s strategic procedures, which requires
attention of several factors to envisage a range of long-term outcomes
to support strategic project portfolio decisions. To evaluate overall
efficiency at the portfolio level, it is essential to identify the
functionality of specific projects as well as to aggregate those
findings in a mathematically meaningful manner that indicates the
strategic significance of the associated projects at a number of levels
of abstraction. PPM success is directly associated with the quality of
decisions made and poor judgment increases portfolio costs. Hence,
various Multi-Criteria Decision Making (MCDM) techniques have
been designed and employed to support the decision-making
functions. This paper reviews possible options to enhance the
decision-making outcomes in organisational portfolio management
processes using the Analytic Hierarchy Process (AHP) both from
academic and practical perspectives and will examine the usability,
certainty and quality of the technique. The results of the study will
also provide insight into the technical risk associated with current
decision-making model to underpin initiative tracking and strategic
portfolio management.
Abstract: The power electronic components within Electric Vehicles (EV) need to operate in several important modes. Some modes directly influence safety, while others influence vehicle performance. Given the variety of functions and operational modes required of the power electronics, it needs to meet efficiency requirements to minimize power losses. Another challenge in the control and construction of such systems is the ability to support bidirectional power flow. This paper considers the construction, operation, and feasibility of available converters for electric vehicles with feasible configurations of electrical buses and loads. This paper describes logic and control signals for the converters for different operations conditions based on the efficiency and energy usage bases.
Abstract: In this paper, a robust fault detection and isolation
(FDI) scheme is developed to monitor a multivariable nonlinear
chemical process called the Chylla-Haase polymerization reactor,
when it is under the cascade PI control. The scheme employs a radial
basis function neural network (RBFNN) in an independent mode to
model the process dynamics, and using the weighted sum-squared
prediction error as the residual. The Recursive Orthogonal Least
Squares algorithm (ROLS) is employed to train the model to
overcome the training difficulty of the independent mode of the
network. Then, another RBFNN is used as a fault classifier to isolate
faults from different features involved in the residual vector. Several
actuator and sensor faults are simulated in a nonlinear simulation of
the reactor in Simulink. The scheme is used to detect and isolate the
faults on-line. The simulation results show the effectiveness of the
scheme even the process is subjected to disturbances and
uncertainties including significant changes in the monomer feed rate,
fouling factor, impurity factor, ambient temperature, and
measurement noise. The simulation results are presented to illustrate
the effectiveness and robustness of the proposed method.
Abstract: A model to predict the plastic zone size for material
under plane stress condition has been developed and verified
experimentally. The developed model is a function of crack size,
crack angle and material property (dislocation density). Simulation
and validation results show that the model developed show good
agreement with experimental results. Samples of low carbon steel
(0.035%C) with included surface crack angles of 45o, 50o, 60o, 70o
and 90o and crack depths of 2mm and 4mm were subjected to low
strain rate between 0.48 x 10-3 s-1 – 2.38 x 10-3 s-1. The mechanical
properties studied were ductility, tensile strength, modulus of
elasticity, yield strength, yield strain, stress at fracture and fracture
toughness. The experimental study shows that strain rate has no
appreciable effect on the size of plastic zone while crack depth and
crack angle plays an imperative role in determining the size of the
plastic zone of mild steel materials.
Abstract: The modelling of physical phenomena, such as the
earth’s free oscillations, the vibration of strings, the interaction of
atomic particles, or the steady state flow in a bar give rise to Sturm-
Liouville (SL) eigenvalue problems. The boundary applications of
some systems like the convection-diffusion equation, electromagnetic
and heat transfer problems requires the combination of Dirichlet and
Neumann boundary conditions. Hence, the incorporation of Robin
boundary condition in the analyses of Sturm-Liouville problem. This
paper deals with the computation of the eigenvalues and
eigenfunction of generalized Sturm-Liouville problems with Robin
boundary condition using the finite element method. Numerical
solution of classical Sturm–Liouville problem is presented. The
results show an agreement with the exact solution. High results
precision is achieved with higher number of elements.
Abstract: In this paper, we propose the variational EM inference
algorithm for the multi-class Gaussian process classification model
that can be used in the field of human behavior recognition. This
algorithm can drive simultaneously both a posterior distribution of a
latent function and estimators of hyper-parameters in a Gaussian
process classification model with multiclass. Our algorithm is based
on the Laplace approximation (LA) technique and variational EM
framework. This is performed in two steps: called expectation and
maximization steps. First, in the expectation step, using the Bayesian
formula and LA technique, we derive approximately the posterior
distribution of the latent function indicating the possibility that each
observation belongs to a certain class in the Gaussian process
classification model. Second, in the maximization step, using a derived
posterior distribution of latent function, we compute the maximum
likelihood estimator for hyper-parameters of a covariance matrix
necessary to define prior distribution for latent function. These two
steps iteratively repeat until a convergence condition satisfies.
Moreover, we apply the proposed algorithm with human action
classification problem using a public database, namely, the KTH
human action data set. Experimental results reveal that the proposed
algorithm shows good performance on this data set.
Abstract: The Com-Poisson (CMP) model is one of the most
popular discrete generalized linear models (GLMS) that handles
both equi-, over- and under-dispersed data. In longitudinal context,
an integer-valued autoregressive (INAR(1)) process that incorporates
covariate specification has been developed to model longitudinal
CMP counts. However, the joint likelihood CMP function is
difficult to specify and thus restricts the likelihood-based estimating
methodology. The joint generalized quasi-likelihood approach
(GQL-I) was instead considered but is rather computationally
intensive and may not even estimate the regression effects due
to a complex and frequently ill-conditioned covariance structure.
This paper proposes a new GQL approach for estimating the
regression parameters (GQL-III) that is based on a single score vector
representation. The performance of GQL-III is compared with GQL-I
and separate marginal GQLs (GQL-II) through some simulation
experiments and is proved to yield equally efficient estimates as
GQL-I and is far more computationally stable.
Abstract: The 1:1 cocrystal of 2-amino-4-chloro-6-
methylpyrimidine (2A4C6MP) with 4-methylbenzoic acid (4MBA)
(I) has been prepared by slow evaporation method in methanol,
which was crystallized in monoclinic C2/c space group, Z = 8, and a
= 28.431 (2) Å, b = 7.3098 (5) Å, c = 14.2622 (10) Å and β =
109.618 (3)°. The presence of unionized –COOH functional group in
cocrystal I was identified both by spectral methods (1H and 13C
NMR, FTIR) and X-ray diffraction structural analysis. The
2A4C6MP molecule interact with the carboxylic group of the
respective 4MBA molecule through N—H⋯O and O—H⋯N
hydrogen bonds, forming a cyclic hydrogen–bonded motif R2
2(8).
The crystal structure was stabilized by Npyrimidine—H⋯O=C and
C=O—H⋯Npyrimidine types hydrogen bonding interactions.
Theoretical investigations have been computed by HF and density
function (B3LYP) method with 6–311+G (d,p)basis set. The
vibrational frequencies together with 1H and 13C NMR chemical
shifts have been calculated on the fully optimized geometry of
cocrystal I. Theoretical calculations are in good agreement with the
experimental results. Solvent–free formation of this cocrystal I is
confirmed by powder X-ray diffraction analysis.
Abstract: It is very important for a developing nation to
developing their infrastructure on the prime priority because their
infrastructure particularly their roads and transportation functions as a
blood in the system. Almost 1.1 billion populations share the travel
and transportation industry in India. On the other hand, the Pakistan
transportation industry is also extensive and elevating about 170
million users of transportation. Indian and Pakistani specifically
within bus industry are well connected within and between the urban
and rural areas. The transportation industry is radically helping the
economic alleviation of both countries. Due to high economic
instability, unemployment and poverty rate both countries
governments are very serious and committed to help for boosting
their economy. They believe that any form of transportation
development would play a vital role in the development of land,
infrastructure which could indirectly support many other industries’
developments, such as tourism, freighting and shipping businesses,
just to mention a few. However, it seems that their previous
transportation planning in the due course has failed to meet the fast
growing demand. As with the span of time, both the countries are
looking forward to a long-term, and economical solutions, because
the demand is from time to time keep appreciating and reacting
according to other key economic drivers. Content analysis method
and case study approach is used in this paper and secondary data
from the bureau of statistic is used for case analysis. The paper
focused on the mobility concerns of the lower and middle-income
people in India and Pakistan. The paper is aimed to highlight the
weaknesses, opportunities and limitations resulting from low priority
industry for a government, which is making the either country's
public suffer. The paper has concluded that the main issue is
identified as the slow, inappropriate, and unfavorable decisions which
are not in favor of long-term country’s economic development and
public interest. The paper also recommends to future research
avenues for public and private transportation, which is continuously
failing to meet the public expectations.
Abstract: To maintain a healthy balanced loyalty, whether to art
or society, posits a debatable issue. The artist is always on the look
out for the potential tension between those two realms. Therefore,
one of the most painful dilemmas the artist finds is how to function in
a society without sacrificing the aesthetic values of his/her work. In
other words, the life-long awareness of failure which derives from the
concept of the artist as caught between unflattering social realities
and the need to invent genuine art forms becomes a fertilizing soil for
the artists to be tackled. Thus, within the framework of this dilemma,
the question of the responsibility of the artist and the relationship of
the art to politics will be illuminating. To a larger extent, however, in
drama, this dilemma is represented by the fictional characters of the
play. The present paper tackles the idea of the amorality of the artist in
selected plays by Tom Stoppard. However, Stoppard’s awareness of
his situation as a refugee has led him to keep at a distance from
politics. He tried hard to avoid any intervention into the realms of
political debate, especially in his earliest work. On the one hand, it is
not meant that he did not interest in politics as such, but rather he
preferred to question it than to create a fixed ideological position. On
the other hand, Stoppard’s refusal to intervene in politics is ascribed
to his feeling of gratitude to Britain where he settled. As a result,
Stoppard has frequently been criticized for a lack of political
engagement and also for not leaning too much for the left when he
does engage. His reaction to these public criticisms finds expression
in his self-conscious statements which defensively stressed the
artifice of his work. He, like Oscar Wilde thinks that the
responsibility of the artist is devoted to the realm of his/her art.
Consequently, his consciousness for the role of the artist is truly
reflected in his two plays, Artist Descending a Staircase (1972) and
Travesties (1974).
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: Machine visualization is an area of interest with fast
and progressive development. We present a method of machine
visualization which will be applicable in real industrial conditions
according to current needs and demands. Real factory data were
obtained in a newly built research plant. Methods described in this
paper were validated on a case study. Input data were processed and
the virtual environment was created. The environment contains
information about dimensions, structure, disposition, and function.
Hardware was enhanced by modular machines, prototypes, and
accessories. We added functionalities and machines into the virtual
environment. The user is able to interact with objects such as testing
and cutting machines, he/she can operate and move them. Proposed
design consists of an environment with two degrees of freedom of
movement. Users are in touch with items in the virtual world which
are embedded into the real surroundings. This paper describes development of the virtual environment. We
compared and tested various options of factory layout virtualization
and visualization. We analyzed possibilities of using a 3D scanner in
the layout obtaining process and we also analyzed various virtual
reality hardware visualization methods such as: Stereoscopic (CAVE)
projection, Head Mounted Display (HMD) and augmented reality
(AR) projection provided by see-through glasses.
Abstract: In order to investigate the prebiotic potential of
oligosaccharides prepared by chemical hydrolysis of water-soluble
polysaccharides (WSP) from Zizyphus lotus leaves, the effect of
oligosaccharides on bacterial growth was studied. The chemical
composition of WSP was evaluated by colorimetric assays revealed
the average values: 7.05±0.73% proteins and 86.21±0.74%
carbohydrates, among them 64.81±0.42% is neutral sugar and the rest
16.25±1.62% is uronic acids. The characterization of
monosaccharides was determined by high performance anion
exchange chromatography with pulsed amperometric detection
(HPAEC-PAD) was found to be composed of galactose (23.95%),
glucose (21.30%), rhamnose (20.28%), arabinose (9.55%), and
glucuronic acid (22.95%). The effects of oligosaccharides on the
growth of lactic acid bacteria were compared with those of fructooligosaccharide
(RP95). The oligosaccharides concentration was
1g/L of Man, Rogosa, Sharpe broth. Bacterial growth was assessed
during 2, 4.5, 6.5, 9, 12, 16 and 24 h by measuring the optical density
of the cultures at 600 nm (OD600) and pH values. During
fermentation, pH in broth cultures decreased from 6.7 to 5.87±0.15.
The enumeration of lactic acid bacteria indicated that
oligosaccharides led to a significant increase in bacteria (P≤0.05)
compared to the control. The fermentative metabolism appeared to be
faster on RP95 than on oligosaccharides from Zizyphus lotus leaves.
Both RP95 and oligosaccharides showed clear prebiotic effects, but
had differences in fermentation kinetics because of to the different
degree of polymerization. This study shows the prebiotic
effectiveness of oligosaccharides, and provides proof for the selection
of leaves of Zizyphus lotus for use as functional food ingredients.
Abstract: Lateral Geniculate Nucleus (LGN) is the relay center
in the visual pathway as it receives most of the input information
from retinal ganglion cells (RGC) and sends to visual cortex. Low
threshold calcium currents (IT) at the membrane are the unique
indicator to characterize this firing functionality of the LGN neurons
gained by the RGC input. According to the LGN functional
requirements such as functional mapping of RGC to LGN, the
morphologies of the LGN neurons were developed. During the
neurological disorders like glaucoma, the mapping between RGC and
LGN is disconnected and hence stimulating LGN electrically using
deep brain electrodes can restore the functionalities of LGN. A
computational model was developed for simulating the LGN neurons
with three predominant morphologies each representing different
functional mapping of RGC to LGN. The firings of action potentials
at LGN neuron due to IT were characterized by varying the
stimulation parameters, morphological parameters and orientation. A
wide range of stimulation parameters (stimulus amplitude, duration
and frequency) represents the various strengths of the electrical
stimulation with different morphological parameters (soma size,
dendrites size and structure). The orientation (0-1800) of LGN
neuron with respect to the stimulating electrode represents the angle
at which the extracellular deep brain stimulation towards LGN
neuron is performed. A reduced dendrite structure was used in the
model using Bush–Sejnowski algorithm to decrease the
computational time while conserving its input resistance and total
surface area. The major finding is that an input potential of 0.4 V is
required to produce the action potential in the LGN neuron which is
placed at 100 μm distance from the electrode. From this study, it can
be concluded that the neuroprostheses under design would need to
consider the capability of inducing at least 0.4V to produce action
potentials in LGN.
Abstract: Diets high in processed foods have been found to lack
essential micro-nutrients for optimum human development and
overall health. Some micro-nutrients such as copper (Cu) have been
found to enhance the inflammatory response through its oxidative
functions, thereby having a role in cardiovascular disease, metabolic
syndrome, diabetes and related complications. This research study
was designed to determine if food crops could be bio-fortified with
micro-nutrients by growing sprouts on mineral fortified fiber mats. In
the feasibility study described in this contribution, recycled cellulose
fibers and clay, saturated with either micro-nutrient copper ions or
copper nanoparticles, were converted to a novel mineral-cellulose
fiber carrier of essential micro-nutrient and of antimicrobial
properties. Seeds of Medicago sativa (alfalfa), purchased from a
commercial, organic supplier were germinated on engineered
cellulose fiber mats. After the appearance of the first leaves, the
sprouts were dehydrated and analyzed for Cu content. Nutrient
analysis showed ~2 increase in Cu of the sprouts grown on the fiber
mats with copper particles, and ~4 increase on mats with ionic copper
as compared to the control samples. This study illustrates the
potential for the use of engineered mats as a viable way to increase
the micro-nutrient composition of locally-grown food crops and the
need for additional research to determine the uptake, nutritional
implications and risks of micro-nutrient bio-fortification.
Abstract: Iranian architects had creative ways for constructing
the buildings in each climate. Some of these architectural elements
were made under the ground. Shovadan is one of these underground
spaces in hot-humid regions in Dezfoul and Shoushtar city that had
special functions and characteristics. In this paper some subjects such
as the history of Shovadan, its elements and effective factors in the
formation of Shovadan in Dezfool city are discussed.
Abstract: Noninvasive diagnostics of diseases via breath
analysis has attracted considerable scientific and clinical interest for
many years and become more and more promising with the rapid
advancements in nanotechnology and biotechnology. The volatile
organic compounds (VOCs) in exhaled breath, which are mainly
blood borne, particularly provide highly valuable information about
individuals’ physiological and pathophysiological conditions.
Additionally, breath analysis is noninvasive, real-time, painless, and
agreeable to patients. We have developed a wireless sensor array
based on single-stranded DNA (ssDNA)-functionalized single-walled
carbon nanotubes (SWNT) for the detection of a number of
physiological indicators in breath. Seven DNA sequences were used
to functionalize SWNT sensors to detect trace amount of methanol,
benzene, dimethyl sulfide, hydrogen sulfide, acetone, and ethanol,
which are indicators of heavy smoking, excessive drinking, and
diseases such as lung cancer, breast cancer, and diabetes. Our test
results indicated that DNA functionalized SWNT sensors exhibit
great selectivity, sensitivity, and repeatability; and different
molecules can be distinguished through pattern recognition enabled
by this sensor array. Furthermore, the experimental sensing results
are consistent with the Molecular Dynamics simulated ssDNAmolecular
target interaction rankings. Thus, the DNA-SWNT sensor
array has great potential to be applied in chemical or biomolecular
detection for the noninvasive diagnostics of diseases and personal
health monitoring.
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: A method of effective planning and control of
industrial facility energy consumption is offered. The method allows
optimally arranging the management and full control of complex
production facilities in accordance with the criteria of minimal
technical and economic losses at the forecasting control. The method
is based on the optimal construction of the power efficiency
characteristics with the prescribed accuracy. The problem of optimal
designing of the forecasting model is solved on the basis of three
criteria: maximizing the weighted sum of the points of forecasting
with the prescribed accuracy; the solving of the problem by the
standard principles at the incomplete statistic data on the basis of
minimization of the regularized function; minimizing the technical
and economic losses due to the forecasting errors.