Abstract: This paper addresses a cutting edge method of
business demand forecasting, based on an empirical probability
function when the historical behavior of the data is random.
Additionally, it presents error determination based on the numerical
method technique ‘propagation of errors.’ The methodology was
conducted characterization and process diagnostics demand planning
as part of the production management, then new ways to predict its
value through techniques of probability and to calculate their mistake
investigated, it was tools used numerical methods. All this based on
the behavior of the data. This analysis was determined considering
the specific business circumstances of a company in the sector of
communications, located in the city of Bogota, Colombia. In
conclusion, using this application it was possible to obtain the
adequate stock of the products required by the company to provide its
services, helping the company reduce its service time, increase the
client satisfaction rate, reduce stock which has not been in rotation
for a long time, code its inventory, and plan reorder points for the
replenishment of stock.
Abstract: Steady three-dimensional and two free surface waves
generated by moving bodies are presented, the flow problem to be
simulated is rich in complexity and poses many modeling challenges
because of the existence of breaking waves around the ship hull, and
because of the interaction of the two-phase flow with the turbulent
boundary layer. The results of several simulations are reported. The
first study was performed for NACA0012 of hydrofoil with different
meshes, this section is analyzed at h/c= 1, 0345 for 2D. In the second
simulation a mathematically defined Wigley hull form is used to
investigate the application of a commercial CFD code in prediction of
the total resistance and its components from tangential and normal
forces on the hull wetted surface. The computed resistance and wave
profiles are used to estimate the coefficient of the total resistance for
Wigley hull advancing in calm water under steady conditions. The
commercial CFD software FLUENT version 12 is used for the
computations in the present study. The calculated grid is established
using the code computer GAMBIT 2.3.26. The shear stress k-ωSST
model is used for turbulence modeling and the volume of fluid
technique is employed to simulate the free-surface motion. The
second order upwind scheme is used for discretizing the convection
terms in the momentum transport equations, the Modified HRIC
scheme for VOF discretization. The results obtained compare well
with the experimental data.
Abstract: Fast speed drives for Permanent Magnet Synchronous
Motor (PMSM) is a crucial performance for the electric traction
systems. In this paper, PMSM is derived with a Model-based
Predictive Control (MPC) technique. Fast speed tracking is achieved
through optimization of the DC source utilization using MPC. The
technique is based on predicting the optimum voltage vector applied
to the driver. Control technique is investigated by comparing to the
cascaded PI control based on Space Vector Pulse Width Modulation
(SVPWM). MPC and SVPWM-based FOC are implemented with the
TMS320F2812 DSP and its power driver circuits. The designed MPC
for a PMSM drive is experimentally validated on a laboratory test
bench. The performances are compared with those obtained by a
conventional PI-based system in order to highlight the improvements,
especially regarding speed tracking response.
Abstract: Atmospheric carbon dioxide emissions are considered
as the greatest environmental challenge the world is facing today.
The tasks to control the emissions include the recovery of CO2 from
flue gas. This concern has been improved due to recent advances in
materials process engineering resulting in the development of
inorganic gas separation membranes with excellent thermal and
mechanical stability required for most gas separations. This paper,
therefore, evaluates the performance of a highly selective inorganic
membrane for CO2 recovery applications. Analysis of results
obtained is in agreement with experimental literature data. Further
results show the prediction performance of the membranes for gas
separation and the future direction of research. The materials
selection and the membrane preparation techniques are discussed.
Method of improving the interface defects in the membrane and its
effect on the separation performance has also been reviewed and in
addition advances to totally exploit the potential usage of this
innovative membrane.
Abstract: Community integration is a construct that an
increasing body of research has shown to have a significant impact
on the wellbeing and recovery of people with psychiatric problems.
However, there are few studies that explore which factors can be
associated and predict community integration. Moreover, community
integration has been mostly studied in minority groups, and current
literature on the definition and manifestation of community
integration in the general population is scarcer. Thus, the current
study aims to characterize community integration and explore
possible predictor variables in a sample of participants with
psychiatric problems (PP, N=183) and a sample of participants from
the general population (GP, N=211).
Results show that people with psychiatric problems present above
average values of community integration, but are significantly lower
than their healthy counterparts. It was also possible to observe that
community integration does not vary in terms of the sociodemographic
characteristics of both groups in this study. Correlation
and multiple regression showed that, among several variables that
literature present as relevant in the community integration process,
only three variables emerged as having the most explanatory value in
community integration of both groups: sense of community, basic
needs satisfaction and submission. These results also shown that
those variables have increased explanatory power in the PP sample,
which leads us to emphasize the need to address this issue in future
studies and increase the understanding of the factors that can be
involved in the promotion of community integration, in order to
devise more effective interventions in this field.
Abstract: Paranoid ideation is a common thought process that
constitutes a defense against perceived social threats. The current
study aimed at the characterization of paranoid ideation in youths and
to explore the possible predictors involved in the development of
paranoid ideations. Paranoid ideation, shame, submission, early
childhood memories and current depressive, anxious and stress
symptomatology were assessed in a sample of 1516 Portuguese
youths. Higher frequencies of paranoid ideation were observed,
particularly in females and youths from lower socioeconomic status.
The main predictors identified relates to submissive behaviors and
adverse childhood experiences, and especially to shame feelings. The
current study emphasizes that the these predictors are similar to
findings in adults and clinical populations, and future implications to
research and clinical practice aiming at paranoid ideations are
discussed, as well as the pertinence of the study of mediating factors
that allow a wider understanding of this thought process in younger
populations and the prevention of psychopathology in adulthood.
Abstract: Pneumatic reactors have been widely employed in various sectors of the chemical industry, especially where are required high heat and mass transfer rates. This study aimed to obtain correlations that allow the prediction of gas hold-up (Ԑ) and volumetric oxygen transfer coefficient (kLa), and compare these values, for three models of pneumatic reactors on two scales utilizing Newtonian fluids. Values of kLa were obtained using the dynamic pressure-step method, while e was used for a new proposed measure. Comparing the three models of reactors studied, it was observed that the mass transfer was superior to draft-tube airlift, reaching e of 0.173 and kLa of 0.00904s-1. All correlations showed good fit to the experimental data (R2≥94%), and comparisons with correlations from the literature demonstrate the need for further similar studies due to shortage of data available, mainly for airlift reactors and high viscosity fluids.
Abstract: This paper presents a method of evaluating the effect
of aggregate angularity on hot mix asphalt (HMA) properties and its
relationship to the Permanent Deformation resistance. The research
concluded that aggregate particle angularity had a significant effect
on the Permanent Deformation performance, and also that with an
increase in coarse aggregate angularity there was an increase in the
resistance of mixes to Permanent Deformation. A comparison
between the measured data and predictive data of permanent
deformation predictive models showed the limits of existing
prediction models. The numerical analysis described the permanent
deformation zones and concluded that angularity has an effect of the
onset of these zones. Prediction of permanent deformation help road
agencies and by extension economists and engineers determine the
best approach for maintenance, rehabilitation, and new construction
works of the road infrastructure.
Abstract: Optical biosensors have become a powerful detection
and analysis tool for wide-ranging applications in biomedical research,
pharmaceuticals and environmental monitoring. This study carried out
the computational fluid dynamics (CFD)-based simulations to explore
the dispersion phenomenon in the micro channel of an optical
biosensor. The predicted time sequences of concentration contours
were utilized to better understand the dispersion development occurred
in different geometric shapes of micro channels. The simulation results
showed the surface concentrations at the sensing probe (with the best
performance of a grating coupler) in respect of time to appraise the
dispersion effect and therefore identify the design configurations
resulting in minimum dispersion.
Abstract: The fatigue life of tubular joints commonly found in
offshore industry is not only dependent on the value of hot-spot stress
(HSS), but is also significantly influenced by the through-thethickness
stress distribution characterized by the degree of bending
(DoB). The determination of DoB values in a tubular joint is essential
for improving the accuracy of fatigue life estimation using the stresslife
(S–N) method and particularly for predicting the fatigue crack
growth based on the fracture mechanics (FM) approach. In the
present paper, data extracted from finite element (FE) analyses of
tubular KT-joints, verified against experimental data and parametric
equations, was used to investigate the effects of geometrical
parameters on DoB values at the crown 0°, saddle, and crown 180°
positions along the weld toe of central brace in tubular KT-joints
subjected to axial loading. Parametric study was followed by a set of
nonlinear regression analyses to derive DoB parametric formulas for
the fatigue analysis of KT-joints under axial loads. The tubular KTjoint
is a quite common joint type found in steel offshore structures.
However, despite the crucial role of the DoB in evaluating the fatigue
performance of tubular joints, this paper is the first attempt to study
and formulate the DoB values in KT-joints.
Abstract: Auditory hallucinations among the most invalidating
and distressing experiences reported by patients diagnosed with
schizophrenia, leading to feelings of powerlessness and helplessness
towards their illness. In more severe cases, these auditory
hallucinations can take the form of commanding voices, which are
often related to high suicidality rates in these patients. Several
authors propose that the meanings attributed to the hallucinatory
experience, rather than characteristics like form and content, can be
determinant in patients’ reactions to hallucinatory activity,
particularly in the case of voice-hearing experiences. In this study, 48
patients diagnosed with paranoid schizophrenia presenting auditory
hallucinations were studied. Multiple regression analyses were
computed to study the influence of several developmental aspects,
such as family and social dynamics, bullying, depression, and sociocognitive
variables on the auditory hallucinations, on patients’
attributions and relationships with their voices, and on the resulting
invalidation of hallucinatory experience. Overall, results showed how
relationships with voices can mirror several aspects of interpersonal
relationship with others, and how self-schemas, depression and actual
social relationships help shaping the voice-hearing experience. Early
experiences of victimization and submission help predict the
attributions of omnipotence of the voices, and increased hostility
from parents seems to increase the malevolence of the voices,
suggesting that socio-cognitive factors can significantly contribute to
the etiology and maintenance of auditory hallucinations. The
understanding of the characteristics of auditory hallucinations and the
relationships patients established with their voices can allow the
development of more promising therapeutic interventions that can be
more effective in decreasing invalidation caused by this devastating
mental illness.
Abstract: Software fault prediction models are created by using
the source code, processed metrics from the same or previous version
of code and related fault data. Some company do not store and keep
track of all artifacts which are required for software fault prediction.
To construct fault prediction model for such company, the training
data from the other projects can be one potential solution. Earlier we
predicted the fault the less cost it requires to correct. The training
data consists of metrics data and related fault data at function/module
level. This paper investigates fault predictions at early stage using the
cross-project data focusing on the design metrics. In this study,
empirical analysis is carried out to validate design metrics for cross
project fault prediction. The machine learning techniques used for
evaluation is Naïve Bayes. The design phase metrics of other projects
can be used as initial guideline for the projects where no previous
fault data is available. We analyze seven datasets from NASA
Metrics Data Program which offer design as well as code metrics.
Overall, the results of cross project is comparable to the within
company data learning.
Abstract: Heat transfer due to forced convection of copper water
based nanofluid has been predicted by Artificial Neural network
(ANN). The present nanofluid is formed by mixing copper
nanoparticles in water and the volume fractions are considered here
are 0% to 15% and the Reynolds number are kept constant at 100.
The back propagation algorithm is used to train the network. The
present ANN is trained by the input and output data which has been
obtained from the numerical simulation, performed in finite volume
based Computational Fluid Dynamics (CFD) commercial software
Ansys Fluent. The numerical simulation based results are compared
with the back propagation based ANN results. It is found that the
forced convection heat transfer of water based nanofluid can be
predicted correctly by ANN. It is also observed that the back
propagation ANN can predict the heat transfer characteristics of
nanofluid very quickly compared to standard CFD method.
Abstract: Plasmin plays an important role in the human
circulatory system owing to its catalytic ability of fibrinolysis. The
immediate injection of plasmin in patients of strokes has intrigued
many scientists to design vectors that can transport plasmin to the
desired location in human body. Here we predict the structure of
human plasmin and investigate the interaction of plasmin with the
gold-nanoparticle.
Because the crystal structure of plasminogen has been solved, we
deleted N-terminal domain (Pan-apple domain) of plasminogen and
generate a mimic of the active form of this enzyme (plasmin). We
conducted a simulated annealing process on plasmin and discovered a
very large conformation occurs. Kringle domains 1, 4 and 5 had been
observed to leave its original location relative to the main body of the
enzyme and the original doughnut shape of this enzyme has been
transformed to a V-shaped by opening its two arms. This observation
of conformational change is consistent with the experimental results of
neutron scattering and centrifugation.
We subsequently docked the plasmin on the simulated gold surface
to predict their interaction. The V-shaped plasmin could utilize its
Kringle domain and catalytic domain to contact the gold surface.
Our findings not only reveal the flexibility of plasmin structure but
also provide a guide for the design of a plasmin-gold nanoparticle.
Abstract: This research paper presents highly optimized barrel
shifter at 22nm Hi K metal gate strained Si technology node. This
barrel shifter is having a unique combination of static and dynamic
body bias which gives lowest power delay product. This power delay
product is compared with the same circuit at same technology node
with static forward biasing at ‘supply/2’ and also with normal reverse
substrate biasing and still found to be the lowest. The power delay
product of this barrel sifter is .39362X10-17J and is lowered by
approximately 78% to reference proposed barrel shifter at 32nm bulk
CMOS technology. Power delay product of barrel shifter at 22nm Hi
K Metal gate technology with normal reverse substrate bias is
2.97186933X10-17J and can be compared with this design’s PDP of
.39362X10-17J. This design uses both static and dynamic substrate
biasing and also has approximately 96% lower power delay product
compared to only forward body biased at half of supply voltage. The
NMOS model used are predictive technology models of Arizona state
university and the simulations to be carried out using HSPICE
simulator.
Abstract: In the present study, RBF neural networks were used
for predicting the performance and emission parameters of a
biodiesel engine. Engine experiments were carried out in a 4 stroke
diesel engine using blends of diesel and Honge methyl ester as the
fuel. Performance parameters like BTE, BSEC, Tex and emissions
from the engine were measured. These experimental results were
used for ANN modeling.
RBF center initialization was done by random selection and by
using Clustered techniques. Network was trained by using fixed and
varying widths for the RBF units. It was observed that RBF results
were having a good agreement with the experimental results.
Networks trained by using clustering technique gave better results
than using random selection of centers in terms of reduced MRE and
increased prediction accuracy. The average MRE for the performance
parameters was 3.25% with the prediction accuracy of 98% and for
emissions it was 10.4% with a prediction accuracy of 80%.
Abstract: To understand the friction stir welding process, it is
very important to know the nature of the material flow in and around
the tool. The process is a combination of both thermal as well as
mechanical work i.e. it is a coupled thermo-mechanical process.
Numerical simulations are very much essential in order to obtain a
complete knowledge of the process as well as the physics underlying
it. In the present work a model based approach is adopted in order to
study material flow. A thermo-mechanical based CFD model is
developed using a Finite Element package, Comsol Multiphysics.
The fluid flow analysis is done. The model simultaneously predicts
shear strain fields, shear strain rates and shear stress over the entire
workpiece for the given conditions. The flow fields generated by the
streamline plot give an idea of the material flow. The variation of
dynamic viscosity, velocity field and shear strain fields with various
welding parameters is studied. Finally the result obtained from the
above mentioned conditions is discussed elaborately and concluded.
Abstract: The polymer foil used for manufacturing of
laminated glass members behaves in a viscoelastic manner with
temperature dependance. This contribution aims at incorporating
the time/temperature-dependent behavior of interlayer to our earlier
elastic finite element model for laminated glass beams. The model
is based on a refined beam theory: each layer behaves according
to the finite-strain shear deformable formulation by Reissner and
the adjacent layers are connected via the Lagrange multipliers
ensuring the inter-layer compatibility of a laminated unit. The
time/temperature-dependent behavior of the interlayer is accounted
for by the generalized Maxwell model and by the time-temperature
superposition principle due to the Williams, Landel, and Ferry.
The resulting system is solved by the Newton method with
consistent linearization and the viscoelastic response is determined
incrementally by the exponential algorithm. By comparing the model
predictions against available experimental data, we demonstrate that
the proposed formulation is reliable and accurately reproduces the
behavior of the laminated glass units.
Abstract: Many factors influence the educational outcome of
students. Some of these have been studied by researchers with many
emphasizing the role of students, schools, governments, peer groups
and so on. More often than not, some of these factors influencing the
academic achievement of the students have been traced back to
parents and family; being the primary platform on which learning not
only begins but is nurtured, encouraged and developed which later
transforms to the performance of the students. This study not only
explores parental and related factors that predict academic
achievement through the review of relevant literatures but also,
investigates the influence of parental background on the academic
achievement of senior secondary school students in Ibadan North
Local Government Area of Oyo State, Nigeria. As one of the criteria
of the quality of education, students’ academic achievement was
investigated because it is most often cited as an indicator of school
effectiveness by school authorities and educationists. The data
collection was done through interviews and use of well-structured
questionnaires administered to one hundred students (100) within the
target local government. This was statistically analysed and the result
showed that parents’ attitudes towards their children’s education had
significant effect(s) on students’ self-reporting of academic
achievement. However, such factors as parental education and socioeconomic
background had no significant relationship with the
students’ self-reporting of academic achievement.
Abstract: Structural Equation Modeling (SEM) was used to test
a hypothesized model explaining Malaysian hypermarket customers’
perceptions of brand trust (BT), customer perceived value (CPV) and
perceived service quality (PSQ) on building their brand loyalty
(CBL) and generating positive word-of-mouth communication
(WOM). Self-administered questionnaires were used to collect data
from 374 Malaysian hypermarket customers from Mydin, Tesco,
Aeon Big and Giant in Kuala Lumpur, a metropolitan city of
Malaysia. The data strongly supported the model exhibiting that BT,
CPV and PSQ are prerequisite factors in building customer brand
loyalty, while PSQ has the strongest effect on prediction of customer
brand loyalty compared to other factors. Besides, the present study
suggests the effect of the aforementioned factors via customer brand
loyalty strongly contributes to generate positive word of mouth
communication.