Abstract: The aim of this paper is to present the concept of an
agile enterprise model and to initiate discussion on the research
assumptions of the model presented. The implementation of the
research project "The agility of enterprises in the process of adapting
to the environment and its changes" began in August 2014 and is
planned to last three years. The article has the form of a work-inprogress
paper which aims to verify and initiate a debate over the
proposed research model. In the literature there are very few
publications relating to research into agility; it can be concluded that
the most controversial issue in this regard is the method of measuring
agility. In previous studies the operationalization of agility was often
fragmentary, focusing only on selected areas of agility, for example
manufacturing, or analysing only selected sectors. As a result the
measures created to date can only be treated as contributory to the
development of precise measurement tools. This research project
aims to fill a cognitive gap in the literature with regard to the
conceptualization and operationalization of an agile company. Thus,
the original contribution of the author of this project is the
construction of a theoretical model that integrates manufacturing
agility (consisting mainly in adaptation to the environment) and
strategic agility (based on proactive measures). The author of this
research project is primarily interested in the attributes of an agile
enterprise which indicate that the company is able to rapidly adapt to
changing circumstances and behave pro-actively.
Abstract: In this work, we explore the capability of the mean
shift algorithm as a powerful preprocessing tool for improving the
quality of spatial data, acquired from airborne scanners, from densely
built urban areas. On one hand, high resolution image data corrupted
by noise caused by lossy compression techniques are appropriately
smoothed while at the same time preserving the optical edges and, on
the other, low resolution LiDAR data in the form of normalized
Digital Surface Map (nDSM) is upsampled through the joint mean
shift algorithm. Experiments on both the edge-preserving smoothing
and upsampling capabilities using synthetic RGB-z data show that the
mean shift algorithm is superior to bilateral filtering as well as to
other classical smoothing and upsampling algorithms. Application of
the proposed methodology for 3D reconstruction of buildings of a
pilot region of Athens, Greece results in a significant visual
improvement of the 3D building block model.
Abstract: A comprehensive CFD model is developed to
represent heterogeneous combustion and two burner designs of
supply sugar-cane bagasse into a furnace. The objective of this work
is to compare the insertion and burning of a Brazilian south-eastern
sugar-cane bagasse using a new swirl burner design against an actual
geometry under operation. The new design allows control the
particles penetration and scattering inside furnace by adjustment of
axial/tangential contributions of air feed without change their mass
flow. The model considers turbulence using RNG k-, combustion
using EDM, radiation heat transfer using DTM with 16 ray directions
and bagasse particle tracking represented by Schiller-Naumann
model. The obtained results are favorable to use of new design swirl
burner because its axial/tangential control promotes more penetration
or more scattering than actual design and allows reproduce the actual
design operation without change the overall mass flow supply.
Abstract: Microscopic simulation tool kits allow for
consideration of the two processes of railway operations and the
previous timetable production. Block occupation conflicts on both
process levels are often solved by using defined train priorities. These
conflict resolutions (dispatching decisions) generate reactionary
delays to the involved trains. The sum of reactionary delays is
commonly used to evaluate the quality of railway operations, which
describes the timetable robustness. It is either compared to an
acceptable train performance or the delays are appraised
economically by linear monetary functions. It is impossible to
adequately evaluate dispatching decisions without a well-founded
objective function. This paper presents a new approach for the
evaluation of dispatching decisions. The approach uses mode choice
models and considers the behaviour of the end-customers. These
models evaluate the reactionary delays in more detail and consider
other competing modes of transport. The new approach pursues the
coupling of a microscopic model of railway operations with the
macroscopic choice mode model. At first, it will be implemented for
railway operations process but it can also be used for timetable
production. The evaluation considers the possibility for the customer
to interchange to other transport modes. The new approach starts to
look at rail and road, but it can also be extended to air travel. The
result of mode choice models is the modal split. The reactions by the
end-customers have an impact on the revenue of the train operating
companies. Different purposes of travel have different payment
reserves and tolerances towards late running. Aside from changes to
revenues, longer journey times can also generate additional costs.
The costs are either time- or track-specific and arise from required
changes to rolling stock or train crew cycles. Only the variable values
are summarised in the contribution margin, which is the base for the
monetary evaluation of delays. The contribution margin is calculated
for different possible solutions to the same conflict. The conflict
resolution is optimised until the monetary loss becomes minimal. The
iterative process therefore determines an optimum conflict resolution
by monitoring the change to the contribution margin. Furthermore, a
monetary value of each dispatching decision can also be derived.
Abstract: Evolutionary optimization methods such as genetic
algorithms have been used extensively for the construction site layout
problem. More recently, ant colony optimization algorithms, which
are evolutionary methods based on the foraging behavior of ants,
have been successfully applied to benchmark combinatorial
optimization problems. This paper proposes a formulation of the site
layout problem in terms of a sequencing problem that is suitable for
solution using an ant colony optimization algorithm.
In the construction industry, site layout is a very important
planning problem. The objective of site layout is to position
temporary facilities both geographically and at the correct time such
that the construction work can be performed satisfactorily with
minimal costs and improved safety and working environment. During
the last decade, evolutionary methods such as genetic algorithms
have been used extensively for the construction site layout problem.
This paper proposes an ant colony optimization model for
construction site layout. A simple case study for a highway project is
utilized to illustrate the application of the model.
Abstract: An efficient remanufacturing network lead to an
efficient design of sustainable manufacturing enterprise. In
remanufacturing network, products are collected from the customer
zone, disassembled and remanufactured at a suitable remanufacturing
facility. In this respect, another issue to consider is how the returned
product to be remanufactured, in other words, what is the best layout
for such facility. In order to achieve a sustainable manufacturing
system, Cellular Manufacturing System (CMS) designs are highly
recommended, CMSs combine high throughput rates of line layouts
with the flexibility offered by functional layouts (job shop).
Introducing the CMS while designing a remanufacturing network will
benefit the utilization of such a network. This paper presents and
analyzes a comprehensive mathematical model for the design of
Dynamic Cellular Remanufacturing Systems (DCRSs). In this paper,
the proposed model is the first one to date that considers CMS and
remanufacturing system simultaneously. The proposed DCRS model
considers several manufacturing attributes such as multi period
production planning, dynamic system reconfiguration, duplicate
machines, machine capacity, available time for workers, worker
assignments, and machine procurement, where the demand is totally
satisfied from a returned product. A numerical example is presented
to illustrate the proposed model.
Abstract: In the present study, the kinetics of thermal
degradation of a phenolic and lignin reinforced phenolic foams, and
the lignin used as reinforcement were studied and the activation
energies of their degradation processes were obtained by a DAEM
model. The average values for five heating rates of the mean
activation energies obtained were: 99.1, 128.2, and 144.0 kJ.mol-1 for
the phenolic foam; 109.5, 113.3, and 153.0 kJ.mol-1 for the lignin
reinforcement; and 82.1, 106.9, and 124.4 kJ.mol-1 for the lignin
reinforced phenolic foam. The standard deviation ranges calculated
for each sample were 1.27-8.85, 2.22-12.82, and 3.17-8.11 kJ.mol-1
for the phenolic foam, lignin and the reinforced foam, respectively.
The DAEM model showed low mean square errors (
Abstract: The article presents two mathematical models of the
interaction between a rotating shaft and an incompressible fluid. The
mathematical model includes both the journal bearings and the
axially traversed hydrodynamic sealing gaps of hydraulic machines.
A method is shown for the identification of additional effects of the
fluid acting on the rotor of the machine, both for a linear and a nonlinear
model. The interaction is expressed by matrices of mass,
stiffness and damping.
Abstract: During the post-Civil War era, the city of Nashville,
Tennessee, had the highest mortality rate in the United States. The
elevated death and disease rates among former slaves were
attributable to lack of quality healthcare. To address the paucity of
healthcare services, Meharry Medical College, an institution with the
mission of educating minority professionals and serving the
underserved population, was established in 1876.
Purpose: The social ecological framework and partial least squares
(PLS) path modeling were used to quantify the impact of
socioeconomic status and adverse health outcome on primary care
professionals serving the disadvantaged community. Thus, the study
results could demonstrate the accomplishment of the College’s
mission of training primary care professionals to serve in underserved
areas.
Methods: Various statistical methods were used to analyze alumni
data from 1975 – 2013. K-means cluster analysis was utilized to
identify individual medical and dental graduates in the cluster groups
of the practice communities (Disadvantaged or Non-disadvantaged
Communities). Discriminant analysis was implemented to verify the
classification accuracy of cluster analysis. The independent t-test was
performed to detect the significant mean differences of respective
clustering and criterion variables. Chi-square test was used to test if
the proportions of primary care and non-primary care specialists are
consistent with those of medical and dental graduates practicing in
the designated community clusters. Finally, the PLS path model was
constructed to explore the construct validity of analytic model by
providing the magnitude effects of socioeconomic status and adverse
health outcome on primary care professionals serving the
disadvantaged community.
Results: Approximately 83% (3,192/3,864) of Meharry Medical
College’s medical and dental graduates from 1975 to 2013 were
practicing in disadvantaged communities. Independent t-test confirmed the content validity of the cluster analysis model. Also, the
PLS path modeling demonstrated that alumni served as primary care
professionals in communities with significantly lower socioeconomic
status and higher adverse health outcome (p < .001). The PLS path
modeling exhibited the meaningful interrelation between primary
care professionals practicing communities and surrounding
environments (socioeconomic statues and adverse health outcome),
which yielded model reliability, validity, and applicability.
Conclusion: This study applied social ecological theory and
analytic modeling approaches to assess the attainment of Meharry
Medical College’s mission of training primary care professionals to
serve in underserved areas, particularly in communities with low
socioeconomic status and high rates of adverse health outcomes. In
summary, the majority of medical and dental graduates from Meharry
Medical College provided primary care services to disadvantaged
communities with low socioeconomic status and high adverse health
outcome, which demonstrated that Meharry Medical College has
fulfilled its mission. The high reliability, validity, and applicability of
this model imply that it could be replicated for comparable
universities and colleges elsewhere.
Abstract: ABC classification is widely used by managers for
inventory control. The classical ABC classification is based on Pareto
principle and according to the criterion of the annual use value only.
Single criterion classification is often insufficient for a closely
inventory control. Multi-criteria inventory classification models have
been proposed by researchers in order to consider other important
criteria. From these models, we will consider a specific model in
order to make a sensitive analysis on the composite score calculated
for each item. In fact, this score, based on a normalized average
between a good and a bad optimized index, can affect the ABC-item
classification. We will focus on items differently assigned to classes
and then propose a classification compromise.
Abstract: Behavioral aspects of experience such as will power
are rarely subjected to quantitative study owing to the numerous
complexities involved. Will is a phenomenon that has puzzled
humanity for a long time. It is a belief that will power of an individual
affects the success achieved by them in life. It is also thought that a
person endowed with great will power can overcome even the most
crippling setbacks in life while a person with a weak will cannot make
the most of life even the greatest assets. This study is an attempt
to subject the phenomena of will to the test of an artificial neural
network through a computational model. The claim being tested is
that will power of an individual largely determines success achieved
in life. It is proposed that data pertaining to success of individuals
be obtained from an experiment and the phenomenon of will be
incorporated into the model, through data generated recursively using
a relation between will and success characteristic to the model.
An artificial neural network trained using part of the data, could
subsequently be used to make predictions regarding data points in
the rest of the model. The procedure would be tried for different
models and the model where the networks predictions are found to
be in greatest agreement with the data would be selected; and used
for studying the relation between success and will.
Abstract: This paper is part of a study to develop robots for
farming. As such power requirement to operate equipment attach to
such robots become an important factor. Soil-tool interaction plays
major role in power consumption, thus predicting accurately the
forces which act on the blade during the farming is very important for
optimal designing of farm equipment. In this paper, a finite element
investigation for tillage tools and soil interaction is described by
using an inelastic constitutive material law for agriculture
application. A 3-dimensional (3D) nonlinear finite element analysis
(FEA) is developed to examine behavior of a blade with different
rake angles moving in a block of soil, and to estimate the blade force.
The soil model considered is an elastic-plastic with non-associated
Drucker-Prager material model. Special use of contact elements are
employed to consider connection between soil-blade and soil-soil
surfaces. The FEA results are compared with experimental ones,
which show good agreement in accurately predicting draft forces
developed on the blade when it moves through the soil. Also a very
good correlation was obtained between FEA results and analytical
results from classical soil mechanics theories for straight blades.
These comparisons verified the FEA model developed. For analyzing
complicated soil-tool interactions and for optimum design of blades,
this method will be useful.
Abstract: A total of 115 yeast strains isolated from local cassava
processing wastes were measured for crude protein content. Among
these strains, the strain MSY-2 possessed the highest protein
concentration (>3.5 mg protein/mL). By using molecular
identification tools, it was identified to be a strain of Pichia
kudriavzevii based on similarity of D1/D2 domain of 26S rDNA
region. In this study, to optimize the protein production by MSY-2
strain, Response Surface Methodology (RSM) was applied. The
tested parameters were the carbon content, nitrogen content, and
incubation time. Here, the value of regression coefficient (R2) =
0.7194 could be explained by the model which is high to support the
significance of the model. Under the optimal condition, the protein
content was produced up to 3.77 g per L of the culture and MSY-2
strain contains 66.8 g protein per 100 g of cell dry weight. These
results revealed the plausibility of applying the novel strain of yeast
in single-cell protein production.
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.
Abstract: The purpose of the paper is to examine the most
critical and important factor which will affect the implementation of
Total Quality Management (TQM) in the construction industry in the
United Arab Emirates. It also examines the most effected Project
outcome from implementing TQM. A framework was also proposed
depending on the literature studies. The method used in this paper is a
quantitative study. A survey with a sample of 60 respondents was
created and distributed in a construction company in Abu Dhabi,
which includes 15 questions to examine the most critical factor that
will affect the implementation of TQM in addition to the most
effected project outcome from implementing TQM. The survey
showed that management commitment is the most important factor in
implementing TQM in a construction company. Also it showed that
Project cost is most effected outcome from the implementation of
TQM.
Management commitment is very important for implementing
TQM in any company. If the management loose interest in quality
then everyone in the organization will do so. The success of TQM
will depend mostly on the top of the pyramid. Also cost is reduced
and money is saved when the project team implement TQM. While if
no quality measures are present within the team, the project will
suffer a commercial failure.
Based on literature, more factors can be examined and added to
the model. In addition, more construction companies could be
surveyed in order to obtain more accurate results. Also this study
could be conducted outside the United Arab Emirates for further
enchantment.
Abstract: An Australian manufacturer has fabricated an
innovative GFRP sandwich panel made from E-glass fiber skin and a
modified phenolic core for structural applications. Debonding, which
refers to separation of skin from the core material in composite
sandwiches, is one of the most common types of damage in
composites. The presence of debonding is of great concern because it
not only severely affects the stiffness but also modifies the dynamic
behaviour of the structure. Generally it is seen that the majority of
research carried out has been concerned about the delamination of
laminated structures whereas skin-core debonding has received
relatively minor attention. Furthermore it is observed that research
done on composite slabs having multiple skin-core debonding is very
limited. To address this gap, a comprehensive research investigating
dynamic behaviour of composite panels with single and multiple
debonding is presented. The study uses finite-element modelling and
analyses for investigating the influence of debonding on free
vibration behaviour of single and multilayer composite sandwich
panels. A broad parametric investigation has been carried out by
varying debonding locations, debonding sizes and support conditions
of the panels in view of both single and multiple debonding.
Numerical models were developed with Strand7 finite element
package by innovatively selecting the suitable elements to diligently
represent their actual behavior. Three-dimensional finite element
models were employed to simulate the physically real situation as
close as possible, with the use of an experimentally and numerically
validated finite element model. Comparative results and conclusions
based on the analyses are presented. For similar extents and locations
of debonding, the effect of debonding on natural frequencies appears
greatly dependent on the end conditions of the panel, giving greater
decrease in natural frequency when the panels are more restrained.
Some modes are more sensitive to debonding and this sensitivity
seems to be related to their vibration mode shapes. The fundamental
mode seems generally the least sensitive mode to debonding with
respect to the variation in free vibration characteristics. The results
indicate the effectiveness of the developed three dimensional finite
element models in assessing debonding damage in composite
sandwich panels.
Abstract: The present research work investigates the seismic
response of reinforced concrete (RC) frame building considering the
effect of modeling masonry infill (MI) walls. The seismic behavior of
a residential 6-storey RC frame building, considering and ignoring
the effect of masonry, is numerically investigated using response
spectrum (RS) analysis. The considered herein building is designed
as a moment resisting frame (MRF) system following the Egyptian
code (EC) requirements. Two developed models in terms of bare
frame and infill walls frame are used in the study. Equivalent
diagonal strut methodology is used to represent the behavior of infill
walls, whilst the well-known software package ETABS is used for
implementing all frame models and performing the analysis. The
results of the numerical simulations such as base shear,
displacements, and internal forces for the bare frame as well as the
infill wall frame are presented in a comparative way. The results of
the study indicate that the interaction between infill walls and frames
significantly change the responses of buildings during earthquakes
compared to the results of bare frame building model. Specifically,
the seismic analysis of RC bare frame structure leads to
underestimation of base shear and consequently damage or even
collapse of buildings may occur under strong shakings. On the other
hand, considering infill walls significantly decrease the peak floor
displacements and drifts in both X and Y-directions.
Abstract: Rice straw is lignocellulosic biomass which can be utilized as substrate for the biogas production. However, due to the property and composition of rice straw, it is difficult to be degraded by hydrolysis enzymes. One of the pretreatment methods that modify such properties of lignocellulosic biomass is the application of lignocellulose-degrading microbial consortia. The aim of this study is to investigate the effect of microbial consortia to enhance biogas production. To select the high efficient consortium, cellulase enzymes were extracted and their activities were analyzed. The results suggested that microbial consortium culture obtained from cattle manure is the best candidate compared to decomposed wood and horse manure. A microbial consortium isolated from cattle manure was then mixed with anaerobic sludge and used as inoculum for biogas production. The optimal conditions for biogas production were investigated using response surface methodology (RSM). The tested parameters were the ratio of amount of microbial consortium isolated and amount of anaerobic sludge (MI:AS), substrate to inoculum ratio (S:I) and temperature. Here, the value of the regression coefficient R2 = 0.7661 could be explained by the model which is high to advocate the significance of the model. The highest cumulative biogas yield was 104.6 ml/g-rice straw at optimum ratio of MI:AS, ratio of S:I, and temperature of 2.5:1, 15:1 and 44°C respectively.
Abstract: This paper provides a quantitative measure of the
time-varying multiunit neuronal spiking activity using an entropy
based approach. To verify the status embedded in the neuronal activity
of a population of neurons, the discrete wavelet transform (DWT) is
used to isolate the inherent spiking activity of MUA. Due to the
de-correlating property of DWT, the spiking activity would be
preserved while reducing the non-spiking component. By evaluating
the entropy of the wavelet coefficients of the de-noised MUA, a
multiresolution Shannon entropy (MRSE) of the MUA signal is
developed. The proposed entropy was tested in the analysis of both
simulated noisy MUA and actual MUA recorded from cortex in rodent
model. Simulation and experimental results demonstrate that the
dynamics of a population can be quantified by using the proposed
entropy.
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.