Abstract: In the last decade the emergence of new social needs
as an effect of the economic crisis has stimulated the flourishing of
business endeavours characterised by explicit social goals. Social
start-ups, social enterprises or Corporate Social Responsibility
operations carried out by traditional companies are quintessential
examples in this regard. This paper analyses these kinds of initiatives
in order to discover the main characteristics of social business models
and to provide insights to social entrepreneurs for developing or
improving their strategies. The research is conducted through the
integration of literature review and case study analysis and, thanks to
the recognition of the importance of both profits and social impacts
as the key success factors for a social business model, proposes a
framework for identifying indicators suitable for measuring the social
impacts generated.
Abstract: Myocardial infarction is one of the leading causes of
death in the world. Some of these deaths occur even before the
patient reaches the hospital. Myocardial infarction occurs as a result
of impaired blood supply. Because the most of these deaths are due to
coronary artery disease, hence the awareness of the warning signs of
a heart attack is essential. Some heart attacks are sudden and intense,
but most of them start slowly, with mild pain or discomfort, then
early detection and successful treatment of these symptoms is vital to
save them. Therefore, importance and usefulness of a system
designing to assist physicians in early diagnosis of the acute heart
attacks is obvious. The main purpose of this study would be to enable patients to
become better informed about their condition and to encourage them
to seek professional care at an earlier stage in the appropriate
situations. For this purpose, the data were collected on 711 heart
patients in Iran hospitals. 28 attributes of clinical factors can be
reported by patients; were studied. Three logistic regression models
were made on the basis of the 28 features to predict the risk of heart
attacks. The best logistic regression model in terms of performance
had a C-index of 0.955 and with an accuracy of 94.9%. The variables,
severe chest pain, back pain, cold sweats, shortness of breath, nausea
and vomiting, were selected as the main features.
Abstract: Since the last decade, there has been a rapid growth in
digital multimedia, such as high-resolution media files and threedimentional
movies. Hence, there is a need for large digital storage
such as Hard Disk Drive (HDD). As such, users expect to have a
quieter HDD in their laptop. In this paper, a jury test has been
conducted on a group of 34 people where 17 of them are students
who are the potential consumer, and the remaining are engineers who
know the HDD. A total 13 HDD sound samples have been selected
from over hundred HDD noise recordings. These samples are
selected based on an agreed subjective feeling. The samples are
played to the participants using head acoustic playback system, which
enabled them to experience as similar as possible the same
environment as have been recorded. Analysis has been conducted and
the obtained results have indicated different group has different
perception over the noises. Two neural network-based acoustic
annoyance models are established based on back propagation neural
network. Four psychoacoustic metrics, loudness, sharpness,
roughness and fluctuation strength, are used as the input of the
model, and the subjective evaluation results are taken as the output.
The developed models are reasonably accurate in simulating both
training and test samples.
Abstract: This paper describes three lumped parameters models
for the study of the dynamic behavior of a boom crane. The models
here proposed allows to evaluate the fluctuations of the load arising
from the rope and structure elasticity and from the type of the
motion command imposed by the winch. A calculation software
was developed in order to determine the actual acceleration of the
lifted mass and the dynamic overload during the lifting phase. Some
application examples are presented, with the aim of showing the
correlation between the magnitude of the stress and the type of the
employed motion command.
Abstract: High moisture content in fruits generates post-harvest
problems such as mechanical, biochemical, microbial and physical
losses. Dehydration, which is based on the reduction of water activity
of the fruit, is a common option for overcoming such losses.
However, regular hot air drying could affect negatively the quality
properties of the fruit due to the long residence time at high
temperature. Power ultrasound (US) application during the
convective drying has been used as a novel method able to enhance
drying rate and, consequently, to decrease drying time. In the present
study, a new approach was tested to evaluate the effect of US on the
drying time, the final antioxidant activity (AA) and the total
polyphenol content (TPC) of banana slices (BS), mango slices (MS)
and guava slices (GS). There were also studied the drying kinetics
with nine different models from which water effective diffusivities
(Deff) (with or without shrinkage corrections) were calculated.
Compared with the corresponding control tests, US assisted drying
for fruit slices showed reductions in drying time between 16.23 and
30.19%, 11.34 and 32.73%, and 19.25 and 47.51% for the MS, BS
and GS respectively. Considering shrinkage effects, Deff calculated
values ranged from 1.67*10-10 to 3.18*10-10 m2/s, 3.96*10-10 and
5.57*10-10 m2/s and 4.61*10-10 to 8.16*10-10 m2/s for the BS, MS and
GS samples respectively. Reductions of TPC and AA (as DPPH)
were observed compared with the original content in fresh fruit data
in all kinds of drying assays.
Abstract: Evaluation of the excavation-induced ground
movements is an important design aspect of support systems in urban
areas. Geological and geotechnical conditions of an excavation area
have significant effects on excavation-induced ground movements and
the related damage. This paper is aimed at studying the performance of
excavation walls supported by nails in jointed rock medium. The
performance of nailed walls is investigated based on evaluating the
excavation-induced ground movements. For this purpose, a set of
calibrated 2D finite element models are developed by taking into
account the nail-rock-structure interactions, the anisotropic properties
of jointed rock, and the staged construction process. The results of this
paper highlight effects of different parameters such as joint
inclinations, anisotropy of rocks and nail inclinations on deformation
parameters of excavation wall supported by nails.
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: 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: The work reported through this paper is an
experimental work conducted on High Performance Concrete (HPC)
with super plasticizer with the aim to develop some models suitable
for prediction of compressive strength of HPC mixes. In this study,
the effect of varying proportions of fly ash (0% to 50% @ 10%
increment) on compressive strength of high performance concrete has
been evaluated. The mix designs studied were M30, M40 and M50 to
compare the effect of fly ash addition on the properties of these
concrete mixes. In all eighteen concrete mixes that have been
designed, three were conventional concretes for three grades under
discussion and fifteen were HPC with fly ash with varying
percentages of fly ash. The concrete mix designing has been done in
accordance with Indian standard recommended guidelines. All the
concrete mixes have been studied in terms of compressive strength at
7 days, 28 days, 90 days, and 365 days. All the materials used have
been kept same throughout the study to get a perfect comparison of
values of results. The models for compressive strength prediction
have been developed using Linear Regression method (LR), Artificial
Neural Network (ANN) and Leave-One-Out Validation (LOOV)
methods.
Abstract: This paper describes I²C Slave implementation using
I²C master obtained from the OpenCores website. This website
provides free Verilog and VHDL Codes to users. The design
implementation for the I²C slave is in Verilog Language and uses
EDA tools for ASIC design known as ModelSim from Mentor
Graphic. This tool is used for simulation and verification purposes.
Common application for this I²C Master-Slave integration is also
included. This paper also addresses the advantages and limitations of
the said design.
Abstract: Different countries have introduced different schemes
and policies to counter global warming. The rationale behind the
proposed policies and the potential barriers to successful
implementation of the policies adopted by the countries were
analyzed and estimated based on different models. It is argued that
these models enhance the transparency and provide a better
understanding to the policy makers. However, these models are
underpinned with several structural and baseline assumptions. These
assumptions, modeling features and future prediction of emission
reductions and other implication such as cost and benefits of a
transition to a low-carbon economy and its economy wide impacts
were discussed. On the other hand, there are potential barriers in the
form political, financial, and cultural and many others that pose a
threat to the mitigation options.
Abstract: Predicting earnings management is vital for the capital
market participants, financial analysts and managers. The aim of this
research is attempting to respond to this query: Is there a significant
difference between the regression model and neural networks’
models in predicting earnings management, and which one leads to a
superior prediction of it? In approaching this question, a Linear
Regression (LR) model was compared with two neural networks
including Multi-Layer Perceptron (MLP), and Generalized
Regression Neural Network (GRNN). The population of this study
includes 94 listed companies in Tehran Stock Exchange (TSE)
market from 2003 to 2011. After the results of all models were
acquired, ANOVA was exerted to test the hypotheses. In general, the
summary of statistical results showed that the precision of GRNN did
not exhibit a significant difference in comparison with MLP. In
addition, the mean square error of the MLP and GRNN showed a
significant difference with the multi variable LR model. These
findings support the notion of nonlinear behavior of the earnings
management. Therefore, it is more appropriate for capital market
participants to analyze earnings management based upon neural
networks techniques, and not to adopt linear regression models.
Abstract: The latest years the number of immigrants at Greece
has increased dramatically. Their impact on the National Health
System (NHS) has not been yet thoroughly investigated. This paper
analyses the cost of immigrants to the NHS hospitals of the region of
Eastern Macedonia and Thrace. The data are collected from 2005 to
2011 from five different hospitals and are analysed using linear
mixed effects models in order to investigate the effects of nationality
and year on the cost of hospitalization and treatment. The results
show that generally the Greek nationality patients have a higher mean
cost of hospitalization compared to the immigrants and that there is
an increasing trend for the cost except for the year 2010.
Abstract: Structural analysis of flexible pavements has been and still is currently performed using multi-layer elastic theory. However, for thinly surfaced pavements subjected to low to medium volumes of traffics, the importance of non-linear stress-strain behavior of unbound granular materials (UGM) requires the use of more sophisticated numerical models for structural design and performance of such pavements. In the present work, nonlinear unbound aggregates constitutive model is implemented within an axisymmetric finite element code developed to simulate the nonlinear behavior of pavement structures including two local aggregates of different mineralogical nature, typically used in Algerian pavements. The performance of the mechanical model is examined about its capability of representing adequately, under various conditions, the granular material non-linearity in pavement analysis. In addition, deflection data collected by Falling Weight Deflectometer (FWD) are incorporated into the analysis in order to assess the sensitivity of critical pavement design criteria and pavement design life to the constitutive model. Finally, conclusions of engineering significance are formulated.
Abstract: In this paper, temperature extremes are forecast by
employing the block maxima method of the Generalized extreme
value(GEV) distribution to analyse temperature data from the
Cameroon Development Corporation (C.D.C). By considering two sets
of data (Raw data and simulated data) and two (stationary and
non-stationary) models of the GEV distribution, return levels analysis
is carried out and it was found that in the stationary model, the
return values are constant over time with the raw data while in the
simulated data, the return values show an increasing trend but with
an upper bound. In the non-stationary model, the return levels of
both the raw data and simulated data show an increasing trend but
with an upper bound. This clearly shows that temperatures in the
tropics even-though show a sign of increasing in the future, there
is a maximum temperature at which there is no exceedence. The
results of this paper are very vital in Agricultural and Environmental
research.
Abstract: This paper describes how to dimension the electric
components of a 48V hybrid system considering real customer use.
Furthermore, it provides information about savings in energy and
CO2 emissions by a customer-tailored 48V hybrid. Based on measured customer profiles, the electric units such as the
electric motor and the energy storage are dimensioned. Furthermore,
the CO2 reduction potential in real customer use is determined
compared to conventional vehicles. Finally, investigations are carried
out to specify the topology design and preliminary considerations in
order to hybridize a conventional vehicle with a 48V hybrid system.
The emission model results from an empiric approach also taking into
account the effects of engine dynamics on emissions. We analyzed
transient engine emissions during representative customer driving
profiles and created emission meta models. The investigation showed
a significant difference in emissions when simulating realistic
customer driving profiles using the created verified meta models
compared to static approaches which are commonly used for vehicle
simulation.
Abstract: In Automotive Industry, sliding door systems that are
also used as body closures are safety members. Extreme product tests
are realized to prevent failures in design process, but these tests
realized experimentally result in high costs. Finite element analysis is
an effective tool used for design process. These analyses are used
before production of prototype for validation of design according to
customer requirement. In result of this, substantial amount of time
and cost is saved. Finite element model is created for geometries that are designed in
3D CAD programs. Different element types as bar, shell and solid,
can be used for creating mesh model. Cheaper model can be created
by selection of element type, but combination of element type that
was used in model, number and geometry of element and degrees of
freedom affects the analysis result. Sliding door system is a good
example which used these methods for this study. Structural analysis
was realized for sliding door mechanism by using FE models. As
well, physical tests that have same boundary conditions with FE
models were realized. Comparison study for these element types,
were done regarding test and analyses results then optimum
combination was achieved.
Abstract: One of the fundamental characteristics of Information
and Communication Technology (ICT) has been the ever-changing
nature of continuous release and models of ICTs with its impact on
the academic, social, and psychological benefits of its introduction in
schools. However, there seems to be a growing concern about its
negative impact on students when introduced early in schools for
teaching and learning. This study aims to design a model of child
development factors affecting the early introduction of ICTs in
schools in an attempt to improve the understanding of child
development and introduction of ICTs in schools. The proposed
model is based on a sound theoretical framework. It was designed
following a literature review of child development theories and child
development factors. The child development theoretical framework
that fitted to the best of all child development factors was then chosen
as the basis for the proposed model. This study hence found that the
Jean Piaget cognitive developmental theory is the most adequate
theoretical frameworks for modeling child development factors for
ICT introduction in schools.
Abstract: E-retailing is the sale of goods online that takes place
over the Internet. The Internet has shrunk the entire World. World eretailing
is growing at an exponential rate in the Americas, Europe
and Asia. However, e-retailing costs require expensive investment,
such as hardware, software, and security systems. Cloud computing
technology is internet-based computing for the management and
delivery of applications and services. Cloud-based e-retailing
application models allow enterprises to lower their costs with their
effective implementation of e-retailing activities. In this paper, we
describe the concept of cloud computing and present the architecture
of cloud computing, combining the features of e-retailing. In
addition, we propose a strategy for implementing cloud computing
with e-retailing. Finally, we explain the benefits from the
architecture.
Abstract: This paper discusses the general methods to saturation
in the steady-state, two axis (d & q) frame models of synchronous
machines. In particular, the important role of the magnetic coupling
between the d-q axes (cross-magnetizing phenomenon), is
demonstrated. For that purpose, distinct methods of saturation
modeling of dumper synchronous machine with cross-saturation are
identified, and detailed models synthesis in d-q axes. A number of
models are given in the final developed form. The procedure and the
novel models are verified by a critical application to prove the
validity of the method and the equivalence between all developed
models is reported. Advantages of some of the models over the
existing ones and their applicability are discussed.