Abstract: Significant attention has recently been paid to the
cross-cultural negotiations due to the growth of international
businesses. Despite the substantial body of literature examining the
influence of National Culture (NC) dimensions on negotiations, there
is a lack of studies comparing the influence of NC in Latin America
with a Western European countries, In particular, an extensive review
of the literature revealed that a contribution to knowledge would be
derived from the comparison of the influence of NC dimensions on
negotiations in UK and Venezuela. The primary data was collected
through qualitative interviews, to obtain an insight about the
perceptions and beliefs of Venezuelan and British business managers
about their negotiating styles. The findings of this study indicated
that NC has a great influence on the negotiating styles. In particular,
Venezuelan and British managers demonstrated to have opposed
negotiating styles, affecting the way they communicate, approach
people and their willingness to take risks.
Abstract: Transparent nickel doped cobalt sulfide was fabricated
on a SnO2:F electrode and tested as an efficient electrocatalyst and as
an alternative to the expensive platinum counter electrode. In order to
investigate how this electrode could affect the electrical
characteristics of a dye-sensitized solar cell, we manufactured cells
with the same TiO2 photoanode sensitized with dye (N719) and
employing the same quasi-solid electrolyte, altering only the counter
electrode used. The cells were electrically and electrochemically
characterized and it was observed that the ones with the Ni doped
CoS2 outperformed the efficiency of the cells with the Pt counter
electrode (3.76% and 3.44% respectively). Particularly, the higher
efficiency of the cells with the Ni doped CoS2 counter electrode (CE)
is mainly because of the enhanced photocurrent density which is
attributed to the enhanced electrocatalytic ability of the CE and the
low charge transfer resistance at the CE/electrolyte interface.
Abstract: Human beings have the ability to make logical
decisions. Although human decision - making is often optimal, it is
insufficient when huge amount of data is to be classified. Medical
dataset is a vital ingredient used in predicting patient’s health
condition. In other to have the best prediction, there calls for most
suitable machine learning algorithms. This work compared the
performance of Artificial Neural Network (ANN) and Decision Tree
Algorithms (DTA) as regards to some performance metrics using
diabetes data. WEKA software was used for the implementation of
the algorithms. Multilayer Perceptron (MLP) and Radial Basis
Function (RBF) were the two algorithms used for ANN, while
RegTree and LADTree algorithms were the DTA models used. From
the results obtained, DTA performed better than ANN. The Root
Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is
0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206
respectively.
Abstract: A bauxite ore can be utilized in Bayer Process, if the
mass ratio of Al2O3 to SiO2 is greater than 10. Otherwise, its FexOy
and SiO2 content should be removed. On the other hand, removal of
TiO2 from the bauxite ore would be beneficial because of both
lowering the red mud residue and obtaining a valuable raw material
containing TiO2 mineral. In this study, the low grade diasporic
bauxite ore of Yalvaç, Isparta, Turkey was roasted under reducing
atmosphere and subjected to magnetic separation. According to the
experimental results, 800°C for reduction temperature and 20000
Gauss of magnetic intensity were found to be the optimum
parameters for removal of iron oxide and rutile from the nonmagnetic
ore. On the other hand, 600°C and 5000 Gauss were
determined to be the optimum parameters for removal of silica from
the non-magnetic ore.
Abstract: In recent years, honeycomb fiber reinforced plastic
(FRP) sandwich panels have been increasingly used in various
industries. Low weight, low price and high mechanical strength are
the benefits of these structures. However, their mechanical properties
and behavior have not been fully explored. The objective of this
study is to conduct a combined numerical-statistical investigation of
honeycomb FRP sandwich beams subject to torsion load. In this
paper, the effect of geometric parameters of sandwich panel on
maximum shear strain in both face and core and angle of torsion in a
honeycomb FRP sandwich structures in torsion is investigated. The
effect of Parameters including core thickness, face skin thickness,
cell shape, cell size, and cell thickness on mechanical behavior of the
structure were numerically investigated. Main effects of factors were
considered in this paper and regression equations were derived.
Taguchi method was employed as experimental design and an
optimum parameter combination for the maximum structure stiffness
has been obtained. The results showed that cell size and face skin
thickness have the most significant impacts on torsion angle,
maximum shear strain in face and core.
Abstract: DNA Barcode provides good sources of needed
information to classify living species. The classification problem has
to be supported with reliable methods and algorithms. To analyze
species regions or entire genomes, it becomes necessary to use the
similarity sequence methods. A large set of sequences can be
simultaneously compared using Multiple Sequence Alignment which
is known to be NP-complete. However, all the used methods are still
computationally very expensive and require significant computational
infrastructure. Our goal is to build predictive models that are highly
accurate and interpretable. In fact, our method permits to avoid the
complex problem of form and structure in different classes of
organisms. The empirical data and their classification performances
are compared with other methods. Evenly, in this study, we present
our system which is consisted of three phases. The first one, is called
transformation, is composed of three sub steps; Electron-Ion
Interaction Pseudopotential (EIIP) for the codification of DNA
Barcodes, Fourier Transform and Power Spectrum Signal Processing.
Moreover, the second phase step is an approximation; it is
empowered by the use of Multi Library Wavelet Neural Networks
(MLWNN). Finally, the third one, is called the classification of DNA
Barcodes, is realized by applying the algorithm of hierarchical
classification.
Abstract: This study was conducted to determine sex
differentiation of laboratory reared Elm nymphalid (Nymphalis
polychloros Linnaeus, 1758) by examining the morphological
structure of pupal stage. Laboratory colony of elm nymphalid, reared
on pear leaves, was used to set up experiments. It was performed
with 5 replications having 8 pupae for each replication. Dorsal,
ventral and lateral parts of external morphological structures of pupae
were examined by Olympus SZX9 stereozoom microscope and
photographed. When fully grown, mature larvae wander the highest
part of the rearing cage and pupae were formed hanging by
cremaster. After completing prepupa stage about 1.5±0.3 days, they
all pupated. Pupal stage was completed at 24±1°C about 4.38±1.20
days. Pupal weights were 0.483±0.05 g in females and 0.392±0.08 g
(n=40) in males respectively. Pupal emergence rate was 95%, with
22 females and 16 males. Examinations of ventral parts of 8th, 9th,
and 10th abdominal segments revealed that anal opening were found
at 10th abdominal segment in both sexes, 3 lumps were determined at
9th abdominal segments then the specific opening structure at 8th
segment was only found on female pupae.
Abstract: In this paper, we present a new segmentation approach
for liver lesions in regions of interest within MRI (Magnetic
Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans
methodology, considers the parameter variable compactness
to handle uncertainty. Fine boundaries are detected by a local
recursive merging of ambiguous pixels with a sequential forward
floating selection with Zernike moments. The method has been tested
on both synthetic and real images. When applied on synthetic images,
the proposed approach provides good performance, segmentations
obtained are accurate, their shape is consistent with the ground truth,
and the extracted information is reliable. The results obtained on MR
images confirm such observations. Our approach allows, even for
difficult cases of MR images, to extract a segmentation with good
performance in terms of accuracy and shape, which implies that the
geometry of the tumor is preserved for further clinical activities (such
as automatic extraction of pharmaco-kinetics properties, lesion
characterization, etc.).
Abstract: In this paper, the specific sound Transmission Loss
(TL) of the Laminated Composite Plate (LCP) with different material
properties in each layer is investigated. The numerical method to
obtain the TL of the LCP is proposed by using elastic plate theory. The
transfer matrix approach is novelty presented for computational
efficiency in solving the numerous layers of dynamic stiffness matrix
(D-matrix) of the LCP. Besides the numerical simulations for
calculating the TL of the LCP, the material properties inverse method
is presented for the design of a laminated composite plate analogous to
a metallic plate with a specified TL. As a result, it demonstrates that
the proposed computational algorithm exhibits high efficiency with a
small number of iterations for achieving the goal. This method can be
effectively employed to design and develop tailor-made materials for
various applications.
Abstract: The economic use and ease of construction of profiled
deck composite slab is marred with the complex and un-economic
strength verification required for the serviceability and general safety
considerations. Beside these, albeit factors such as shear span length,
deck geometries and mechanical frictions greatly influence the
longitudinal shear strength, that determines the ultimate strength of
profiled deck composite slab, and number of methods available for its
determination; partial shear and slope-intercept are the two methods
according to Euro-code 4 provision. However, the complexity
associated with shear behavior of profiled deck composite slab, the
use of these methods in determining the load carrying capacities of
such slab yields different and conflicting values. This couple with the
time and cost constraint associated with the strength verification is a
source of concern that draws more attentions nowadays, the issue is
critical. Treating some of these known shear strength influencing
factors as random variables, the load carrying capacity violation of
profiled deck composite slab from the use of the two-methods
defined according to Euro-code 4 are determined using reliability
approach, and comparatively studied. The study reveals safety values
from the use of m-k method shows good standing compared with that
from the partial shear method.
Abstract: We apply the non-parametric, unconditional,
hyperbolic order-α quantile estimator to appraise the relative
efficiency of Microfinance Institutions in Africa in terms of outreach.
Our purpose is to verify if these institutions, which must constantly
try to strike a compromise between their social role and financial
sustainability are operationally efficient.
Using data on African MFIs extracted from the Microfinance
Information eXchange (MIX) database and covering the 2004 to
2006 periods, we find that more efficient MFIs are also the most
profitable. This result is in line with the view that social performance
is not in contradiction with the pursuit of excellent financial
performance. Our results also show that large MFIs in terms of asset
and those charging the highest fees are not necessarily the most
efficient.
Abstract: The efficient and economic allocation of resources is
one main goal in the field of production planning and control.
Nowadays, a new variable gains in importance throughout the
planning process: Energy. Energy-efficiency has already been widely
discussed in literature, but with a strong focus on reducing the overall
amount of energy used in production. This paper provides a brief
systematic approach, how energy-supply-orientation can be used for
an energy-cost-efficient production planning and thus combining the
idea of energy-efficiency and energy-flexibility.
Abstract: Superabsorbent polymers received much attention and
are used in many fields because of their superior characters to
traditional absorbents, e.g., sponge and cotton. So, it is very
important but challenging to prepare highly and fast-swelling
superabsorbents. A reliable, efficient and low-cost technique for
removing heavy metal ions from wastewater is the adsorption using
bio-adsorbents obtained from biological materials, such as
polysaccharides-based hydrogels superabsorbents. In this study, novel multi-functional superabsorbent composites
type semi-interpenetrating polymer networks (Semi-IPNs) were
prepared via graft polymerization of acrylamide onto chitosan
backbone in presence of gelatin, CTS-g-PAAm/Ge, using potassium
persulfate and N,N’-methylene bisacrylamide as initiator and
crosslinker, respectively. These hydrogels were also partially
hydrolyzed to achieve superabsorbents with ampholytic properties
and uppermost swelling capacity. The formation of the grafted
network was evidenced by Fourier Transform Infrared Spectroscopy
(ATR-FTIR) and Thermogravimetric Analysis (TGA). The porous
structures were observed by Scanning Electron Microscope (SEM).
From TGA analysis, it was concluded that the incorporation of the Ge
in the CTS-g-PAAm network has marginally affected its thermal
stability. The effect of gelatin content on the swelling capacities of
these superabsorbent composites was examined in various media
(distilled water, saline and pH-solutions). The water absorbency was
enhanced by adding Ge in the network, where the optimum value was
reached at 2 wt. % of Ge. Their hydrolysis has not only greatly
optimized their absorption capacity but also improved the swelling
kinetic.These materials have also showed reswelling ability. We
believe that these super-absorbing materials would be very effective
for the adsorption of harmful metal ions from wastewater.
Abstract: Steepest descent method is a simple gradient method
for optimization. This method has a slow convergence in heading to
the optimal solution, which occurs because of the zigzag form of the
steps. Barzilai and Borwein modified this algorithm so that it
performs well for problems with large dimensions. Barzilai and
Borwein method results have sparked a lot of research on the method
of steepest descent, including alternate minimization gradient method
and Yuan method. Inspired by previous works, we modified the step
size of the steepest descent method. We then compare the
modification results against the Barzilai and Borwein method,
alternate minimization gradient method and Yuan method for
quadratic function cases in terms of the iterations number and the
running time. The average results indicate that the steepest descent
method with the new step sizes provide good results for small
dimensions and able to compete with the results of Barzilai and
Borwein method and the alternate minimization gradient method for
large dimensions. The new step sizes have faster convergence
compared to the other methods, especially for cases with large
dimensions.
Abstract: EEG correlates of mathematical and trait anxiety level
were studied in 52 healthy Russian-speakers during execution of
error-recognition tasks with lexical, arithmetic and algebraic
conditions. Event-related spectral perturbations were used as a
measure of brain activity. The ERSP plots revealed alpha/beta
desynchronizations within a 500-3000 ms interval after task onset
and slow-wave synchronization within an interval of 150-350 ms.
Amplitudes of these intervals reflected the accuracy of error
recognition, and were differently associated with the three conditions.
The correlates of anxiety were found in theta (4-8 Hz) and beta2 (16-
20 Hz) frequency bands. In theta band the effects of mathematical
anxiety were stronger expressed in lexical, than in arithmetic and
algebraic condition. The mathematical anxiety effects in theta band
were associated with differences between anterior and posterior
cortical areas, whereas the effects of trait anxiety were associated
with inter-hemispherical differences. In beta1 and beta2 bands effects
of trait and mathematical anxiety were directed oppositely. The trait
anxiety was associated with increase of amplitude of
desynchronization, whereas the mathematical anxiety was associated
with decrease of this amplitude. The effect of mathematical anxiety
in beta2 band was insignificant for lexical condition but was the
strongest in algebraic condition. EEG correlates of anxiety in theta
band could be interpreted as indexes of task emotionality, whereas
the reaction in beta2 band is related to tension of intellectual
resources.
Abstract: Artificial neural networks have gained a lot of interest
as empirical models for their powerful representational capacity,
multi input and output mapping characteristics. In fact, most feedforward
networks with nonlinear nodal functions have been proved to
be universal approximates. In this paper, we propose a new
supervised method for color image classification based on selforganizing
feature maps (SOFM). This algorithm is based on
competitive learning. The method partitions the input space using
self-organizing feature maps to introduce the concept of local
neighborhoods. Our image classification system entered into RGB
image. Experiments with simulated data showed that separability of
classes increased when increasing training time. In additional, the
result shows proposed algorithms are effective for color image
classification.
Abstract: Aurèsregion is one of the arid and semi-arid areas that
have suffered climate crises and overexploitation of natural resources
they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and
its spatiotemporal changes in the Aurès between 1987 and 2013, for
this work, we adopted a method of analysis based on the exploitation
of the images satellite Landsat TM 1987 and Landsat OLI 2013, from
the supervised classification likelihood coupled with field surveys of
the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover
maps from 1987 and 2013, one can extract a spatial map change of
different land cover units. The results show that between 1987 and
2013 vegetation has suffered negative changes are the significant
degradation of forests and steppe rangelands, and sandy soils and
bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013
allows us to understand the extensive or regressive orientation of
vegetation and soil, this map shows that dense forests give his place
to clear forests and steppe vegetation develops from a degraded forest
vegetation and bare, sandy soils earn big steppe surfaces that explain
its remarkable extension.
The analysis of remote sensing data highlights the profound
changes in our environment over time and quantitative monitoring of
the risk of desertification.
Abstract: Numerical investigations were conducted to study the
influence of flexural reinforcement ratio on the diagonal cracking
strength and ultimate shear strength of reinforced concrete (RC)
beams without stirrups. Three-dimensional nonlinear finite element
analyses (FEAs) of the beams with flexural reinforcement ratios
ranging from 0.58% to 2.20% subjected to a mid-span concentrated
load were carried out. It is observed that the load-deflection and loadstrain
curves obtained from the numerical analyses agree with those
obtained from the experiments. It is concluded that flexural
reinforcement ratio has a significant effect on the shear strength and
deflection capacity of RC beams without stirrups. The predictions of
diagonal cracking strength and ultimate shear strength of beams
obtained by using the equations defined by a number of codes and
researchers are compared with each other and with the experimental
values.
Abstract: Lead time is a critical measure of a supply chain's
performance. It impacts both the customer satisfactions as well as the
total cost of inventory. This paper presents the result of a study on the
analysis of the customer order lead-time for a multinational company.
In the study, the lead time was divided into three stages respectively:
order entry, order fulfillment, and order delivery. A sample of size 2,425 order lines was extracted from the
company's records to use for this study. The sample data entails
information regarding customer orders from the time of order entry
until order delivery. Data regarding the lead time of each stage for
different orders were also provided. Summary statistics on lead time
data reveals that about 30% of the orders were delivered later than the
scheduled due date. The result of the multiple linear regression
analysis technique revealed that component type, logistics parameter,
order size and the customer type have significant impacts on lead
time. Data analysis on the stages of lead time indicates that stage 2
consumed over 50% of the lead time. Pareto analysis was made to
study the reasons for the customer order delay in each stage.
Recommendation was given to resolve the problem.
Abstract: Accurate forecasting of fresh produce demand is one
the challenges faced by Small Medium Enterprise (SME)
wholesalers. This paper is an attempt to understand the cause for the
high level of variability such as weather, holidays etc., in demand of
SME wholesalers. Therefore, understanding the significance of
unidentified factors may improve the forecasting accuracy. This
paper presents the current literature on the factors used to predict
demand and the existing forecasting techniques of short shelf life
products. It then investigates a variety of internal and external
possible factors, some of which is not used by other researchers in the
demand prediction process. The results presented in this paper are
further analysed using a number of techniques to minimize noise in
the data. For the analysis past sales data (January 2009 to May 2014)
from a UK based SME wholesaler is used and the results presented
are limited to product ‘Milk’ focused on café’s in derby. The
correlation analysis is done to check the dependencies of variability
factor on the actual demand. Further PCA analysis is done to
understand the significance of factors identified using correlation.
The PCA results suggest that the cloud cover, weather summary and
temperature are the most significant factors that can be used in
forecasting the demand. The correlation of the above three factors
increased relative to monthly and becomes more stable compared to
the weekly and daily demand.