Abstract: The development of composite materials and the
related design and manufacturing technologies is one of the most
important advances in the history of materials. Composites are
multifunctional materials having unprecedented mechanical and
physical properties that can be tailored to meet the requirements of a
particular application. Some composites also exhibit great resistance
to high-temperature corrosion, oxidation, and wear. Polymers are
widely used indoors and outdoors, therefore they are exposed to a
chemical environment which may include atmospheric oxygen, acidic
fumes, acidic rain, moisture heat and thermal shock, ultra-violet light,
high energy radiation, etc. Different polymers are affected differently
by these factors even though the amorphous polymers are more
sensitive. Ageing is also important and it is defined as the process of
deterioration of engineering materials resulting from the combined
effects of atmospheric radiation, heat, oxygen, water, microorganisms
and other atmospheric factors.
Abstract: Modelling of building processes of a multimodal
freight transportation support information system is discussed based
on modern CASE technologies. Functional efficiencies of ports in
the eastern part of the Black Sea are analyzed taking into account
their ecological, seasonal, resource usage parameters. By resources,
we mean capacities of berths, cranes, automotive transport, as well as
work crews and neighbouring airports. For the purpose of designing
database of computer support system for Managerial (Logistics)
function, using Object-Role Modeling (ORM) tool (NORMA–Natural ORM Architecture) is proposed, after which Entity
Relationship Model (ERM) is generated in automated process.
Software is developed based on Process-Oriented and Service-Oriented architecture, in Visual Studio.NET environment.
Abstract: The market competition is moving from the single
firm to the whole supply chain because of increasing competition and
growing need for operational efficiencies and customer orientation.
Supply chain management allows companies to look beyond their
organizational boundaries to develop and leverage resources and
capabilities of their supply chain partners. This creates competitive
advantages in the marketplace and because of this SCM has acquired
strategic importance. Lean Approach is a management strategy that focuses on reducing
every type of waste present in an organization. This approach is
becoming more and more popular among supply chain managers. The supply chain application of lean approach is not frequent. In
particular, it is not well studied which are the impacts of lean
approach principles in a supply chain context. In literature there are
only few studies aimed at understanding the qualitative impact of the
lean approach in supply chains. Therefore, the goal of this research
work is to study the impacts of lean principles implementation along
a supply chain. To achieve this, a simulation model of a threeechelon
multi-product supply chain has been built. Kanban system (and several priority policies) and setup time
reduction degrees are implemented in the lean-configured supply
chain to apply pull and lot-sizing decrease principles respectively. To
evaluate the benefits of lean approach, lean supply chain is compared
with an EOQ-configured supply chain. The simulation results show
that Kanban system and setup-time reduction improve inventory
stock level. They also show that logistics efforts are affected to lean
implementation degree. The paper concludes describing
performances of lean supply chain in different contexts.
Abstract: Multiple Input Multiple Output (MIMO) systems are
wireless systems with multiple antenna elements at both ends of the
link. Wireless communication systems demand high data rate and
spectral efficiency with increased reliability. MIMO systems have
been popular techniques to achieve these goals because increased
data rate is possible through spatial multiplexing scheme and
diversity. Spatial Multiplexing (SM) is used to achieve higher
possible throughput than diversity. In this paper, we propose a Zero-
Forcing (ZF) detection using a combination of Ordered Successive
Interference Cancellation (OSIC) and Zero Forcing using
Interference Cancellation (ZF-IC). The proposed method used an
OSIC based on Signal to Noise Ratio (SNR) ordering to get the
estimation of last symbol, then the estimated last symbol is
considered to be an input to the ZF-IC. We analyze the Bit Error Rate
(BER) performance of the proposed MIMO system over Rayleigh
Fading Channel, using Binary Phase Shift Keying (BPSK)
modulation scheme. The results show better performance than the
previous methods.
Abstract: The research explores the relationship between
management responsibility and corporate governance of listed
companies in Kazakhstan. This research employs firm level data of
selected listed non-financial firms and firm level data “operational”
financial sector, consisted from banking sector, insurance companies
and accumulated pension funds using multivariate regression analysis
under fixed effect model approach. Ownership structure includes
institutional ownership, managerial ownership and private investor’s
ownership. Management responsibility of the firm is expressed by the
decision of the firm on amount of leverage. Results of the cross
sectional panel study for non-financial firms showed that only
institutional shareholding is significantly negatively correlated with
debt to equity ratio. Findings from “operational” financial sector
show that leverage is significantly affected only by the CEO/Chair
duality and the size of financial institutions, and insignificantly
affected by ownership structure. Also, the findings show, that there is
a significant negative relationship between profitability and the debt
to equity ratio for non-financial firms, which is consistent with
pecking order theory. Generally, the found results suggest that
corporate governance and a management responsibility play
important role in corporate performance of listed firms in
Kazakhstan.
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: Cortisol is essential to the regulation of the immune
system and pathological yawning is a symptom of multiple sclerosis
(MS). Electromyography activity (EMG) in the jaw muscles typically
rises when the muscles are moved – extended or flexed; and yawning
has been shown to be highly correlated with cortisol levels in healthy
people as shown in the Thompson Cortisol Hypothesis. It is likely
that these elevated cortisol levels are also seen in people with MS.
The possible link between EMG in the jaw muscles and rises in saliva
cortisol levels during yawning were investigated in a randomized
controlled trial of 60 volunteers aged 18-69 years who were exposed
to conditions that were designed to elicit the yawning response.
Saliva samples were collected at the start and after yawning, or at the
end of the presentation of yawning-provoking stimuli, in the absence
of a yawn, and EMG data was additionally collected during rest and
yawning phases. Hospital Anxiety and Depression Scale, Yawning
Susceptibility Scale, General Health Questionnaire, demographic,
and health details were collected and the following exclusion criteria
were adopted: chronic fatigue, diabetes, fibromyalgia, heart
condition, high blood pressure, hormone replacement therapy,
multiple sclerosis, and stroke. Significant differences were found
between the saliva cortisol samples for the yawners, t (23) = -4.263, p
= 0.000, as compared with the non-yawners between rest and poststimuli,
which was non-significant. There were also significant
differences between yawners and non-yawners for the EMG
potentials with the yawners having higher rest and post-yawning
potentials. Significant evidence was found to support the Thompson
Cortisol Hypothesis suggesting that rises in cortisol levels are
associated with the yawning response. Further research is underway
to explore the use of cortisol as a potential diagnostic tool as an assist
to the early diagnosis of symptoms related to neurological disorders.
Bournemouth University Research & Ethics approval granted:
JC28/1/13-KA6/9/13. Professional code of conduct, confidentiality,
and safety issues have been addressed and approved in the Ethics
submission. Trials identification number: ISRCTN61942768.
http://www.controlled-trials.com/isrctn/
Abstract: In this talk, we introduce a newly developed quantile
function model that can be used for estimating conditional
distributions of financial returns and for obtaining multi-step ahead
out-of-sample predictive distributions of financial returns. Since we
forecast the whole conditional distributions, any predictive quantity
of interest about the future financial returns can be obtained simply
as a by-product of the method. We also show an application of the
model to the daily closing prices of Dow Jones Industrial Average
(DJIA) series over the period from 2 January 2004 - 8 October 2010.
We obtained the predictive distributions up to 15 days ahead for
the DJIA returns, which were further compared with the actually
observed returns and those predicted from an AR-GARCH model.
The results show that the new model can capture the main features
of financial returns and provide a better fitted model together with
improved mean forecasts compared with conventional methods. We
hope this talk will help audience to see that this new model has the
potential to be very useful in practice.
Abstract: This paper describes a subarray based low
computational design method of multiuser massive multiple
input multiple output (MIMO) system. In our previous works, use of
large array is assumed only in transmitter, but this study considers
the case both of transmitter and receiver sides are equipped with
large array antennas. For this aim, receive arrays are also divided
into several subarrays, and the former proposed method is modified
for the synthesis of a large array from subarrays in both ends.
Through computer simulations, it is verified that the performance
of the proposed method is degraded compared with the original
approach, but it can achieve the improvement in the aspect of
complexity, namely, significant reduction of the computational load
to the practical level.
Abstract: Recently, numerous documents including large
volumes of unstructured data and text have been created because of the
rapid increase in the use of social media and the Internet. Usually,
these documents are categorized for the convenience of users. Because
the accuracy of manual categorization is not guaranteed, and such
categorization requires a large amount of time and incurs huge costs.
Many studies on automatic categorization have been conducted to help
mitigate the limitations of manual categorization. Unfortunately, most
of these methods cannot be applied to categorize complex documents
with multiple topics because they work on the assumption that
individual documents can be categorized into single categories only.
Therefore, to overcome this limitation, some studies have attempted to
categorize each document into multiple categories. However, the
learning process employed in these studies involves training using a
multi-categorized document set. These methods therefore cannot be
applied to the multi-categorization of most documents unless
multi-categorized training sets using traditional multi-categorization
algorithms are provided. To overcome this limitation, in this study, we
review our novel methodology for extending the category of a
single-categorized document to multiple categorizes, and then
introduce a survey-based verification scenario for estimating the
accuracy of our automatic categorization methodology.
Abstract: Si-Ge solid solutions (bulk poly- and mono-crystalline
samples, thin films) are characterized by high perspectives for
application in semiconductor devices, in particular, optoelectronics
and microelectronics. From this point of view, complex studying of
structural state of the defects and structural-sensitive physical
properties of Si-Ge solid solutions depending on the contents of Si
and Ge components is very important. Present work deals with the
investigations of microstructure, microhardness, internal friction and
shear modulus of Si1-xGex(x≤0,02) bulk monocrystals conducted at
room temperature. Si-Ge bulk crystals were obtained by Czochralski
method in [111] crystallographic direction. Investigated
monocrystalline Si-Ge samples are characterized by p-type
conductivity and carriers’ concentration 5.1014-1.1015cm-3.
Microhardness was studied on Dynamic Ultra Micro hardness Tester
DUH-201S with Berkovich indenter. Investigate samples are characterized with 0,5x0,5x(10-15)mm3
sizes, oriented along [111] direction at torsion oscillations ≈1Hz,
multistage changing of internal friction and shear modulus has been
revealed in an interval of strain amplitude of 10-5-5.10-3. Critical
values of strain amplitude have been determined at which hysteretic
changes of inelastic characteristics and microplasticity are observed. The critical strain amplitude and elasticity limit values are also
determined. Dynamic mechanical characteristics decreasing trend is
shown with increasing Ge content in Si-Ge solid solutions. Observed
changes are discussed from the point of view of interaction of various
dislocations with point defects and their complexes in a real structure
of Si-Ge solid solutions.
Abstract: Due to the fast and flawless technological innovation
there is a tremendous amount of data dumping all over the world in
every domain such as Pattern Recognition, Machine Learning, Spatial
Data Mining, Image Analysis, Fraudulent Analysis, World Wide
Web etc., This issue turns to be more essential for developing several
tools for data mining functionalities. The major aim of this paper is to
analyze various tools which are used to build a resourceful analytical
or descriptive model for handling large amount of information more
efficiently and user friendly. In this survey the diverse tools are
illustrated with their extensive technical paradigm, outstanding
graphical interface and inbuilt multipath algorithms in which it is
very useful for handling significant amount of data more indeed.
Abstract: This paper studies a mathematical model based on the
integral equations for dynamic analyzes numerical investigations of a
non-uniform or multi-material composite beam. The beam is
subjected to a sub-tangential follower force and elastic foundation.
The boundary conditions are represented by generalized
parameterized fixations by the linear and rotary springs. A
mathematical formula based on Euler-Bernoulli beam theory is
presented for beams with variable cross-sections. The non-uniform
section introduces non-uniformity in the rigidity and inertia of beams
and consequently, more complicated equilibrium who governs the
equation. Using the boundary element method and radial basis
functions, the equation of motion is reduced to an algebro-differential
system related to internal and boundary unknowns. A generalized
formula for the deflection, the slope, the moment and the shear force
are presented. The free vibration of non-uniform loaded beams is
formulated in a compact matrix form and all needed matrices are
explicitly given. The dynamic stability analysis of slender beam is
illustrated numerically based on the coalescence criterion. A realistic
case related to an industrial chimney is investigated.
Abstract: New and more powerful communications technologies
continue to emerge at a rapid pace and their uses in education are
widespread and the impact remarkable in the developing societies.
This study investigates Mobile Collaboration Learning Technique
(MCLT) on learners’ outcome among students in tertiary institutions
of developing nations (a case of Nigeria students). It examines the
significance of retention achievement scores of students taught using
mobile collaboration and conventional method. The sample consisted
of 120 students using Stratified random sampling method. Five
research questions and hypotheses were formulated, and tested at
0.05 level of significance. A student achievement test (SAT) was
made of 40 items of multiple-choice objective type, developed and
validated for data collection by professionals. The SAT was
administered to students as pre-test and post-test. The data were
analyzed using t-test statistic to test the hypotheses. The result
indicated that students taught using MCLT performed significantly
better than their counterparts using the conventional method of
instruction. Also, there was no significant difference in the post-test
performance scores of male and female students taught using MCLT.
Based on the findings, the following submissions was made that:
Mobile collaboration system be encouraged in the institutions to
boost knowledge sharing among learners, workshop and training
should be organized to train teachers on the use of this technique,
schools and government should consistently align curriculum
standard to trends of technological dictates and formulate policies
and procedures towards responsible use of MCLT.
Abstract: Carbon nanotubes (CNTs) are known for having high elastic properties with high surface area that promote them as good candidates for reinforcing polymeric matrices. In composite materials, CNTs lack chemical bonding with the surrounding matrix which decreases the possibility of better stress transfer between the components. In this work, a chemical treatment for activating the surface of the multi-wall carbon nanotubes (MWCNT) was applied and the effect of this functionalization on the elastic properties of the epoxy nanocomposites was studied. Functional amino-groups were added to the surface of the CNTs and it was evaluated to be about 34% of the total weight of the CNTs. Elastic modulus was found to increase by about 40% of the neat epoxy resin at CNTs’ weight fraction of 0.5%. The elastic modulus was found to decrease after reaching a certain concentration of CNTs which was found to be 1% wt. The scanning electron microscopic pictures showed the effect of the CNTs on the crack propagation through the sample by forming stress concentrated spots at the nanocomposite samples.
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: Complex environments triggered by globalization
have necessitated new paradigms of leadership – Complexity
Leadership that encompass multiple roles that leaders need to take
upon. Success of Higher Education institutions depends on how well
leaders can provide adaptive, administrative and enabling leadership.
Complexity Leadership seems all the more relevant for institutions
that are knowledge-driven and thrive on Knowledge creation,
Knowledge storage and retrieval, Knowledge Sharing and
Knowledge applications. Discussed in this paper are the elements of
Globalization and the opportunities and challenges that are brought
forth by globalization. The Complexity leadership paradigm in a
knowledge-based economy and the need for such a paradigm shift for
higher education institutions is presented. Further, the paper also
discusses the support the leader requires in a knowledge-driven
economy through knowledge management initiatives.
Abstract: This paper presents a speed estimation scheme based
on second-order sliding-mode Super Twisting Algorithm (STA) and
Model Reference Adaptive System (MRAS) estimation theory for
Sensorless control of multiphase induction machine. A stator current
observer is designed based on the STA, which is utilized to take the
place of the reference voltage model of the standard MRAS
algorithm. The observer is insensitive to the variation of rotor
resistance and magnetizing inductance when the states arrive at the
sliding mode. Derivatives of rotor flux are obtained and designed as
the state of MRAS, thus eliminating the integration. Compared with
the first-order sliding-mode speed estimator, the proposed scheme
makes full use of the auxiliary sliding-mode surface, thus alleviating
the chattering behavior without increasing the complexity. Simulation
results show the robustness and effectiveness of the proposed
scheme.
Abstract: Environmental and functional conditions, sometimes,
necessitate the architectural plan of the building to be asymmetric,
and this result in an asymmetric structure. In such cases finding an
optimal pattern for locating the components of lateral load bearing
system, including shear walls, in the building’s plan is desired. In
case of shear wall in addition to the location the shape of the wall
cross-section is also an effective factor. Various types of shear walls
and their proper layout might come effective in better stiffness
distribution and more appropriate seismic response of the building.
Several studies have been conducted in the context of analysis and
design of shear walls; however, few studies have been performed on
making decisions for the location and form of shear walls in multistory
buildings, especially those with irregular plan. In this study, an
attempt has been made to obtain the most reliable seismic behavior of
multi-story reinforced concrete vertically chamfered buildings by
using more appropriate shear walls form and arrangement in 7-, 10-,
12-, and 15-stoy buildings. The considered forms and arrangements
include common rectangular walls and L-, T-, U- and Z-shaped plan,
located as the core or in the outer frames of the building structure.
Comparison of seismic behaviors of the buildings, including
maximum roof displacement and particularly formation of plastic
hinges and their distribution in the buildings’ structures, have been
done based on the results of a series of nonlinear time history
analyses, by using a set of selected earthquake records. Results show
that shear walls with U-shaped cross-section, placed as the building
central core, and also walls with Z-shaped cross-section, placed at the
corners give the building more reliable seismic behavior.
Abstract: This paper reports on the response of a fiber-optic
sensing probe to small concentrations of hydrogen peroxide (H2O2)
vapor at room temperature. H2O2 has extensive applications in industrial and medical
environments. Conversely, H2O2 can be a health hazard by itself. For
example, H2O2 induces cellular damage in human cells and its
presence can be used to diagnose illnesses such as asthma and human
breast cancer. Hence, development of reliable H2O2 sensor is of vital
importance to detect and measure this species. Ferric ferrocyanide, referred to as Prussian Blue (PB), was
deposited on the tip of a multimode optical fiber through the single
source precursor technique and served as an indicator of H2O2 in a
spectroscopic manner. Sensing tests were performed in H2O2-H2O
vapor mixtures with different concentrations of H2O2. The results of sensing tests show the sensor is able to detect H2O2
concentrations in the range of 50.6 ppm to 229.5 ppm. Furthermore,
the sensor response to H2O2 concentrations is linear in a log-log scale
with the adjacent R-square of 0.93. This sensing behavior allows us
to detect and quantify the concentration of H2O2 in the vapor phase.