Abstract: The linear methods of heart rate variability analysis
such as non-parametric (e.g. fast Fourier transform analysis) and
parametric methods (e.g. autoregressive modeling) has become an
established non-invasive tool for marking the cardiac health, but their
sensitivity and specificity were found to be lower than expected with
positive predictive value
Abstract: The effect of the number of quantum dot (QD) layers
on the saturated gain of doped QD semiconductor optical amplifiers
(SOAs) has been studied using multi-population coupled rate
equations. The developed model takes into account the effect of
carrier coupling between adjacent layers. It has been found that
increasing the number of QD layers (K) increases the unsaturated
optical gain for K
Abstract: This study examines the relevance of disclosure
practices in improving the accountability and transparency of
religious nonprofit organizations (RNPOs). The assessment of
disclosure is based on the annual returns of RNPOs for the financial
year 2010. In order to quantify the information disclosed in the
annual returns, partial disclosure indexes of basic information (BI)
disclosure index, financial information (FI) disclosure index and
governance information (GI) disclosure index have been built which
takes into account the content of information items in the annual
returns. The empirical evidence obtained revealed low disclosure
practices among RNPOs in the sample. The multiple regression
results showed that the organizational attribute of the board size
appeared to be the most significant predictor for both partial index on
the extent of BI disclosure index, and FI disclosure index. On the
other hand, the extent of financial information disclosure is related to
the amount of donation received by RNPOs. On GI disclosure index,
the existence of an external audit appeared to be significant variable.
This study has contributed to the academic literature in providing
empirical evidence of the disclosure practices among RNPOs.
Abstract: Soil organic carbon (SOC) plays a key role in soil
fertility, hydrology, contaminants control and acts as a sink or source
of terrestrial carbon content that can affect the concentration of
atmospheric CO2. SOC supports the sustainability and quality of
ecosystems, especially in semi-arid region. This study was
conducted to determine relative importance of 13 different
exploratory climatic, soil and geometric factors on the SOC contents
in one of the semiarid watershed zones in Iran. Two methods
canonical discriminate analysis (CDA) and feed-forward back
propagation neural networks were used to predict SOC. Stepwise
regression and sensitivity analysis were performed to identify
relative importance of exploratory variables. Results from sensitivity
analysis showed that 7-2-1 neural networks and 5 inputs in CDA
models output have highest predictive ability that explains %70 and
%65 of SOC variability. Since neural network models outperformed
CDA model, it should be preferred for estimating SOC.
Abstract: Search for a tertiary substructure that geometrically
matches the 3D pattern of the binding site of a well-studied protein provides a solution to predict protein functions. In our previous work,
a web server has been built to predict protein-ligand binding sites
based on automatically extracted templates. However, a drawback of such templates is that the web server was prone to resulting in many
false positive matches. In this study, we present a sequence-order constraint to reduce the false positive matches of using automatically
extracted templates to predict protein-ligand binding sites. The binding site predictor comprises i) an automatically constructed template library and ii) a local structure alignment algorithm for
querying the library. The sequence-order constraint is employed to
identify the inconsistency between the local regions of the query protein and the templates. Experimental results reveal that the sequence-order constraint can largely reduce the false positive matches and is effective for template-based binding site prediction.
Abstract: This study investigated students- perception of self
efficacy and anxiety in acquiring English language, and consequently
examined the relationship existing among the independent variables,
confounding variables and students- performances in the English
language. The researcher tested the research hypotheses using a
sample group of 318 respondents out of the population size of 400
students. The results obtained revealed that there was a significant
moderate negative relationship between English language anxiety
and performance in English language, but no significant relationship
between self-efficacy and English language performance, among the
middle-school students. There was a significant moderate negative
relationship between English language anxiety and self-efficacy. It
was discovered that general self-efficacy and English language
anxiety represented a significantly more powerful set of predictors
than the set of confounding variables. Thus, the study concluded that
English language anxiety and general self-efficacy were significant
predictors of English language performance among middle-school
students in Satri Si Suriyothai School.
Abstract: Work Breakdown Structure (WBS) is one of the
most vital planning processes of the project management since it
is considered to be the fundamental of other processes like
scheduling, controlling, assigning responsibilities, etc. In fact
WBS or activity list is the heart of a project and omission of a
simple task can lead to an irrecoverable result. There are some
tools in order to generate a project WBS. One of the most
powerful tools is mind mapping which is the basis of this article.
Mind map is a method for thinking together and helps a project
manager to stimulate the mind of project team members to
generate project WBS. Here we try to generate a WBS of a
sample project involving with the building construction using the
aid of mind map and the artificial intelligence (AI) programming
language. Since mind map structure can not represent data in a
computerized way, we convert it to a semantic network which can
be used by the computer and then extract the final WBS from the
semantic network by the prolog programming language. This
method will result a comprehensive WBS and decrease the
probability of omitting project tasks.
Abstract: School leadership is commonly considered to have a
significant influence on school effectiveness and improvement.
Effective school leaders are expected to successfully introduce and
support change and innovation at the school unit. Despite an
abundance of studies on educational leadership, very few studies
have provided evidence on the link between leadership models, and
specific educational and school outcomes. This is true of a popular
contemporary approach to leadership, namely, distributed leadership.
The paper provides an overview of research findings on the effect of
distributed leadership on educational outcomes. The theoretical basis
for this approach to leadership is presented, with reference to
methodological and research limitations. The paper discusses
research findings and draws their implications for educational
research on school leadership.
Abstract: The solvated electron is self-trapped (polaron) owing
to strong interaction with the quantum polarization field. If the
electron and quantum field are strongly coupled then the collective
localized state of the field and quasi-particle is formed. In such a
formation the electron motion is rather intricate. On the one hand the
electron oscillated within a rather deep polarization potential well
and undergoes the optical transitions, and on the other, it moves
together with the center of inertia of the system and participates in
the thermal random walk. The problem is to separate these motions
correctly, rigorously taking into account the conservation laws. This
can be conveniently done using Bogolyubov-Tyablikov method of
canonical transformation to the collective coordinates. This
transformation removes the translational degeneracy and allows one
to develop the successive approximation algorithm for the energy and
wave function while simultaneously fulfilling the law of conservation
of total momentum of the system. The resulting equations determine
the electron transitions and depend explicitly on the translational
velocity of the quasi-particle as whole. The frequency of optical
transition is calculated for the solvated electron in ammonia, and an
estimate is made for the thermal-induced spectral bandwidth.
Abstract: Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.
Abstract: Abstraction of water from the dry river sand-beds is
well-known as an alternative source of water during dry seasons.
Internally, because of the form of sand particles, voids are created
which can store water in the riverbeds. Large rivers are rare in South
Africa. Many rivers are sand river types and without water during the
prolonged dry periods. South Africa has not taken full advantage of
water storage in sand as a solution to the growing water scarcity both
in urban and rural areas. The paper reviews the benefits of run-off
storage in sand reservoirs gained from other arid areas and need for
adoption in rural areas of South Africa as an alternative water supply
where it is probable.
Abstract: Hexapod Machine Tool (HMT) is a parallel robot
mostly based on Stewart platform. Identification of kinematic
parameters of HMT is an important step of calibration procedure. In
this paper an algorithm is presented for identifying the kinematic
parameters of HMT using inverse kinematics error model. Based on
this algorithm, the calibration procedure is simulated. Measurement
configurations with maximum observability are decided as the first
step of this algorithm for a robust calibration. The errors occurring in
various configurations are illustrated graphically. It has been shown
that the boundaries of the workspace should be searched for the
maximum observability of errors. The importance of using
configurations with sufficient observability in calibrating hexapod
machine tools is verified by trial calibration with two different
groups of randomly selected configurations. One group is selected to
have sufficient observability and the other is in disregard of the
observability criterion. Simulation results confirm the validity of the
proposed identification algorithm.
Abstract: In the visual servoing systems, the data obtained by
Visionary is used for controlling robots. In this project, at first the
simulator which was proposed for simulating the performance of a
6R robot before, was examined in terms of software and test, and in
the proposed simulator, existing defects were obviated. In the first
version of simulation, the robot was directed toward the target object only in a Position-based method using two cameras in the
environment. In the new version of the software, three cameras were used simultaneously. The camera which is installed as eye-inhand on the end-effector of the robot is used for visual servoing in a
Feature-based method. The target object is recognized according to
its characteristics and the robot is directed toward the object in compliance with an algorithm similar to the function of human-s
eyes. Then, the function and accuracy of the operation of the robot are examined through Position-based visual servoing method using
two cameras installed as eye-to-hand in the environment. Finally, the obtained results are tested under ANSI-RIA R15.05-2 standard.
Abstract: The paper discusses the mathematics of pattern
indexing and its applications to recognition of visual patterns that are
found in video clips. It is shown that (a) pattern indexes can be
represented by collections of inverted patterns, (b) solutions to
pattern classification problems can be found as intersections and
histograms of inverted patterns and, thus, matching of original
patterns avoided.
Abstract: This study analyses store layout among the many
factors that underlie supermarket store design, this; in terms of what to
display in a shop and where to place the items. This report examines
newly-opened stores and evaluates their interior shop floor layouts,
which we then attempt to categorize by various styles. We then
consider the interaction between shop floor layout and customer
behavior from the perspective of the supermarket as the seller. At this
point, we focus on the “store magnets"–the main sections within the
shop likely to attract customers into the store.
Abstract: This paper presents one of the best applications of wireless sensor network for campus Monitoring. With the help of PIR sensor, temperature sensor and humidity sensor, effective utilization of energy resources has been implemented in one of rooms of Sharda University, Greater Noida, India. The RISC microcontroller is used here for analysis of output of sensors and providing proper control using ZigBee protocol. This wireless sensor module presents a tremendous power saving method for any campus
Abstract: Sensory nerves in the foot play an important part in the diagnosis of various neuropathydisorders, especially in diabetes mellitus.However, a detailed description of the anatomical distribution of the nerves is currently lacking. A computationalmodel of the afferent nerves inthe foot may bea useful tool for the study of diabetic neuropathy. In this study, we present the development of an anatomically-based model of various major sensory nerves of the sole and dorsal sidesof the foot. In addition, we presentan algorithm for generating synthetic somatosensory nerve networks in the big-toe region of a right foot model. The algorithm was based on a modified version of the Monte Carlo algorithm, with the capability of being able to vary the intra-epidermal nerve fiber density in differentregionsof the foot model. Preliminary results from the combinedmodel show the realistic anatomical structure of the major nerves as well as the smaller somatosensory nerves of the foot. The model may now be developed to investigate the functional outcomes of structural neuropathyindiabetic patients.
Abstract: Electric vehicles are considered as technology which
can significantly reduce the problems related to road transport such
as increasing GHG emissions, air pollutions and energy import
dependency.
The core objective of this paper is to analyze the current energetic,
ecological and economic characteristics of different types of electric
vehicles.
The major conclusions of this analysis are: The high investments
cost are the major barrier for broad market breakthrough of battery
electric vehicles and fuel cell vehicles. For battery electric vehicles
also the limited driving range states a key obstacle. The analyzed
hybrids could in principle serve as a bridging technology. However,
due to their tank-to-wheel emissions they cannot state a proper
solution for urban areas.
Finally, the most important perception is that also battery electric
vehicles and fuel cell vehicles are environmentally benign solution if
the primary fuel source is renewable.
Abstract: In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.
Abstract: The purpose of this research is to reduce the amount of incomplete coating of stainless steel washers in the electrodeposition painting process by using an experimental design technique. The surface preparation was found to be a major cause of painted surface quality. The influence of pretreating and painting process parameters, which are cleaning time, chemical concentration and shape of hanger were studied. A 23 factorial design with two replications was performed. The analysis of variance for the designed experiment showed the great influence of cleaning time and shape of hanger. From this study, optimized cleaning time was determined and a newly designed electrical conductive hanger was proved to be superior to the original one. The experimental verification results showed that the amount of incomplete coating defects decreased from 4% to 1.02% and operation cost decreased by 10.5%.