Abstract: The physiological effects of physical exercise on
human body are relatively well known in literature, which describes
in detail the changes that occur in the cardiovascular system, the
respiratory one, in bones and other systems, both during exercise
and after its delivery. However, the effects of exercise on mental
processes are less treated. From the literature reviews discussed in
this study, it can be detached the idea that we can not exactly say that
physical exercise has beneficial effects on mental processes, but
neither that it would have potentially negative effects. This
uncertainty, reflected in the inability to indicate precise and
unequivocal meaning, favorable-unfavorable physical effort in acting
on mental processes, is a prime reason to undertake a study of the
phenomenon influence effort administered physical education classes
on the dynamics of mental processes like attention and memory.
Abstract: The pollutant removal efficiency of the Intermittently
Decanted Extended Aeration (IDEA) wastewater treatment system at
Curtin University Sarawak Campus, and conventional activated
sludge wastewater treatment system at a local resort, Resort A, is
monitored. The influent and effluent characteristics are tested during
wet and dry weather conditions, and peak and off peak periods. For
the wastewater treatment systems at Curtin Sarawak and Resort A,
during dry weather and peak season, it was found that the BOD5
concentration in the influent is 121.7mg/L and 80.0mg/L
respectively, and in the effluent, 18.7mg/L and and 18.0mg/L
respectively. Analysis of the performance of the IDEA treatment
system showed that the operational costs can be minimized by 3%, by
decreasing the number of operating cycles. As for the treatment
system in Resort A, by utilizing a smaller capacity air blower, a
saving of 12% could be made in the operational costs.
Abstract: Identifying protein coding regions in DNA sequences is a basic step in the location of genes. Several approaches based on signal processing tools have been applied to solve this problem, trying to achieve more accurate predictions. This paper presents a new predictor that improves the efficacy of three techniques that use the Fourier Transform to predict coding regions, and that could be computed using an algorithm that reduces the computation load. Some ideas about the combination of the predictor with other methods are discussed. ROC curves are used to demonstrate the efficacy of the proposed predictor, based on the computation of 25 DNA sequences from three different organisms.
Abstract: This paper seeks to give a general idea of the universe of project portfolio management, from its multidisciplinary nature, to the many challenges it raises, passing through the different techniques, models and tools used to solve the multiple problems known. It is intended to contribute to the clarification, with great depth, of the impacts and relationships involved in managing the projects- portfolio. It aims at proposing a technique for the project alignment with the organisational strategy, in order to select projects that later on will be considered in the analysis and selection of the portfolio. We consider the development of a methodology for assessing the project alignment index very relevant in the global market scenario. It can help organisations to gain a greater awareness of market dynamics, speed up the decision process and increase its consistency, thus enabling the strategic alignment and the improvement of the organisational performance.
Abstract: Most of the biclustering/projected clustering algorithms are based either on the Euclidean distance or correlation coefficient which capture only linear relationships. However, in many applications, like gene expression data and word-document data, non linear relationships may exist between the objects. Mutual Information between two variables provides a more general criterion to investigate dependencies amongst variables. In this paper, we improve upon our previous algorithm that uses mutual information for biclustering in terms of computation time and also the type of clusters identified. The algorithm is able to find biclusters with mixed relationships and is faster than the previous one. To the best of our knowledge, none of the other existing algorithms for biclustering have used mutual information as a similarity measure. We present the experimental results on synthetic data as well as on the yeast expression data. Biclusters on the yeast data were found to be biologically and statistically significant using GO Tool Box and FuncAssociate.
Abstract: Representation and description of object shapes by the
slopes of their contours or borders are proposed. The idea is to capture
the essence of the features that make it easier for a shape to be
stored, transmitted, compared and recognized. These features must
be independent of translation, rotation and scaling of the shape. A
approach is proposed to obtain high performance, efficiency and to
merge the boundaries into sequence of straight line segments with
the fewest possible segments. Evaluation on the performance of the
proposed method is based on its comparison with established method
of object shape description.
Abstract: In this contribution, a way to enhance the performance of the classic Genetic Algorithm is proposed. The idea of restarting a Genetic Algorithm is applied in order to obtain better knowledge of the solution space of the problem. A new operator of 'insertion' is introduced so as to exploit (utilize) the information that has already been collected before the restarting procedure. Finally, numerical experiments comparing the performance of the classic Genetic Algorithm and the Genetic Algorithm with restartings, for some well known test functions, are given.
Abstract: In recent years, fast neural networks for object/face detection have been introduced based on cross correlation in the frequency domain between the input matrix and the hidden weights of neural networks. In our previous papers [3,4], fast neural networks for certain code detection was introduced. It was proved in [10] that for fast neural networks to give the same correct results as conventional neural networks, both the weights of neural networks and the input matrix must be symmetric. This condition made those fast neural networks slower than conventional neural networks. Another symmetric form for the input matrix was introduced in [1-9] to speed up the operation of these fast neural networks. Here, corrections for the cross correlation equations (given in [13,15,16]) to compensate for the symmetry condition are presented. After these corrections, it is proved mathematically that the number of computation steps required for fast neural networks is less than that needed by classical neural networks. Furthermore, there is no need for converting the input data into symmetric form. Moreover, such new idea is applied to increase the speed of neural networks in case of processing complex values. Simulation results after these corrections using MATLAB confirm the theoretical computations.
Abstract: This research aimed to modify pineapple leaf paper
(PALP) for using as wet media in the evaporation cooling system by
improving wet mechanical property (tensile strength) without
compromising water absorption property. Polyamideamineepichorohydrin
resin (PAE) and carboxymethylcellulose (CMC)
were used to strengthen the paper, and the PAE and CMC ratio of
80:20 showed the optimum wet and dry tensile index values, which
were higher than those of the commercial cooling pad (CCP).
Compared with CCP, PALP itself and all the PAE/CMC modified
PALP possessed better water absorption. The PAE/CMC modified
PALP had potential to become a new type of wet media.
Abstract: The rotation of starting pitchers is a strategic issue
which has a significant impact on the performance of a professional
team. Choosing an optimal starting pitcher from among many
alternatives is a multi-criteria decision-making (MCDM) problem. In
this study, a model using the Analytic Hierarchy Process (AHP) and
Technique for Order Performance by Similarity to the Ideal Solution
(TOPSIS) is proposed with which to arrange the starting pitcher
rotation for teams of the Chinese Professional Baseball League. The
AHP is used to analyze the structure of the starting pitcher selection
problem and to determine the weights of the criteria, while the
TOPSIS method is used to make the final ranking. An empirical
analysis is conducted to illustrate the utilization of the model for the
starting pitcher rotation problem. The results demonstrate the
effectiveness and feasibility of the proposed model.
Abstract: In this paper, the application of sliding-mode control to a permanent-magnet synchronous motor (PMSM) is presented. The control design is based on a generic mathematical model of the motor. Some dynamics of the motor and of the power amplification stage remain unmodelled. This model uncertainty is estimated in realtime. The estimation is based on the differentiation of measured signals using the ideas of robust exact differentiator (RED). The control law is implemented on an industrial servo drive. Simulations and experimental results are presented and compared to the same control strategy without uncertainty estimation. It turns out that the proposed concept is superior to the same control strategy without uncertainty estimation especially in the case of non-smooth reference signals.
Abstract: The evaluation of the contribution of professional
baseball starting pitchers is a complex decision-making problem that
includes several quantitative attributes. It is considered a type of
multi-attribute or multi-criteria decision making (MADM/MCDM)
problem. This study proposes a model using the Grey Relational
Analysis (GRA) to evaluate the starting pitcher contribution for teams
of the Chinese Professional Baseball League. The GRA calculates the
individual grey relational degree of each alternative to the positive
ideal alternative. An empirical analysis was conducted to show the use
of the model for the starting pitcher contribution problem. The results
demonstrate the effectiveness and feasibility of the proposed model.
Abstract: A manufacturing feature can be defined simply as a
geometric shape and its manufacturing information to create the shape.
In a feature-based process planning system, feature library plays an
important role in the extraction of manufacturing features with their
proper manufacturing information. However, to manage the
manufacturing information flexibly, it is important to build a feature
library that is easy to modify. In this paper, a Wiki-based feature
library is proposed.
Abstract: Recent years have witnessed the rapid development of
the Internet and telecommunication techniques. Information security
is becoming more and more important. Applications such as covert
communication, copyright protection, etc, stimulate the research of
information hiding techniques. Traditionally, encryption is used to
realize the communication security. However, important information
is not protected once decoded. Steganography is the art and science
of communicating in a way which hides the existence of the communication.
Important information is firstly hidden in a host data, such
as digital image, video or audio, etc, and then transmitted secretly
to the receiver.In this paper a data hiding model with high security
features combining both cryptography using finite state sequential
machine and image based steganography technique for communicating
information more securely between two locations is proposed.
The authors incorporated the idea of secret key for authentication
at both ends in order to achieve high level of security. Before the
embedding operation the secret information has been encrypted with
the help of finite-state sequential machine and segmented in different
parts. The cover image is also segmented in different objects through
normalized cut.Each part of the encoded secret information has been
embedded with the help of a novel image steganographic method
(PMM) on different cuts of the cover image to form different stego
objects. Finally stego image is formed by combining different stego
objects and transmit to the receiver side. At the receiving end different
opposite processes should run to get the back the original secret
message.
Abstract: In this study, a double-sided linear switched reluctance
motor (LSRM) drive was investigated as an alternative actuator for
vertical linear transportation applications such as a linear elevator
door, hospital and subway doors which move linearly and where
accurate position control and rapid response is requested. A prototype
sliding elevator door that is focused on a home elevator with LSRMs
is designed. The motor has 6/4 poles, 3 phases, 8A, 24V, 250 W and
250 N pull forces. Air gap between rotor and translator poles of the
designed motor and phase coil-s ideal inductance profile are obtained
in compliance with the geometric dimensions. Operation and
switching sections as motor and generator has been determined from
the inductance profile.
Abstract: Real world Speaker Identification (SI) application
differs from ideal or laboratory conditions causing perturbations that
leads to a mismatch between the training and testing environment
and degrade the performance drastically. Many strategies have been
adopted to cope with acoustical degradation; wavelet based Bayesian
marginal model is one of them. But Bayesian marginal models
cannot model the inter-scale statistical dependencies of different
wavelet scales. Simple nonlinear estimators for wavelet based
denoising assume that the wavelet coefficients in different scales are
independent in nature. However wavelet coefficients have significant
inter-scale dependency. This paper enhances this inter-scale
dependency property by a Circularly Symmetric Probability Density
Function (CS-PDF) related to the family of Spherically Invariant
Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain
and corresponding joint shrinkage estimator is derived by Maximum
a Posteriori (MAP) estimator. A framework is proposed based on
these to denoise speech signal for automatic speaker identification
problems. The robustness of the proposed framework is tested for
Text Independent Speaker Identification application on 100 speakers
of POLYCOST and 100 speakers of YOHO speech database in three
different noise environments. Experimental results show that the
proposed estimator yields a higher improvement in identification
accuracy compared to other estimators on popular Gaussian Mixture
Model (GMM) based speaker model and Mel-Frequency Cepstral
Coefficient (MFCC) features.
Abstract: In this paper, fabrication and study of electronic properties of Au/methyl-red/Ag surface type Schottky diode by current-voltage (I-V) method has been reported. The I-V characteristics of the Schottky diode showed the good rectifying behavior. The values of ideality factor n and barrier height b of Au/methyl-red/Ag Schottky diode were calculated from the semi-log I-V characteristics and by using the Cheung functions. From semi-log current-voltage characteristics the values of n and b were found 1.93 and 0.254 eV, respectively, while by using Cheung functions their values were calculated 1.89 and 0.26 eV, respectively. The effect of series resistance was also analyzed by Cheung functions. The series resistance RS values were determined from dV/d(lnI)–I and H(I)–I graphs and were found to be 1.1 k and 1.3 k, respectively.
Abstract: One of the most important areas of knowledge management studies is knowledge sharing. Measured in terms of number of scientific articles and organization-s applications, knowledge sharing stands as an example of success in the field. This paper reviews the related papers in the context of the underlying individual behavioral variables to providea direction framework for future research and writing.
Abstract: The problem of frequent pattern discovery is defined
as the process of searching for patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns
has become an important data mining task because it reveals associations, correlations, and many other interesting relationships
hidden in a database. Most of the proposed frequent pattern mining
algorithms have been implemented with imperative programming
languages. Such paradigm is inefficient when set of patterns is large
and the frequent pattern is long. We suggest a high-level declarative
style of programming apply to the problem of frequent pattern
discovery. We consider two languages: Haskell and Prolog. Our
intuitive idea is that the problem of finding frequent patterns should
be efficiently and concisely implemented via a declarative paradigm
since pattern matching is a fundamental feature supported by most
functional languages and Prolog. Our frequent pattern mining
implementation using the Haskell and Prolog languages confirms our
hypothesis about conciseness of the program. The comparative
performance studies on line-of-code, speed and memory usage of
declarative versus imperative programming have been reported in the
paper.
Abstract: Educational reforms are focused point of different
nations. New reform movements generally claim that something is
wrong with the current state of affairs, and that the system is deficient in its goals, its accomplishments and it is accused not being
adopted into global changes all over the world. It is the same for
Turkish education system. It is considered those recent reforms of
teacher education in Turkey and the extent to which they reflect a
response to global economic pressures. The paper challenges the
view that such imposes are inevitable determinants of educational
policy and argues that any country will need to develop its own
national approach to modernizing teacher education in light of the
global context and its particular circumstances. It draws on the idea
of reflexive modernization developed by educators and discusses its
implications for teacher education policy. The paper deals with four
themes teacher education in last decade policy in Turkey; the shift
away from the educational disciplines, the shift towards school-based
approaches, and the emergence of more centralized forms of
accountability of teacher competence.