Abstract: In this paper, an analytical approach for free vibration
analysis of four edges simply supported rectangular Kirchhoff plates
is presented. The method is based on wave approach. From wave
standpoint vibration propagate, reflect and transmit in a structure.
Firstly, the propagation and reflection matrices for plate with simply
supported boundary condition are derived. Then, these matrices are
combined to provide a concise and systematic approach to free
vibration analysis of a simply supported rectangular Kirchhoff plate.
Subsequently, the eigenvalue problem for free vibration of plates is
formulated and the equation of plate natural frequencies is
constructed. Finally, the effectiveness of the approach is shown by
comparison of the results with existing classical solution.
Abstract: Data stream analysis is the process of computing
various summaries and derived values from large amounts of data
which are continuously generated at a rapid rate. The nature of a
stream does not allow a revisit on each data element. Furthermore,
data processing must be fast to produce timely analysis results. These
requirements impose constraints on the design of the algorithms to
balance correctness against timely responses. Several techniques
have been proposed over the past few years to address these
challenges. These techniques can be categorized as either dataoriented
or task-oriented. The data-oriented approach analyzes a
subset of data or a smaller transformed representation, whereas taskoriented
scheme solves the problem directly via approximation
techniques. We propose a hybrid approach to tackle the data stream
analysis problem. The data stream has been both statistically
transformed to a smaller size and computationally approximated its
characteristics. We adopt a Monte Carlo method in the approximation
step. The data reduction has been performed horizontally and
vertically through our EMR sampling method. The proposed method
is analyzed by a series of experiments. We apply our algorithm on
clustering and classification tasks to evaluate the utility of our
approach.
Abstract: Wavelet transform provides several important
characteristics which can be used in a texture analysis and
classification. In this work, an efficient texture classification method,
which combines concepts from wavelet and co-occurrence matrices,
is presented. An Euclidian distance classifier is used to evaluate the
various methods of classification. A comparative study is essential to
determine the ideal method. Using this conjecture, we developed a
novel feature set for texture classification and demonstrate its
effectiveness
Abstract: The inability to implement the principles of good
corporate governance (GCG) as demonstrated in the surveys is due to
a number of constraints which can be classified into three; namely internal constraints, external constraints, and constraints coming
from the structure of ownership. The issues in the internal constraints
mentioned are related to the function of several elements of the company. As a business organization, corporation is unable to
achieve its goal to successfully implement GCG principles since it is
not support by its internal elements- functions. Two of several numbers of internal elements of a company are ethical work climate
and leadership style of the top management.
To prove the correlation between internal function of organization
(in this case ethical work climate and transformational leadership)
and the successful implementation of GCG principles, this study
proposes two hypotheses to be empirically tested on thirty surveyed organizations; eleven of which are state-owned companies and
nineteen are private companies. These thirty corporations are listed in
the Jakarta Stock Exchange. All state-owned companies in the
samples are those which have been privatized.
The research showed that internal function of organization give
support to the successful implementation of GCG principle. In this
research we can prove that : (i) ethical work climate has positive
significance of correlation with the successful implementation of
social awareness principle (one of principles on GCG) and, (ii) only
at the state-owned companies, transformational leadership have
positive significance effect to forming the ethical work climate.
Abstract: Classification is one of the primary themes in
computational biology. The accuracy of classification strongly
depends on quality of a dataset, and we need some method to
evaluate this quality. In this paper, we propose a new graphical
analysis method using 'Membership-Deviation Graph (MDG)' for
analyzing quality of a dataset. MDG represents degree of
membership and deviations for instances of a class in the dataset. The
result of MDG analysis is used for understanding specific feature and
for selecting best feature for classification.
Abstract: In this paper in consideration of each available
techniques deficiencies for speech recognition, an advanced method
is presented that-s able to classify speech signals with the high
accuracy (98%) at the minimum time. In the presented method, first,
the recorded signal is preprocessed that this section includes
denoising with Mels Frequency Cepstral Analysis and feature
extraction using discrete wavelet transform (DWT) coefficients; Then
these features are fed to Multilayer Perceptron (MLP) network for
classification. Finally, after training of neural network effective
features are selected with UTA algorithm.
Abstract: The Linear discriminant analysis (LDA) can be
generalized into a nonlinear form - kernel LDA (KLDA) expediently
by using the kernel functions. But KLDA is often referred to a general
eigenvalue problem in singular case. To avoid this complication, this
paper proposes an iterative algorithm for the two-class KLDA. The
proposed KLDA is used as a nonlinear discriminant classifier, and the
experiments show that it has a comparable performance with SVM.
Abstract: Due to the non- intuitive nature of Quantum
algorithms, it becomes difficult for a classically trained person to
efficiently construct new ones. So rather than designing new
algorithms manually, lately, Genetic algorithms (GA) are being
implemented for this purpose. GA is a technique to automatically
solve a problem using principles of Darwinian evolution. This has
been implemented to explore the possibility of evolving an n-qubit
circuit when the circuit matrix has been provided using a set of
single, two and three qubit gates. Using a variable length population
and universal stochastic selection procedure, a number of possible
solution circuits, with different number of gates can be obtained for
the same input matrix during different runs of GA. The given
algorithm has also been successfully implemented to obtain two and
three qubit Boolean circuits using Quantum gates. The results
demonstrate the effectiveness of the GA procedure even when the
search spaces are large.
Abstract: With the rapid expansion of city scale and the
excessive concentration of population, achieving relative equality of
extracurricular education resources and improving spatial service
performance of relevant facilities become necessary arduous tasks. In
urban space, extracurricular education facilities should offer better
service to its targeted area and promote the equality and efficiency of
education, which is accomplished by the allocation of facilities. Based
on questionnaire and survey for local students in Hangzhou City in
2009, this study classifies extracurricular education facilities in
meg-city and defines the equalization of these facilities. Then it is
suggested to establish extracurricular education facilities system
according to the development level of city and demands of local
students, and to introduce a spatial analysis method into urban
planning through the aspects of spatial distribution, travel cost and
spatial service scope. Finally, the practice of nine sub-districts of
Hangzhou is studied.
Abstract: Histogram plays an important statistical role in digital
image processing. However, the existing quantum image models are
deficient to do this kind of image statistical processing because
different gray scales are not distinguishable. In this paper, a novel
quantum image representation model is proposed firstly in which the
pixels with different gray scales can be distinguished and operated
simultaneously. Based on the new model, a fast quantum algorithm of
constructing histogram for quantum image is designed. Performance
comparison reveals that the new quantum algorithm could achieve an
approximately quadratic speedup than the classical counterpart. The
proposed quantum model and algorithm have significant meanings for
the future researches of quantum image processing.
Abstract: In this paper, Differential Evolution (DE) algorithm, a new promising evolutionary algorithm, is proposed to train Radial Basis Function (RBF) network related to automatic configuration of network architecture. Classification tasks on data sets: Iris, Wine, New-thyroid, and Glass are conducted to measure the performance of neural networks. Compared with a standard RBF training algorithm in Matlab neural network toolbox, DE achieves more rational architecture for RBF networks. The resulting networks hence obtain strong generalization abilities.
Abstract: The classic problem of recovering arbitrary values of
a band-limited signal from its samples has an added complication
in software radio applications; namely, the resampling calculations
inevitably fold aliases of the analog signal back into the original
bandwidth. The phenomenon is quantified by the spur-free dynamic
range. We demonstrate how a novel application of the Remez (Parks-
McClellan) algorithm permits optimal signal recovery and SFDR, far
surpassing state-of-the-art resamplers.
Abstract: Group work, projects and discussions are important
components of teacher education courses whether they are face-toface,
blended or exclusively online formats. This paper examines the varieties of tasks and challenges with this learning format in a face to
face class teacher education class providing specific examples of both
failure and success from both the student and instructor perspective.
The discussion begins with a brief history of collaborative and cooperative learning, moves to an exploration of the promised
benefits and then takes a look at some of the challenges which can
arise specifically from the use of new technologies. The discussion concludes with guidelines and specific suggestions.
Abstract: Finger spelling is an art of communicating by signs
made with fingers, and has been introduced into sign language to serve
as a bridge between the sign language and the verbal language.
Previous approaches to finger spelling recognition are classified into
two categories: glove-based and vision-based approaches. The
glove-based approach is simpler and more accurate recognizing work
of hand posture than vision-based, yet the interfaces require the user to
wear a cumbersome and carry a load of cables that connected the
device to a computer. In contrast, the vision-based approaches provide
an attractive alternative to the cumbersome interface, and promise
more natural and unobtrusive human-computer interaction. The
vision-based approaches generally consist of two steps: hand
extraction and recognition, and two steps are processed independently.
This paper proposes real-time vision-based Korean finger spelling
recognition system by integrating hand extraction into recognition.
First, we tentatively detect a hand region using CAMShift algorithm.
Then fill factor and aspect ratio estimated by width and height
estimated by CAMShift are used to choose candidate from database,
which can reduce the number of matching in recognition step. To
recognize the finger spelling, we use DTW(dynamic time warping)
based on modified chain codes, to be robust to scale and orientation
variations. In this procedure, since accurate hand regions, without
holes and noises, should be extracted to improve the precision, we use
graph cuts algorithm that globally minimize the energy function
elegantly expressed by Markov random fields (MRFs). In the
experiments, the computational times are less than 130ms, and the
times are not related to the number of templates of finger spellings in
database, as candidate templates are selected in extraction step.
Abstract: Non-Destructive evaluation of in-service power
transformer condition is necessary for avoiding catastrophic failures.
Dissolved Gas Analysis (DGA) is one of the important methods.
Traditional, statistical and intelligent DGA approaches have been
adopted for accurate classification of incipient fault sources.
Unfortunately, there are not often enough faulty patterns required for
sufficient training of intelligent systems. By bootstrapping the
shortcoming is expected to be alleviated and algorithms with better
classification success rates to be obtained. In this paper the
performance of an artificial neural network, K-Nearest Neighbour
and support vector machine methods using bootstrapped data are
detailed and shown that while the success rate of the ANN algorithms
improves remarkably, the outcome of the others do not benefit so
much from the provided enlarged data space. For assessment, two
databases are employed: IEC TC10 and a dataset collected from
reported data in papers. High average test success rate well exhibits
the remarkable outcome.
Abstract: In this paper, we consider a designed and
implemented phase-cutting dimmer. In fact, the dimmer is closed
loop and a microcontroller calculates and then regulates the firing
delay angles of each channel. Depending on the firing angle, the
harmonic distortion in the input current will not comply with
international standards, such as IEC 61000-3-2 (class C equipments).
For solving this problem, eight harmonic compensators have been
added to the dimmer. So, the proposed dimmer has a little harmonic
distortion in the input current whereas conventional phase-cutting
dimmers are not so. Sensitivity and removed THD of the proposed
dimmer will be presented.
Abstract: In the present article, a new class of solutions of
Einstein field equations is investigated for a spherically symmetric
space-time when the source of gravitation is a perfect fluid. All the
solutions have been derived by making some suitable arrangements
in the field equations. The solutions so obtained have been seen to
describe Schwarzschild interior solutions. Most of the solutions are
subjected to the reality conditions. As far as the authors are aware the
solutions are new.
Abstract: Inner class is a specialized class that defined within a
regular outer class. It is used in some programming languages such as
Java to carry out the task which is related to its outer class. The
functional relatedness between inner class and outer class is always
the main concern of defining an inner class. However, excessive use
of inner class could sabotage the class cohesiveness. In addition,
excessive inner class leads to the difficulty of software maintenance
and comprehension. Our research aims at determining the minimum
threshold for the functional relatedness of inner-outer class. Such
minimum threshold is a guideline for removing or relocating the
excessive inner class. Our research provides a feasible way for
software developers to define inner classes which are functionally
related to the outer class.
Abstract: Transmission and distribution lines are vital links between the generating unit and consumers. They are exposed to atmosphere, hence chances of occurrence of fault in transmission line is very high which has to be immediately taken care of in order to minimize damage caused by it. In this paper Discrete wavelet transform of voltage signals at the two ends of transmission lines have been analyzed. The transient energy of the detail information of level five is calculated for different fault conditions. It is observed that the variation of transient energy of healthy and faulted line can give important information which can be very useful in classifying and locating the fault.
Abstract: This research work is concerned with the eigenvalue problem for the integral operators which are obtained by linearization of a nonlocal evolution equation. The purpose of section II.A is to describe the nature of the problem and the objective of the project. The problem is related to the “stable solution" of the evolution equation which is the so-called “instanton" that describe the interface between two stable phases. The analysis of the instanton and its asymptotic behavior are described in section II.C by imposing the Green function and making use of a probability kernel. As a result , a classical Theorem which is important for an instanton is proved. Section III devoted to a study of the integral operators related to interface dynamics which concern the analysis of the Cauchy problem for the evolution equation with initial data close to different phases and different regions of space.