Abstract: In this paper, we apply the FM methodology to the
cross-section of Romanian-listed common stocks and investigate the
explanatory power of market beta on the cross-section of commons
stock returns from Bucharest Stock Exchange. Various assumptions
are empirically tested, such us linearity, market efficiency, the “no
systematic effect of non-beta risk" hypothesis or the positive
expected risk-return trade-off hypothesis. We find that the Romanian
stock market shows the same properties as the other emerging
markets in terms of efficiency and significance of the linear riskreturn
models. Our analysis included weekly returns from January
2002 until May 2010 and the portfolio formation, estimation and
testing was performed in a rolling manner using 51 observations (one
year) for each stage of the analysis.
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: Carbon nanotubes (CNTs) are attractive because of
their excellent chemical durability mechanical strength and electrical
properties. Therefore there is interest in CNTs for not only electrical
and mechanical application, but also biological and medical
application.
In this study, the dispersion power of surfactant-treated multiwalled
carbon nanotubes (MWCNTs) and their effect on the antibacterial
activity were examined. Surfactant was used sodium
dodecyl-benzenesulfonate (SDBS). UV-vis absorbance and
transmission electron microscopy(TEM) were used to characterize the
dispersion of MWCNTs in the aqueous phase, showing that the
surfactant molecules had been adsorbed onto the MWCNTs surface.
The surfactant-treated MWCNTs exhibited antimicrobial activities
to streptococcus mutans. The optical density growth curves and viable
cell number determined by the plating method suggested that the
antimicrobial activity of surfactant-treated MWCNTs was both
concentration and treatment time-dependent.
Abstract: An efficient parallel form in digital signal processor can improve the algorithm performance. The butterfly structure is an important role in fast Fourier transform (FFT), because its symmetry form is suitable for hardware implementation. Although it can perform a symmetric structure, the performance will be reduced under the data-dependent flow characteristic. Even though recent research which call as novel memory reference reduction methods (NMRRM) for FFT focus on reduce memory reference in twiddle factor, the data-dependent property still exists. In this paper, we propose a parallel-computing approach for FFT implementation on digital signal processor (DSP) which is based on data-independent property and still hold the property of low-memory reference. The proposed method combines final two steps in NMRRM FFT to perform a novel data-independent structure, besides it is very suitable for multi-operation-unit digital signal processor and dual-core system. We have applied the proposed method of radix-2 FFT algorithm in low memory reference on TI TMSC320C64x DSP. Experimental results show the method can reduce 33.8% clock cycles comparing with the NMRRM FFT implementation and keep the low-memory reference property.
Abstract: Pressure driven microscale gas flow-separation has
been investigated by solving the compressible Navier-Stokes (NS)
system of equations. A two dimensional explicit finite volume (FV)
compressible flow solver has been developed using modified
advection upwind splitting methods (AUSM+) with no-slip/first
order Maxwell-s velocity slip conditions to predict the flowseparation
behavior in microdimensions. The effects of scale-factor
of the flow geometry and gas species on the microscale gas flowseparation
have been studied in this work. The intensity of flowseparation
gets reduced with the decrease in scale of the flow
geometry. In reduced dimension, flow-separation may not at all be
present under similar flow conditions compared to the larger flow
geometry. The flow-separation patterns greatly depend on the
properties of the medium under similar flow conditions.
Abstract: There are many researches to detect collision between real object and virtual object in 3D space. In general, these techniques are need to huge computing power. So, many research and study are constructed by using cloud computing, network computing, and distribute computing. As a reason of these, this paper proposed a novel fast 3D collision detection algorithm between real and virtual object using 2D intersection area. Proposed algorithm uses 4 multiple cameras and coarse-and-fine method to improve accuracy and speed performance of collision detection. In the coarse step, this system examines the intersection area between real and virtual object silhouettes from all camera views. The result of this step is the index of virtual sensors which has a possibility of collision in 3D space. To decide collision accurately, at the fine step, this system examines the collision detection in 3D space by using the visual hull algorithm. Performance of the algorithm is verified by comparing with existing algorithm. We believe proposed algorithm help many other research, study and application fields such as HCI, augmented reality, intelligent space, and so on.
Abstract: A control system design with Characteristic Ratio
Assignment (CRA) is proven that effective for SISO control design.
But the control system design for MIMO via CRA is not concrete
procedure. In this paper presents the control system design method
for quadruple-tank process via CRA. By using the decentralized
method for both minimum phase and non-minimum phase are made.
The results from PI and PID controller design via CRA can be
illustrated the validity of our approach by MATLAB.
Abstract: The problem of updating damped gyroscopic systems using measured modal data can be mathematically formulated as following two problems. Problem I: Given Ma ∈ Rn×n, Λ = diag{λ1, ··· , λp} ∈ Cp×p, X = [x1, ··· , xp] ∈ Cn×p, where p
Abstract: When programming in languages such as C, Java, etc.,
it is difficult to reconstruct the programmer's ideas only from the
program code. This occurs mainly because, much of the programmer's
ideas behind the implementation are not recorded in the code during
implementation. For example, physical aspects of computation such as
spatial structures, activities, and meaning of variables are not required
as instructions to the computer and are often excluded. This makes the
future reconstruction of the original ideas difficult. AIDA, which is a
multimedia programming language based on the cyberFilm model, can
solve these problems allowing to describe ideas behind programs
using advanced annotation methods as a natural extension to
programming. In this paper, a development environment that
implements the AIDA language is presented with a focus on the
annotation methods. In particular, an actual scientific numerical
computation code is created and the effects of the annotation methods
are analyzed.
Abstract: With the increasing complexity of engineering
problems, the traditional, single-objective and deterministic
optimization method can not meet people-s requirements. A
multi-objective fuzzy optimization model of resource input is built for
M chlor-alkali chemical eco-industrial park in this paper. First, the
model is changed into the form that can be solved by genetic algorithm
using fuzzy theory. And then, a fitness function is constructed for
genetic algorithm. Finally, a numerical example is presented to show
that the method compared with traditional single-objective
optimization method is more practical and efficient.
Abstract: Knowledge discovery from text and ontology learning
are relatively new fields. However their usage is extended in many
fields like Information Retrieval (IR) and its related domains. Human
Plausible Reasoning based (HPR) IR systems for example need a
knowledge base as their underlying system which is currently made
by hand. In this paper we propose an architecture based on ontology
learning methods to automatically generate the needed HPR
knowledge base.
Abstract: In this paper the General Game problem is described.
In this problem the competition or cooperation dilemma occurs as the
two basic types of strategies. The strategy possibilities have been
analyzed for finding winning strategy in uncertain situations (no
information about the number of players and their strategy types).
The winning strategy is missing, but a good solution can be found by
simulation by varying the ratio of the two types of strategies. This
new method has been used in a real contest with human players,
where the created strategies by simulation have reached very good
ranks. This construction can be applied in other real social games as
well.
Abstract: Company strategy expresses a basic idea of how to reach company objectives. A whole range of models of strategic management are used in practice. The concept of strategic management should fulfill some basic requirements to make it applicable for both the typical, but also more specific company environment. The financial strategy plays an important role in corporate strategy. The paper develops a methodology of strategic model implementing into the category of micro, small and medium-sized enterprises (SMEs). Furthermore, the methodology recommends procedures while solving an up-to-date worldwide task of the definition of the company strategy and its financial strategy.
Abstract: A new stochastic algorithm called Probabilistic Global Search Johor (PGSJ) has recently been established for global optimization of nonconvex real valued problems on finite dimensional Euclidean space. In this paper we present convergence guarantee for this algorithm in probabilistic sense without imposing any more condition. Then, we jointly utilize this algorithm along with control
parameterization technique for the solution of constrained optimal control problem. The numerical simulations are also included to illustrate the efficiency and effectiveness of the PGSJ algorithm in the solution of control problems.
Abstract: The control of sprayer boom undesired vibrations pose a great challenge to investigators due to various disturbances and conditions. Sprayer boom movements lead to reduce of spread efficiency and crop yield. This paper describes the design of a novel control method for an active suspension system applying proportional-integral-derivative (PID) controller with an active force control (AFC) scheme integration of an iterative learning algorithm employed to a sprayer boom. The iterative learning as an intelligent method is principally used as a method to calculate the best value of the estimated inertia of the sprayer boom needed for the AFC loop. Results show that the proposed AFC-based scheme performs much better than the standard PID control technique. Also, this shows that the system is more robust and accurate.
Abstract: Sparse representation has long been studied and several
dictionary learning methods have been proposed. The dictionary
learning methods are widely used because they are adaptive. In this
paper, a new dictionary learning method for audio is proposed. Signals
are at first decomposed into different degrees of Intrinsic Mode
Functions (IMF) using Empirical Mode Decomposition (EMD)
technique. Then these IMFs form a learned dictionary. To reduce the
size of the dictionary, the K-means method is applied to the dictionary
to generate a K-EMD dictionary. Compared to K-SVD algorithm, the
K-EMD dictionary decomposes audio signals into structured
components, thus the sparsity of the representation is increased by
34.4% and the SNR of the recovered audio signals is increased by
20.9%.
Abstract: The purpose of this study is to revisit the concept of
rape as represented by professionals in the literature as well as its
perception (beliefs and attitudes) in the population at large and to
propose methodological improvements to its measurement tool. Rape
is a serious crime threatening its victim-s physical and mental health
and integrity; and as such is legally prosecuted in all modern
societies. The problem is not in accepting or rejecting rape as a
criminal act, but rather in the vagueness of its interpretations and
“justifications" maintained in the mentality of modern societies -
known in the literature as the phenomenon of "rape-myth". The rapemyth
can be studied from different perspectives: criminology,
sociology, ethics, medicine and psychology. Its investigation requires
rigorous scientific objectivity, free of passion (victims of rape are at
risk of emotional bias), free of activism (social activists, even if wellintentioned
are also biased), free of any pre-emptive assumptions or
prejudices. To apply a rigorous scientific procedure, we need a solid,
valid and reliable measurement. Rape is a form of heterosexual or
homosexual aggression, violently forcing the victim to give-in in the
sexual activity of the aggressor against her/his will. Human beings
always try to “understand" or find a reason justifying their acts.
Psychological literature provides multiple clinical and experimental
examples of it; just to mention the famous studies by Milgram on the
level of electroshock delivered by the “teacher" towards the “learner"
if “scientifically justifiable" or the studies on the behavior of
“prisoners" and the “guards" and many other experiments and field
observations. Sigmund Freud presented the phenomenon of
unconscious justification and called it rationalization. The multiple
justifications, rationalizations and repeated opinions about sexual
behavior contribute to a myth maintained in the society. What kind of
“rationale" our societies apply to “understand" the non-consensual
sexual behavior? There are many, just to mention few:
• Sex is a ludistic activity for both participants, therefore –
even if not consented – it should bring pleasure to both.
• Everybody wants sex, but only men are allowed to manifest
it openly while women have to pretend the opposite, thus men have
to initiate sexual behavior and women would follow.
• A person who strongly needs sex is free to manifest it and
struggle to get it; the person who doesn-t want it must not reveal
her/his sexual attraction and avoid risky situations; otherwise she/he
is perceived as a promiscuous seducer.
• A person who doesn-t fight against the sexual initiator
unconsciously accepts the rape (does it explain why homosexual
rapes are reported less frequently than rapes against women?).
• Women who are raped deserve it because their wardrobe is
very revealing and seducing and they ''willingly'' go to highly risky
places (alleys, dark roads, etc.).
• Men need to ventilate their sexual energy and if they are
deprived of a partner their urge to have sex is difficult to control.
• Men are supposed to initiate and insist even by force to have
sex (their testosterone makes them both sexual and aggressive).
The paper overviews numerous cultural beliefs about masculine
versus feminine behavior and their impact on the “rape myth".
Abstract: Transportation is of great importance in the current
life of human beings. The transportation system plays many roles,
from economical development to after-catastrophe aids such as
rescue operation in the first hours and days after an earthquake. In
after earthquakes response phase, transportation system acts as a
basis for ground operations including rescue and relief operation,
food providing for victims and etc. It is obvious that partial or
complete obstruction of this system results in the stop of these
operations. Bridges are one of the most important elements of
transportation network. Failure of a bridge, in the most optimistic
case, cuts the relation between two regions and in more developed
countries, cuts the relation of numerous regions. In this paper, to
evaluate the vulnerability and estimate the damage level of Tehran
bridges, HAZUS method, developed by Federal Emergency
Management Agency (FEMA) with the aid of National Institute of
Building Science (NIBS), is used for the first time in Iran. In this
method, to evaluate the collapse probability, fragility curves are
used. Iran is located on seismic belt and thus, it is vulnerable to
earthquakes. Thus, the study of the probability of bridge collapses, as
an important part of transportation system, during earthquakes is of
great importance. The purpose of this study is to provide fragility
curves for Gisha Bridge, one of the longest steel bridges in Tehran,
as an important lifeline element. Besides, the damage probability for
this bridge during a specific earthquake, introduced as scenario
earthquakes, is calculated. The fragility curves show that for the
considered scenario, the probability of occurrence of complete
collapse for the bridge is 8.6%.
Abstract: Preprocessing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. In this paper, we present some popular statistical outlier-detection based strategies to segregate the silence/unvoiced part of the speech signal from the voiced portion. The proposed methods are based on the utilization of the 3 σ edit rule, and the Hampel Identifier which are compared with the conventional techniques: (i) short-time energy (STE) based methods, and (ii) distribution based methods. The results obtained after applying the proposed strategies on some test voice signals are encouraging.
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.