Abstract: There are many studies in the literature on
institutional investors- efforts to improve corporate governance,
generally focused on the role of pension funds and private equity
firms. There are only a few studies that analyze the influence of
development banks in the governance of investee companies. The
objective of this research is to examine the role of the Brazilian
Development Bank (BNDES) in the governance of listed companies.
Our analysis provides evidence that companies in which BNDES is a
shareholder have better governance.
Abstract: At present, intelligent planning in the Graphplan framework is a focus of artificial intelligence. While the Creating or Destroying Objects Planning (CDOP) is one unsolved problem of this field, one of the difficulties, too. In this paper, we study this planning problem and bring forward the idea of transforming objects to propositions, based on which we offer an algorithm, Creating or Destroying Objects in the Graphplan framework (CDOGP). Compared to Graphplan, the new algorithm can solve not only the entire problems that Graphplan do, but also a part of CDOP. It is for the first time that we introduce the idea of object-proposition, and we emphasize the discussion on the representations of creating or destroying objects operator and an algorithm in the Graphplan framework. In addition, we analyze the complexity of this algorithm.
Abstract: In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.
Abstract: The purpose of Grid computing is to utilize
computational power of idle resources which are distributed in
different areas. Given the grid dynamism and its decentralize
resources, there is a need for an efficient scheduler for scheduling
applications. Since task scheduling includes in the NP-hard problems
various researches have focused on invented algorithms especially
the genetic ones. But since genetic is an inherent algorithm which
searches the problem space globally and does not have the efficiency
required for local searching, therefore, its combination with local
searching algorithms can compensate for this shortcomings. The aim
of this paper is to combine the genetic algorithm and GELS (GAGELS)
as a method to solve scheduling problem by which
simultaneously pay attention to two factors of time and number of
missed tasks. Results show that the proposed algorithm can decrease
makespan while minimizing the number of missed tasks compared
with the traditional methods.
Abstract: In a state-of-the-art industrial production line of
photovoltaic products the handling and automation processes are of
particular importance and implication. While processing a fully
functional crystalline solar cell an as-cut photovoltaic wafer is subject
to numerous repeated handling steps. With respect to stronger
requirements in productivity and decreasing rejections due to defects
the mechanical stress on the thin wafers has to be reduced to a
minimum as the fragility increases by decreasing wafer thicknesses.
In relation to the increasing wafer fragility, researches at the
Fraunhofer Institutes IPA and CSP showed a negative correlation
between multiple handling processes and the wafer integrity. Recent
work therefore focused on the analysis and optimization of the dry
wafer stack separation process with compressed air. The achievement
of a wafer sensitive process capability and a high production
throughput rate is the basic motivation in this research.
Abstract: In this research, the authors analyze network stability
using agent-based simulation. Firstly, the authors focus on analyzing
large networks (eight agents) by connecting different two stable small
social networks (A small stable network is consisted on four agents.).
Secondly, the authors analyze the network (eight agents) shape which
is added one agent to a stable network (seven agents). Thirdly, the
authors analyze interpersonal comparison of utility. The “star-network
"was not found on the result of interaction among stable two small
networks. On the other hand, “decentralized network" was formed
from several combination. In case of added one agent to a stable
network (seven agents), if the value of “c"(maintenance cost of per
a link) was larger, the number of patterns of stable network was
also larger. In this case, the authors identified the characteristics of a
large stable network. The authors discovered the cases of decreasing
personal utility under condition increasing total utility.
Abstract: Recent quasi-experimental evaluation of the Canadian Active Labour Market Policies (ALMP) by Human Resources and Skills Development Canada (HRSDC) has provided an opportunity to examine alternative methods to estimating the incremental effects of Employment Benefits and Support Measures (EBSMs) on program participants. The focus of this paper is to assess the efficiency and robustness of inverse probability weighting (IPW) relative to kernel matching (KM) in the estimation of program effects. To accomplish this objective, the authors compare pairs of 1,080 estimates, along with their associated standard errors, to assess which type of estimate is generally more efficient and robust. In the interest of practicality, the authorsalso document the computationaltime it took to produce the IPW and KM estimates, respectively.
Abstract: Nowadays, the demand for high product quality
focuses extensive attention to the quality of machined surface. The
(CNC) milling machine facilities provides a wide variety of
parameters set-up, making the machining process on the glass
excellent in manufacturing complicated special products compared to
other machining processes. However, the application of grinding
process on the CNC milling machine could be an ideal solution to
improve the product quality, but adopting the right machining
parameters is required. In glass milling operation, several machining
parameters are considered to be significant in affecting surface
roughness. These parameters include the lubrication pressure, spindle
speed, feed rate and depth of cut. In this research work, a fuzzy logic
model is offered to predict the surface roughness of a machined
surface in glass milling operation using CBN grinding tool. Four
membership functions are allocated to be connected with each input
of the model. The predicted results achieved via fuzzy logic model
are compared to the experimental result. The result demonstrated
settlement between the fuzzy model and experimental results with the
93.103% accuracy.
Abstract: In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.
Abstract: Content-based Image Retrieval (CBIR) aims at searching image databases for specific images that are similar to a given query image based on matching of features derived from the image content. This paper focuses on a low-dimensional color based indexing technique for achieving efficient and effective retrieval performance. In our approach, the color features are extracted using the mean shift algorithm, a robust clustering technique. Then the cluster (region) mode is used as representative of the image in 3-D color space. The feature descriptor consists of the representative color of a region and is indexed using a spatial indexing method that uses *R -tree thus avoiding the high-dimensional indexing problems associated with the traditional color histogram. Alternatively, the images in the database are clustered based on region feature similarity using Euclidian distance. Only representative (centroids) features of these clusters are indexed using *R -tree thus improving the efficiency. For similarity retrieval, each representative color in the query image or region is used independently to find regions containing that color. The results of these methods are compared. A JAVA based query engine supporting query-by- example is built to retrieve images by color.
Abstract: This research focus on developing a new segmentation method for improving forecasting model which is call trend based segmentation method (TBSM). Generally, the piece-wise linear representation (PLR) can finds some of pair of trading points is well for time series data, but in the complicated stock environment it is not well for stock forecasting because of the stock has more trends of trading. If we consider the trends of trading in stock price for the trading signal which it will improve the precision of forecasting model. Therefore, a TBSM with SVR model used to detect the trading points for various stocks of Taiwanese and America under different trend tendencies. The experimental results show our trading system is more profitable and can be implemented in real time of stock market
Abstract: Direction of Arrival estimation refers to defining a mathematical function called a pseudospectrum that gives an indication of the angle a signal is impinging on the antenna array. This estimation is an efficient method of improving the quality of service in a communication system by focusing the reception and transmission only in the estimated direction thereby increasing fidelity with a provision to suppress interferers. This improvement is largely dependent on the performance of the algorithm employed in the estimation. Many DOA algorithms exists amongst which are MUSIC, Root-MUSIC and ESPRIT. In this paper, performance of these three algorithms is analyzed in terms of complexity, accuracy as assessed and characterized by the CRLB and memory requirements in various environments and array sizes. It is found that the three algorithms are high resolution and dependent on the operating environment and the array size.
Abstract: This is the second part of the paper. It, aside from the
core subroutine test reported previously, focuses on the simulation of
turbulence governed by the full STF Navier-Stokes equations on a
large scale. Law of the wall is found plausible in this study as a model
of the boundary layer dynamics. Model validations proceed to
include velocity profiles of a stationary turbulent Couette flow, pure
sloshing flow simulations, and the identification of water-surface
inclination due to fluid accelerations. Errors resulting from the
irrotational and hydrostatic assumptions are explored when studying
a wind-driven water circulation with no shakings. Illustrative
examples show that this numerical strategy works for the simulation
of sloshing-shear mixed flow in a 3-D rigid rectangular base tank.
Abstract: The article presents findings from the study and
analysis of the results of an experimental programme focused on the
production of concrete and fibre reinforced concrete in which natural
aggregate has been substituted with brick or concrete recyclate. The
research results are analyzed to monitor the effect of mechanicalphysical
characteristics on the durability properties of tested
cementitious composites. The key parts of the fibre reinforced
concrete mix are the basic components: aggregates – recyclate,
cement, fly ash, water and fibres. Their specific ratios and the
properties of individual components principally affect the resulting
behaviour of fresh fibre reinforced concrete and the characteristics of
the final product. The article builds on the sources dealing with the
use of recycled aggregates from construction and demolition waste in
the production of fibre reinforced concrete. The implemented
procedure of testing the composite contributes to the building
sustainability in environmental engineering.
Abstract: Qualification of doctoral students- and the candidates for a scientific degree is evaluated by the ability to solve scientific ideas in an innovative way, consequently, being a potential of research and science they play a significant role in the sustainability context of the society. The article deals with the analysis of the results of the pilot project, the aim of which has been to study the structure of doctoral students- research competences in the sustainability context. With the existance of variety of theories on research competence development, their analysis focuses on the attained aim approach. Three competence groups have been identified in this study: informative, communicative and instrumental. Within the study the doctoral students and candidates for a scientific degree (N=64) made their self-assessment of research competences. The study results depict their present research competence development level and its dynamics according to the aim to attain.
Abstract: Although Model Driven Architecture has taken
successful steps toward model-based software development, this
approach still faces complex situations and ambiguous questions
while applying to real world software systems. One of these
questions - which has taken the most interest and focus - is how
model transforms between different abstraction levels, MDA
proposes. In this paper, we propose an approach based on Story
Driven Modeling and Aspect Oriented Programming to ease these
transformations. Service Oriented Architecture is taken as the target
model to test the proposed mechanism in a functional system.
Service Oriented Architecture and Model Driven Architecture [1]
are both considered as the frontiers of their own domain in the
software world. Following components - which was the greatest step
after object oriented - SOA is introduced, focusing on more
integrated and automated software solutions. On the other hand - and
from the designers' point of view - MDA is just initiating another
evolution. MDA is considered as the next big step after UML in
designing domain.
Abstract: This study examines appearances of brand placement
as an alternative communication strategy in television series by
focusing on Yalan Dünya which is one of the most popular television
series in Turkey. Consequently, this study has a descriptive research
design and quantitative content analysis method is used in order to
analyze frequency and time data of brand placement appearances in
first 3 seasons of Yalan Dünya with 16 episodes.
Analysis of brand placement practices in Yalan Dünya is dealt in
three categories: episode-based analysis, season-based analysis and
comparative analysis. At the end, brand placement practices in Yalan
Dünya are evaluated in terms of type, form, duration and legal
arrangements.
As a result of this study, it is seen that brand placement plays a
determinant role in Yalan Dünya content. Also, current legal
arrangements make brand placement closer to other traditional
communication strategies instead of differing brand placement from
them distinctly.
Abstract: The present study is concerned with the absorption
center of photophoresis within a micro-sized and spheroidal particle in
a gaseous medium. A particle subjected to an intense light beam can
absorb electromagnetic energy within the particle unevenly, which
results in photophoretic force to drive the particle in motion. By
evaluating the energy distribution systematically at various conditions,
the study focuses on the effects of governing parameters, such as
particle aspect ratio, size parameter, refractivity, and absorptivity, on
the heat source function within the particle and their potential
influences to the photophoresis.
Abstract: Bandwidth allocation in wired network is less complex
and to allocate bandwidth in wireless networks is complex and
challenging, due to the mobility of source end system.This paper
proposes a new approach to bandwidth allocation to higher and lower
priority mobile nodes.In our proposal bandwidth allocation to new
mobile node is based on bandwidth utilization of existing mobile
nodes.The first section of the paper focuses on introduction to
bandwidth allocation in wireless networks and presents the existing
solutions available for allocation of bandwidth. The second section
proposes the new solution for the bandwidth allocation to higher and
lower priority nodes. Finally this paper ends with the analytical
evaluation of the proposed solution.
Abstract: The purpose of this research is to compare the original
intra-oral digital dental radiograph images with images that are
enhanced using a combination of image processing algorithms. Intraoral
digital dental radiograph images are often noisy, blur edges and
low in contrast. A combination of sharpening and enhancement
method are used to overcome these problems. Three types of
proposed compound algorithms used are Sharp Adaptive Histogram
Equalization (SAHE), Sharp Median Adaptive Histogram
Equalization (SMAHE) and Sharp Contrast adaptive histogram
equalization (SCLAHE). This paper presents an initial study of the
perception of six dentists on the details of abnormal pathologies and
improvement of image quality in ten intra-oral radiographs. The
research focus on the detection of only three types of pathology
which is periapical radiolucency, widen periodontal ligament space
and loss of lamina dura. The overall result shows that SCLAHE-s
slightly improve the appearance of dental abnormalities- over the
original image and also outperform the other two proposed
compound algorithms.