Abstract: A novel robust audio watermarking scheme is
proposed in this paper. In the proposed scheme, the host audio signals
are segmented into frames. Two consecutive frames are assessed if
they are suitable to represent a watermark bit. If so, frequency
transform is performed on these two frames. The compressionexpansion
technique is adopted to generate distortion over the two
frames. The distortion is used to represent one watermark bit.
Psychoacoustic model is applied to calculate local auditory mask to
ensure that the distortion is not audible. The watermarking schemes
using mono and stereo audio signals are designed differently. The
correlation-based detection method is used to detect the distortion
and extract embedded watermark bits. The experimental results show
that the quality degradation caused by the embedded watermarks is
perceptually transparent and the proposed schemes are very robust
against different types of attacks.
Abstract: Due to the excess of a vehicle operation through its life, some elements may face failure and deteriorate with time. This leads us to carry out maintenance, repair, tune up or full overhaul. After a certain period, the vehicle elements deteriorations increase with time which causes a very high increase of doing the maintenance operations and their costs. However, the logic decision at this point is to replace the current vehicle by a new one with minimum failure and maximum income. The importance of studying vehicle replacement problems come from the increase of stopping days due to many deteriorations in the vehicle parts. These deteriorations increase year after year causing an increase of operating costs and decrease the vehicle income. Vehicle replacement aims to determine the optimum time to keep, maintain, overhaul, renew and replace vehicles. This leads to an improvement in vehicle income, total operating costs, maintenance cost, fuel and oil costs, ton-kilometers, vehicle and engine performance, vehicle noise, vibration, and pollution. The aim of this paper is to find the optimum replacement policies of Kuwait Passenger Transport Company (KPTCP) fleet of busses. The objective of these policies is to maximize the busses pure profits. The dynamic programming (D.P.) technique is used to generate the busses optimal replacement policies
Abstract: In this paper an algorithm based on the adaptive
neuro-fuzzy controller is provided to enhance the tipover stability of
mobile manipulators when they are subjected to predefined
trajectories for the end-effector and the vehicle. The controller
creates proper configurations for the manipulator to prevent the robot
from being overturned. The optimal configuration and thus the most
favorable control are obtained through soft computing approaches
including a combination of genetic algorithm, neural networks, and
fuzzy logic. The proposed algorithm, in this paper, is that a look-up
table is designed by employing the obtained values from the genetic
algorithm in order to minimize the performance index and by using
this data base, rule bases are designed for the ANFIS controller and
will be exerted on the actuators to enhance the tipover stability of the
mobile manipulator. A numerical example is presented to
demonstrate the effectiveness of the proposed algorithm.
Abstract: The search for competitive advantages as one of the
main activities of a company has become a principle of contemporary
theories on Strategic Management. Innovation facilitates a company's
adaptation to the global competitive environment, representing the
important strategic role that it has to play in relation to managerial
performance and, as such, underlines the growing importance of
innovation and the use of a company's technological assets. This
paper therefore studies the effect in the results of four dimensions of
technological innovation strategy on a sample of Spanish wineries,
situated in the Castilla La-Mancha region of Spain, all of which are
registered under the La Mancha Designation of Origin (DO).
Abstract: In this paper a new approach to prioritize urban planning projects in an efficient and reliable way is presented. It is based on environmental pressure indices and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity of rank ordering urban development proposals according to their environmental pressure. The technique combines the use of Environmental Pressure Indicators, the aggregation of indicators in an Environmental Pressure Index by means of the Analytic Network Process method and interpreting the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts- judgments on each of the indicators into one Environmental Pressure Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts- estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The method has been applied to the proposal for urban development of La Carlota airport in Caracas (Venezuela). The Venezuelan Government would like to see a recreational project develop on the abandoned area and mean a significant improvement for the capital. There are currently three options on their table which are currently under evaluation. They include a Health Club, a Residential area and a Theme Park. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional techniques such as environmental impact studies, lifecycle analysis, etc. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods.
Abstract: Automatic reusability appraisal could be helpful in
evaluating the quality of developed or developing reusable software
components and in identification of reusable components from
existing legacy systems; that can save cost of developing the software
from scratch. But the issue of how to identify reusable components
from existing systems has remained relatively unexplored. In this
paper, we have mentioned two-tier approach by studying the
structural attributes as well as usability or relevancy of the
component to a particular domain. Latent semantic analysis is used
for the feature vector representation of various software domains. It
exploits the fact that FeatureVector codes can be seen as documents
containing terms -the idenifiers present in the components- and so
text modeling methods that capture co-occurrence information in
low-dimensional spaces can be used. Further, we devised Neuro-
Fuzzy hybrid Inference System, which takes structural metric values
as input and calculates the reusability of the software component.
Decision tree algorithm is used to decide initial set of fuzzy rules for
the Neuro-fuzzy system. The results obtained are convincing enough
to propose the system for economical identification and retrieval of
reusable software components.
Abstract: Fiber optic sensor technology offers the possibility of
sensing different parameters like strain, temperature, pressure in
harsh environment and remote locations. these kinds of sensors
modulates some features of the light wave in an optical fiber such an
intensity and phase or use optical fiber as a medium for transmitting
the measurement information.
The advantages of fiber optic sensors in contrast to conventional
electrical ones make them popular in different applications and now a
day they consider as a key component in improving industrial
processes, quality control systems, medical diagnostics, and
preventing and controlling general process abnormalities.
This paper is an introduction to fiber optic sensor technology and
some of the applications that make this branch of optic technology,
which is still in its early infancy, an interesting field.
Abstract: The main thrust of this paper is to assess the level of disclosure in the annual reports of non-financial Greek firms and to empirically investigate the hypothesized impact of several firm characteristics on the extent of mandatory disclosure. A disclosure checklist consisting of 100 mandatory items was developed to assess the level of disclosure in the 2009 annual reports of 43 Greek companies listed at the Athens stock exchange. The association between the level of disclosure and some firm characteristics was examined using multiple linear regression analysis. The study reveals that Greek companies on general have responded adequately to the mandatory disclosure requirements of the regulatory bodies. The findings also indicate that firm size was significant positively associated with the level of disclosure. The remaining variables such as age, profitability, liquidity, and board composition were found to be insignificant in explaining the variation of mandatory disclosures. The outcome of this study is undoubtedly of great concern to the investment community at large to assist in evaluating the extent of mandatory disclosure by Greek firms and explaining the variation of disclosure in light of firm-specific characteristics.
Abstract: In this paper a new Genetic Algorithm based on a heuristic operator and Centre of Mass selection operator (CMGA) is designed for the unbounded knapsack problem(UKP), which is NP-Hard combinatorial optimization problem. The proposed genetic algorithm is based on a heuristic operator, which utilizes problem specific knowledge. This center of mass operator when combined with other Genetic Operators forms a competitive algorithm to the existing ones. Computational results show that the proposed algorithm is capable of obtaining high quality solutions for problems of standard randomly generated knapsack instances. Comparative study of CMGA with simple GA in terms of results for unbounded knapsack instances of size up to 200 show the superiority of CMGA. Thus CMGA is an efficient tool of solving UKP and this algorithm is competitive with other Genetic Algorithms also.
Abstract: In order to study the effects of supplemental irrigation, different levels of nitrogen chemical fertilizer and inoculation with rhizobium bacteria on the grain yield of chickpea, an experiment was carried out using split plot arrangement in randomize complete block design with three replication in agricultural researches station of Zanjan, Iran during 2009-2010 cropping season. The factors of experiment consisted of irritation (without irrigation (I1), irrigation at flowering stage (I2), irrigation at flowering and grain filling stages (I3) and full irrigation (I4)) and different levels of nitrogen fertilizer (without using of nitrogen fertilizer (N0), 75 kg.ha-1 (N75), 150 kg.ha-1 (N150) and inoculation with rhizobium bacteria (N4). The results of the analysis of variance showed that the effects of irrigation, nitrogen fertilizer levels and bacterial inoculation, were significant affect on number of pods per plant, number grains per plant, grain weight, grain yield, biological yield and harvest index at 1% probability level. Also Results showed that the grain yield in full irrigation treatment and inoculated with rhizobium bacteria was significantly higher than the other treatments.
Abstract: In this paper test generation methods and appropriate fault models for testing and analysis of embedded systems described as (extended) finite state machines ((E)FSMs) are presented. Compared to simple FSMs, EFSMs specify not only the control flow but also the data flow. Thus, we define a two-level fault model to cover both aspects. The goal of this paper is to reuse well-known FSM-based test generation methods for automation of embedded system testing. These methods have been widely used in testing and validation of protocols and communicating systems. In particular, (E)FSMs-based specification and testing is more advantageous because (E)FSMs support the formal semantic of already standardised formal description techniques (FDTs) despite of their popularity in the design of hardware and software systems.
Abstract: The database reverse engineering problems and
solving processes are getting mature, even though, the academic
community is facing the complex problem of knowledge transfer,
both in university and industrial contexts. This paper presents a new
CASE tool developed at the University of Jordan which addresses an
efficient support of this transfer, namely UJ-CASE-TOOL. It is a
small and self-contained application exhibiting representative
problems and appropriate solutions that can be understood in a
limited time. It presents an algorithm that describes the developed
academic CASE tool which has been used for several years both as
an illustration of the principles of database reverse engineering and
as an exercise aimed at academic and industrial students.
Abstract: Data mining techniques have been used in medical
research for many years and have been known to be effective. In order
to solve such problems as long-waiting time, congestion, and delayed
patient care, faced by emergency departments, this study concentrates
on building a hybrid methodology, combining data mining techniques
such as association rules and classification trees. The methodology is
applied to real-world emergency data collected from a hospital and is
evaluated by comparing with other techniques. The methodology is
expected to help physicians to make a faster and more accurate
classification of chest pain diseases.
Abstract: In this paper, linear multistep technique using power
series as the basis function is used to develop the block methods
which are suitable for generating direct solution of the special second
order ordinary differential equations with associated initial or
boundary conditions. The continuous hybrid formulations enable us
to differentiate and evaluate at some grids and off – grid points to
obtain two different four discrete schemes, each of order (5,5,5,5)T,
which were used in block form for parallel or sequential solutions of
the problems. The computational burden and computer time wastage
involved in the usual reduction of second order problem into system
of first order equations are avoided by this approach. Furthermore, a
stability analysis and efficiency of the block methods are tested on
linear and non-linear ordinary differential equations and the results
obtained compared favorably with the exact solution.
Abstract: This paper is devoted to present and discuss a model that allows a local segmentation by using statistical information of a given image. It is based on Chan-Vese model, curve evolution, partial differential equations and binary level sets method. The proposed model uses the piecewise constant approximation of Chan-Vese model to compute Signed Pressure Force (SPF) function, this one attracts the curve to the true object(s)-s boundaries. The implemented model is used to extract weld defects from weld radiographic images in the aim to calculate the perimeter and surfaces of those weld defects; encouraged resultants are obtained on synthetic and real radiographic images.
Abstract: Mounds are one of the most valuable sources of
information on various aspects of life, household skills, rituals and
beliefs of the ancient peoples of Kazakhstan. Moreover, the objects
associated with the cult of the burial of the dead are the most
informative, and often the only source of knowledge about past eras.
The present study is devoted to some results of the excavations
carried out on the mound "Baygetobe" of Shilikti burial ground. The
purpose of the work is associated with certain categories of grave
goods and reading "Fine Text" of Shilikti graves, whose structure is
the same for burials of nobles and ordinary graves. The safety of a
royal burial mounds, the integrity and completeness of the source are
of particular value for studying.
Abstract: With advances in computer vision, non-contact gaze tracking systems are heading towards being much easier to operate and more comfortable for use, the technique proposed in this paper is specially designed for achieving these goals. For the convenience in operation, the proposal aims at the system with simple configuration which is composed of a fixed wide angle camera and dual infrared illuminators. Then in order to enhance the usability of the system based on single camera, a self-adjusting method which is called Real-time gaze Tracking Algorithm with head movement Compensation (RTAC) is developed for estimating the gaze direction under natural head movement and simplifying the calibration procedure at the same time. According to the actual evaluations, the average accuracy of about 1° is achieved over a field of 20×15×15 cm3.
Abstract: The aim of current research was to investigate ASLT method suitability for accelerated beer shelf-life determination. The research was accomplished on popular Latvian beer: light filtrated and unfiltered pasteurized beer with alcohol content 5.2%; dark filtrated pasteurized beer with alcohol content 4.2% with shelf-life five months. Bottled in dark glass bottles beer samples were storage during 20 weeks at several temperature regimes: +10±1 °C, +20±1 °C, +30±1 °C, +40±1 °C. Samples quality parameters as physically-chemical and microbiological was tested every two weeks using standard methods. It is possible to determine beer shelf-life rapidly during storage at +30±1 °C for filtered pasteurized light beer by 2.5 times, unfiltered pasteurized light beer by 1.4 times and for filtered pasteurized dark beer by 1.7 times. During preset experiments it was proved, that it is possible to determine beer shelf-life rapidly using ASLT method if beer storage temperature could be increased by +10±1 °C.
Abstract: Let n ≥ 3 be an integer and p be a prime odd number. Let us consider Gp(n) the subgroup of (Z/nZ)* defined by : Gp(n) = {x ∈ (Z/nZ)* / xp = 1}. In this paper, we give an algorithm that computes a generating set of this subgroup.
Abstract: The growth and interconnection of power networks in many regions has invited complicated techniques for energy management services (EMS). State estimation techniques become a powerful tool in power system control centers, and that more information is required to achieve the objective of EMS. For the online state estimator, assuming the continuous time is equidistantly sampled with period Δt, processing events must be finished within this period. Advantage of Kalman Filtering (KF) algorithm in using system information to improve the estimation precision is utilized. Computational power is a major issue responsible for the achievement of the objective, i.e. estimators- solution at a small sampled period. This paper presents the optimum utilization of processors in a state estimator based on KF. The model used is presented using Petri net (PN) theory.