Abstract: This paper explores the extent of the gap in poverty rates between immigrant and native households in Spanish regions and assess to what extent regional differences in individual and contextual characteristics can explain the divergences in such a gap. By using multilevel techniques and European Union Survey on Income and Living Conditions, we estimate immigrant households experiments an increase of 76 per cent in the odds of being poor compared with a native one when we control by individual variables. In relation to regional differences in the risk of poverty, regionallevel variables have higher effect in the reduction of these differences than individual variables.
Abstract: Mixed model assembly lines (MMAL) are a type of
production line where a variety of product models similar in product
characteristics are assembled. The effective design of these lines
requires that schedule for assembling the different products is
determined. In this paper we tried to fit the sequencing problem with
the main characteristics of make to order (MTO) environment. The
problem solved in this paper is a multiple objective sequencing
problem in mixed model assembly lines sequencing using weighted
Sum Method (WSM) using GAMS software for small problem and
an effective GA for large scale problems because of the nature of
NP-hardness of our problem and vast time consume to find the
optimum solution in large problems. In this problem three practically
important objectives are minimizing: total utility work, keeping a
constant production rate variation, and minimizing earliness and
tardiness cost which consider the priority of each customer and
different due date which is a real situation in mixed model assembly
lines and it is the first time we consider different attribute to
prioritize the customers which help the company to reduce the cost of
earliness and tardiness. This mechanism is a way to apply an advance
available to promise (ATP) in mixed model assembly line sequencing
which is the main contribution of this paper.
Abstract: Study investigates the level and extent of voluntary disclosure practice in Croatia. The research was conducted on the sample of 130 medium and large companies. Findings indicate that two thirds of the companies analyzed disclose below-average number of additional information. The explanatory analyses has shown that firm size, listing status and industrial sector significantly and positively affect the level and extent of voluntary disclosure in the annual report of Croatian companies. On the other hand, profitability and ownership structure were found statistically insignificant. Unlike previous studies, this paper deals with level of voluntary disclosure of medium and large companies, as well as companies whose shares are not listed on the organized capital market, which can be found as our contribution. Also, the research makes contribution by providing the insights into voluntary disclosure practices in Croatia, as a case of macro-oriented accounting system economy, i.e. bank oriented economy with an emerging capital market.
Abstract: The objective of this paper is to characterize the spontaneous Electroencephalogram (EEG) signals of four different motor imagery tasks and to show hereby a possible solution for the present binary communication between the brain and a machine ora Brain-Computer Interface (BCI). The processing technique used in this paper was the fractal analysis evaluated by the Critical Exponent Method (CEM). The EEG signal was registered in 5 healthy subjects,sampling 15 measuring channels at 1024 Hz.Each channel was preprocessed by the Laplacian space ltering so as to reduce the space blur and therefore increase the spaceresolution. The EEG of each channel was segmented and its Fractaldimension (FD) calculated. The FD was evaluated in the time interval corresponding to the motor imagery and averaged out for all the subjects (each channel). In order to characterize the FD distribution,the linear regression curves of FD over the electrodes position were applied. The differences FD between the proposed mental tasks are quantied and evaluated for each experimental subject. The obtained results of the proposed method are a substantial fractal dimension in the EEG signal of motor imagery tasks and can be considerably utilized as the multiple-states BCI applications.
Abstract: In the time of globalisation, growing uncertainty, ambiguity and change, traditional way of doing business are no longer sufficient and it is important to consider non-conventional methods and approaches to release creativity and facilitate innovation and growth. Thus, creative industries, as a natural source of creativity and innovation, draw particular attention. This paper explores feasibility of building creative partnerships between creative industries and business and brings attention to mutual benefits derived from such partnerships. Design/approach - This paper is a theoretical exploration of projects, practices and research findings addressing collaboration between creative industries and business. Thus, it concerns creative industries, arts, business and its representatives in order to define requirements for creative partnerships to work and succeed. Findings – Current practices in engaging into arts-business partnerships are still very few, although most of creative partnerships proved to be highly valuable and mutually beneficial. Certain conditions shall be provided in order to benefit from arts-business creative synergy. Originality/value- By integrating different sources of literature, this article provides a base for conducting empirical research in several dimensions within arts-business partnerships.
Abstract: Background: Blunt aortic trauma (BAT) includes
various morphological changes that occur during deceleration,
acceleration and/or body compression in traffic accidents. The
various forms of BAT, from limited laceration of the intima to
complete transection of the aorta, depends on the force acting on the
vessel wall and the tolerance of the aorta to injury. The force depends
on the change in velocity, the dynamics of the accident and of the
seating position in the car. Tolerance to aortic injury depends on the
anatomy, histological structure and pathomorphological alterations
due to aging or disease of the aortic wall.
An overview of the literature and medical documentation reveals
that different terms are used to describe certain forms of BAT, which
can lead to misinterpretation of findings or diagnoses. We therefore,
propose a classification that would enable uniform systematic
screening of all forms of BAT. We have classified BAT into three
morphologycal types: TYPE I (intramural), TYPE II (transmural) and
TYPE III (multiple) aortic ruptures with appropriate subtypes.
Methods: All car accident casualties examined at the Institute of
Forensic Medicine from 2001 to 2009 were included in this
retrospective study. Autopsy reports were used to determine the
occurrence of each morphological type of BAT in deceased drivers,
front seat passengers and other passengers in cars and to define the
morphology of BAT in relation to the accident dynamics and the age
of the fatalities.
Results: A total of 391 fatalities in car accidents were included in
the study. TYPE I, TYPE II and TYPE III BAT were observed in
10,9%, 55,6% and 33,5%, respectively. The incidence of BAT in
drivers, front seat and other passengers was 36,7%, 43,1% and
28,6%, respectively. In frontal collisions, the incidence of BAT was
32,7%, in lateral collisions 54,2%, and in other traffic accidents
29,3%. The average age of fatalities with BAT was 42,8 years and of
those without BAT 39,1 years.
Conclusion: Identification and early recognition of the risk factors
of BAT following a traffic accident is crucial for successful treatment
of patients with BAT. Front seat passengers over 50 years of age who
have been injured in a lateral collision are the most at risk of BAT.
Abstract: One of the most important applications of
wireless sensor networks is data collection. This paper
proposes as efficient approach for data collection in wireless
sensor networks by introducing Member Forward List. This list
includes the nodes with highest priority for forwarding the data.
When a node fails or dies, this list is used to select the next node
with higher priority. The benefit of this node is that it prevents
the algorithm from repeating when a node fails or dies. The
results show that Member Forward List decreases power
consumption and latency in wireless sensor networks.
Abstract: This paper presents the design and implementation of CASTE, a Cloud-based automatic software test environment. We first present the architecture of CASTE, then the main packages and classes of it are described in detail. CASTE is built upon a private Infrastructure as a Service platform. Through concentrated resource management of virtualized testing environment and automatic execution control of test scripts, we get a better solution to the testing resource utilization and test automation problem. Experiments on CASTE give very appealing results.
Abstract: The paper presents an analytical solution for dispersion
of a solute in the peristaltic motion of a micropolar fluid in the
presence of magnetic field and both homogeneous and heterogeneous
chemical reactions. The average effective dispersion coefficient has
been found using Taylor-s limiting condition under long wavelength
approximation. The effects of various relevant parameters on the average
coefficient of dispersion have been studied. The average effective
dispersion coefficient increases with amplitude ratio, cross viscosity
coefficient and heterogeneous chemical reaction rate parameter. But it
decreases with magnetic field parameter and homogeneous chemical
reaction rate parameter. It can be noted that the presence of peristalsis
enhances dispersion of a solute.
Abstract: Real-time hand tracking is a challenging task in many
computer vision applications such as gesture recognition. This paper
proposes a robust method for hand tracking in a complex environment
using Mean-shift analysis and Kalman filter in conjunction with 3D
depth map. The depth information solve the overlapping problem
between hands and face, which is obtained by passive stereo measuring
based on cross correlation and the known calibration data of
the cameras. Mean-shift analysis uses the gradient of Bhattacharyya
coefficient as a similarity function to derive the candidate of the hand
that is most similar to a given hand target model. And then, Kalman
filter is used to estimate the position of the hand target. The results
of hand tracking, tested on various video sequences, are robust to
changes in shape as well as partial occlusion.
Abstract: These Nowadays the explosion of bombs or explosive
materials such as gas and oil near or inside the buildings cause some
losses in installations and building components. This has made the
engineers to make the buildings and their components resistance
against the effects of explosion. These activities lead to provide
regulations and different methods. The above regulations are mostly
focused on the explosion effects resulting from the vehicles around
the buildings. Therefore, the explosion resulting from the vehicles
outside the buildings will be studied in this research.
In the present study, the main goals are to investigate the
explosion load effects on the structures located on the piles with the
specific quantity of plasticity and observing the permissible response
of these structures. The concentrated mass system and the spring with
two degree of freedom will be used to study the structural system.
Abstract: Sequential pattern mining is a challenging task in data mining area with large applications. One among those applications is mining patterns from weblog. Recent times, weblog is highly dynamic and some of them may become absolute over time. In addition, users may frequently change the threshold value during the data mining process until acquiring required output or mining interesting rules. Some of the recently proposed algorithms for mining weblog, build the tree with two scans and always consume large time and space. In this paper, we build Revised PLWAP with Non-frequent Items (RePLNI-tree) with single scan for all items. While mining sequential patterns, the links related to the nonfrequent items are not considered. Hence, it is not required to delete or maintain the information of nodes while revising the tree for mining updated transactions. The algorithm supports both incremental and interactive mining. It is not required to re-compute the patterns each time, while weblog is updated or minimum support changed. The performance of the proposed tree is better, even the size of incremental database is more than 50% of existing one. For evaluation purpose, we have used the benchmark weblog dataset and found that the performance of proposed tree is encouraging compared to some of the recently proposed approaches.
Abstract: In this paper we present, propose and examine
additional membership functions for the Smoothing Transition
Autoregressive (STAR) models. More specifically, we present the
tangent hyperbolic, Gaussian and Generalized bell functions.
Because Smoothing Transition Autoregressive (STAR) models
follow fuzzy logic approach, more fuzzy membership functions
should be tested. Furthermore, fuzzy rules can be incorporated or
other training or computational methods can be applied as the error
backpropagation or genetic algorithm instead to nonlinear squares.
We examine two macroeconomic variables of US economy, the
inflation rate and the 6-monthly treasury bills interest rates.
Abstract: The anti-lock braking systems installed on vehicles
for safe and effective braking, are high-order nonlinear and timevariant.
Using fuzzy logic controllers increase efficiency of such
systems, but impose a high computational complexity as well. The
main concept introduced by this paper is reducing computational
complexity of fuzzy controllers by deploying problem-solution data
structure. Unlike conventional methods that are based on
calculations, this approach is based on data oriented modeling.
Abstract: Relay based communication has gained considerable importance in the recent years. In this paper we find the end-toend statistics of a two hop non-regenerative relay branch, each hop being Nakagami-m faded. Closed form expressions for the probability density functions of the signal envelope at the output of a selection combiner and a maximal ratio combiner at the destination node are also derived and analytical formulations are verified through computer simulation. These density functions are useful in evaluating the system performance in terms of bit error rate and outage probability.
Abstract: In this research study, an intelligent detection system
to support medical diagnosis and detection of abnormal lesions by
processing endoscopic images is presented. The images used in this
study have been obtained using the M2A Swallowable Imaging
Capsule - a patented, video color-imaging disposable capsule.
Schemes have been developed to extract texture features from the
fuzzy texture spectra in the chromatic and achromatic domains for a
selected region of interest from each color component histogram of
endoscopic images. The implementation of an advanced fuzzy
inference neural network which combines fuzzy systems and
artificial neural networks and the concept of fusion of multiple
classifiers dedicated to specific feature parameters have been also
adopted in this paper. The achieved high detection accuracy of the
proposed system has provided thus an indication that such intelligent
schemes could be used as a supplementary diagnostic tool in
endoscopy.
Abstract: Sequences of execution of algorithms in an interactive
manner using multimedia tools are employed in this paper. It helps to
realize the concept of fundamentals of algorithms such as searching
and sorting method in a simple manner. Visualization gains more
attention than theoretical study and it is an easy way of learning
process. We propose methods for finding runtime sequence of each
algorithm in an interactive way and aims to overcome the drawbacks
of the existing character systems. System illustrates each and every
step clearly using text and animation. Comparisons of its time
complexity have been carried out and results show that our approach
provides better perceptive of algorithms.
Abstract: At very high speeds, bubbles form in the underwater vehicles because of sharp trailing edges or of places where the local pressure is lower than the vapor pressure. These bubbles are called cavities and the size of the cavities grows as the velocity increases. A properly designed cavitator can induce the formation of a single big cavity all over the vehicle. Such a vehicle travelling in the vaporous cavity is called a supercavitating vehicle and the present research work mainly focuses on the dynamic modeling of such vehicles. Cavitation of the fins is also accounted and the effect of the same on trajectory is well explained. The entire dynamics has been developed using the state space approach and emphasis is given on the effect of size and angle of attack of the cavitator. Control law has been established for the motion of the vehicle using Non-linear Dynamic Inverse (NDI) with cavitator as the control surface.
Abstract: Exploring an autistic child in Elementary school is a
difficult task that must be fully thought out and the teachers should
be aware of the many challenges they face raising their child
especially the behavioral problems of autistic children. Hence there
arises a need for developing Artificial intelligence (AI)
Contemporary Techniques to help diagnosis to discover autistic
people.
In this research, we suggest designing architecture of expert
system that combine Cognitive Maps (CM) with Case Based
Reasoning technique (CBR) in order to reduce time and costs of
traditional diagnosis process for the early detection to discover
autistic children. The teacher is supposed to enter child's information
for analyzing by CM module. Then, the reasoning processor would
translate the output into a case to be solved a current problem by
CBR module. We will implement a prototype for the model as a
proof of concept using java and MYSQL.
This will be provided a new hybrid approach that will achieve new
synergies and improve problem solving capabilities in AI. And we
will predict that will reduce time, costs, the number of human errors
and make expertise available to more people who want who want to
serve autistic children and their families.
Abstract: Healthcare issues continue to pose huge problems and incur massive costs. As a result there are many challenging problems still unresolved. In this paper, we will carry out an extensive scientific survey of different areas of management and planning in an attempt to identify where there has already been a substantial contribution from management science methods to healthcare problems and where there is a clear potential for more work to be done. The focus will be on the read-across to the healthcare domain from such approaches applied generally to management and planning and how the methods can be used to improvement patient care. We conclude that, since the healthcare domain significantly differs from traditional areas of management and planning, in some cases there is a need to modify the approaches so as to incorporate the complexities of healthcare, and fully exploit the potential for improvement.