Abstract: Because today-s media centric students have adopted
digital as their native form of communication, teachers are having
increasingly difficult time motivating reluctant readers to read and
write. Our research has shown these text-averse individuals can learn
to understand the importance of reading and writing if the instruction
is based on digital narratives. While these students are naturally
attracted to story, they are better at consuming them than creating
them. Therefore, any intervention that utilizes story as its basis needs
to include instruction on the elements of story making. This paper
presents a series of digitally-based tools to identify potential
weaknesses of visually impaired visual learners and to help motivate
these and other media-centric students to select and complete books
that are assigned to them
Abstract: In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.
Abstract: This article examines the emergence and development
of the Kazakhstan species of humanism. The biggest challenge for
Kazakhstan in terms of humanism is connected with advocating
human values in parallel to promoting national interests; preserving
the continuity of traditions in various spheres of life, business and
culture. This should be a common goal for the entire society, the
main direction for a national intelligence, and a platform for the state
policy. An idea worth considering is a formation of national humanist
tradition model; the challenges are adapting people to live in the
context of new industrial and innovative economic conditions,
keeping the balance during intensive economic development of the
country, and ensuring social harmony in the society.
Abstract: The paper deals with cartographic visualisation of
results of transport accessibility monitoring with the use of a semiautomated
method of unipolar anamorphosis, developed by the
authors in the GIS environment. The method is based on
transformation of distance in the map to values of a geographical
phenomenon. In the case of time accessibility it is based on
transformation of isochrones converted into the form of concentric
circles, taking into account selected topographic and thematic
elements in the map. The method is most suitable for analyses of
accessibility to or from a centre and for modelling its long-term
context.
The paper provides a detailed analysis of the procedures and
functionality of the method, discussing the issues of coordinates,
transformation, scale and visualisation. It also offers a discussion of
possible problems and inaccuracies. A practical application of the
method is illustrated by previous research results by the authors in
the filed of accessibility in Czechia.
Abstract: The development of aid's systems for the medical
diagnosis is not easy thing because of presence of inhomogeneities in
the MRI, the variability of the data from a sequence to the other as
well as of other different source distortions that accentuate this
difficulty. A new automatic, contextual, adaptive and robust
segmentation procedure by MRI brain tissue classification is
described in this article. A first phase consists in estimating the
density of probability of the data by the Parzen-Rozenblatt method.
The classification procedure is completely automatic and doesn't
make any assumptions nor on the clusters number nor on the
prototypes of these clusters since these last are detected in an
automatic manner by an operator of mathematical morphology called
skeleton by influence zones detection (SKIZ). The problem of
initialization of the prototypes as well as their number is transformed
in an optimization problem; in more the procedure is adaptive since it
takes in consideration the contextual information presents in every
voxel by an adaptive and robust non parametric model by the
Markov fields (MF). The number of bad classifications is reduced by
the use of the criteria of MPM minimization (Maximum Posterior
Marginal).
Abstract: In recent years linguistic research has turned
increasing attention to covert/overt strategies to modulate authorial
stance and positioning in scientific texts, and to the recipients'
response. This study discussed some theoretical implications of the
use of rhetoric in scientific communication and analysed qualitative
data from the authoritative The Cognitive Neurosciences III (2004)
volume. Its genre-identity, status and readability were considered, in
the social interactive context of contemporary disciplinary discourses
– in their polyphony of traditional and new, emerging genres.
Evidence was given of the ways its famous authors negotiate and
shape knowledge and research results – explicitly appraising team
work and promoting faith in the fast-paced progress of Cognitive
Neuroscience, also through experiential metaphors – by presenting a
set of examples, ordered according to their dominant rhetorical
quality.
Abstract: The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widely used to stop this unwanted flood as it combines good performance with simplicity of the training and classification processes. However, facing the constantly changing patterns of spam, it is necessary to assure online adaptability of the classifier. This work proposes combining such a classifier with another NBC (naïve Bayesian classifier) based on pairs of adjacent words. Only the latter will be retrained with examples of spam reported by users. Tests are performed on considerable sets of mails both from public spam archives and CERN mailboxes. They suggest that this architecture can increase spam recall without affecting the classifier precision as it happens when only the NBC based on single words is retrained.
Abstract: Presents a concept for a multidisciplinary process
supporting effective task transitions between different technical
domains during the architectural design stage.
A system configuration challenge is the multifunctional driven
increased solution space. As a consequence, more iteration is needed
to find a global optimum, i.e. a compromise between involved
disciplines without negative impact on development time. Since state
of the art standards like ISO 15288 and VDI 2206 do not provide a
detailed methodology on multidisciplinary design process, higher
uncertainties regarding final specifications arise. This leads to the
need of more detailed and standardized concepts or processes which
could mitigate risks.
The performed work is based on analysis of multidisciplinary
interaction, of modeling and simulation techniques. To demonstrate
and prove the applicability of the presented concept, it is applied to
the design of aircraft high lift systems, in the context of the
engineering disciplines kinematics, actuation, monitoring, installation
and structure design.
Abstract: Emerging adulthood, between the ages of 18 and 25, as a distinct developmental stage extending from adolescence to young adulthood. The proportions composing the five-factor model are neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. In the literature, there is any study which includes the relationship between emerging adults loneliness and personality traits. Therefore, the relationship between emerging adults loneliness and personality traits have to be investigated. This study examines the association between the Big Five personality traits, and loneliness among Turkish emerging adults. A total of 220 emerging adults completed the NEO Five Factor Inventory (NEO-FFI), and the The UCLA Loneliness Scale (UCLALS). Correlation analysis showed that three Big Five personality dimensions which are Neuroticism (positively), and Extraversion and Aggreableness (negatively) are moderately correlated with emerging adults loneliness. Regression analysis shows that Extraversion, Aggreableness and Neuroticism are the most important predictors of emerging adults loneliness. Results can be discussed in the context of emerging adulthood theory.
Abstract: Views on therapists- attraction have influenced the ethical and professional development of the mental health fields. Because the majority of therapist attraction literature (63.6%) has been conducted from a psychoanalytic standpoint, approaches to attraction from feminist perspectives have not been adequately developed. Considering the lack of a feminist voice regarding attraction, this article attempts to offer a feminist perspective on this issue. The purpose of this article is to offer a feminist perspective on the phenomenon of attraction in order to raise awareness about the importance of power inequalities, intersectionalities, contextual variables and the need for action in the field.
Abstract: Heterogeneity has to be taken into account when
integrating a set of existing information sources into a distributed
information system that are nowadays often based on Service-
Oriented Architectures (SOA). This is also particularly applicable to
distributed services such as event monitoring, which are useful in the
context of Event Driven Architectures (EDA) and Complex Event
Processing (CEP). Web services deal with this heterogeneity at a
technical level, also providing little support for event processing. Our
central thesis is that such a fully generic solution cannot provide
complete support for event monitoring; instead, source specific
semantics such as certain event types or support for certain event
monitoring techniques have to be taken into account. Our core result
is the design of a configurable event monitoring (Web) service that
allows us to trade genericity for the exploitation of source specific
characteristics. It thus delivers results for the areas of SOA, Web
services, CEP and EDA.
Abstract: Nowadays, power systems, energy generation by wind
has been very important. Noting that the production of electrical
energy by wind turbines on site to several factors (such as wind speed
and profile site for the turbines, especially off the wind input speed,
wind rated speed and wind output speed disconnect) is dependent. On
the other hand, several different types of turbines in the market there.
Therefore, selecting a turbine that its capacity could also answer the
need for electric consumers the efficiency is high something is
important and necessary. In this context, calculating the amount of
wind power to help optimize overall network, system operation, in
determining the parameters of wind power is very important.
In this article, to help calculate the amount of wind power plant,
connected to the national network in the region Manjil wind,
selecting the best type of turbine and power delivery profile
appropriate to the network using Monte Carlo method has been.
In this paper, wind speed data from the wind site in Manjil, as minute
and during the year has been. Necessary simulations based on
Random Numbers Simulation method and repeat, using the software
MATLAB and Excel has been done.
Abstract: CIM is the standard formalism for modeling management
information developed by the Distributed Management Task
Force (DMTF) in the context of its WBEM proposal, designed to
provide a conceptual view of the managed environment. In this
paper, we propose the inclusion of formal knowledge representation
techniques, based on Description Logics (DLs) and the Web Ontology
Language (OWL), in CIM-based conceptual modeling, and then we
examine the benefits of such a decision. The proposal is specified as a
CIM metamodel level mapping to a highly expressive subset of DLs
capable of capturing all the semantics of the models. The paper shows
how the proposed mapping can be used for automatic reasoning
about the management information models, as a design aid, by means
of new-generation CASE tools, thanks to the use of state-of-the-art
automatic reasoning systems that support the proposed logic and use
algorithms that are sound and complete with respect to the semantics.
Such a CASE tool framework has been developed by the authors and
its architecture is also introduced. The proposed formalization is not
only useful at design time, but also at run time through the use of
rational autonomous agents, in response to a need recently recognized
by the DMTF.
Abstract: Text categorization is the problem of classifying text
documents into a set of predefined classes. In this paper, we
investigated three approaches to build a meta-classifier in order to
increase the classification accuracy. The basic idea is to learn a metaclassifier
to optimally select the best component classifier for each
data point. The experimental results show that combining classifiers
can significantly improve the accuracy of classification and that our
meta-classification strategy gives better results than each individual
classifier. For 7083 Reuters text documents we obtained a
classification accuracies up to 92.04%.
Abstract: This paper presents a new steganography approach suitable for Arabic texts. It can be classified under steganography feature coding methods. The approach hides secret information bits within the letters benefiting from their inherited points. To note the specific letters holding secret bits, the scheme considers the two features, the existence of the points in the letters and the redundant Arabic extension character. We use the pointed letters with extension to hold the secret bit 'one' and the un-pointed letters with extension to hold 'zero'. This steganography technique is found attractive to other languages having similar texts to Arabic such as Persian and Urdu.
Abstract: The paper proposes an approach using genetic algorithm for computing the region based image similarity. The image is denoted using a set of segmented regions reflecting color and texture properties of an image. An image is associated with a family of image features corresponding to the regions. The resemblance of two images is then defined as the overall similarity between two families of image features, and quantified by a similarity measure, which integrates properties of all the regions in the images. A genetic algorithm is applied to decide the most plausible matching. The performance of the proposed method is illustrated using examples from an image database of general-purpose images, and is shown to produce good results.
Abstract: The inherent iterative nature of product design and development poses significant challenge to reduce the product design and development time (PD). In order to shorten the time to market, organizations have adopted concurrent development where multiple specialized tasks and design activities are carried out in parallel. Iterative nature of work coupled with the overlap of activities can result in unpredictable time to completion and significant rework. Many of the products have missed the time to market window due to unanticipated or rather unplanned iteration and rework. The iterative and often overlapped processes introduce greater amounts of ambiguity in design and development, where the traditional methods and tools of project management provide less value. In this context, identifying critical metrics to understand the iteration probability is an open research area where significant contribution can be made given that iteration has been the key driver of cost and schedule risk in PD projects. Two important questions that the proposed study attempts to address are: Can we predict and identify the number of iterations in a product development flow? Can we provide managerial insights for a better control over iteration? The proposal introduces the concept of decision points and using this concept intends to develop metrics that can provide managerial insights into iteration predictability. By characterizing the product development flow as a network of decision points, the proposed research intends to delve further into iteration probability and attempts to provide more clarity.
Abstract: Under-representation of women in leadership positions" is still a general phenomenon in Germany despite the high number of implemented measures. The under-representation of female executives in the aviation sector is even worse. In this context our research hypothesis is that the representation and acceptance of women in management positions is determined by corporate culture.
Abstract: In this paper a new robust and efficient algorithm to automatic text extraction from colored book and journal cover sheets is proposed. First, we perform wavelet transform. Next for edge detecting from detail wavelet coefficient, we use dynamic threshold. By blurring approximate coefficients with alternative heuristic thresholding, achieve effective edge,. Afterward, with ROI technique get binary image. Finally text boxes would be extracted with new projection profile.
Abstract: A neuron can emit spikes in an irregular time basis and by averaging over a certain time window one would ignore a lot of information. It is known that in the context of fast information processing there is no sufficient time to sample an average firing rate of the spiking neurons. The present work shows that the spiking neurons are capable of computing the radial basis functions by storing the relevant information in the neurons' delays. One of the fundamental findings of the this research also is that when using overlapping receptive fields to encode the data patterns it increases the network-s clustering capacity. The clustering algorithm that is discussed here is interesting from computer science and neuroscience point of view as well as from a perspective.