Abstract: This paper explores the importance of privacy in a
contemporary online world. Crucial to the discussion is the idea of
the Lacanian postmodern fragmented self and the problem of how to
ensure that we have room to fully explore various aspects of our
personalities in an environment which is–or at least feels--safe and
free from observation by others. The paper begins with an
exploration of the idea of the self with particular regard to the ways
in which contemporary life and technology seems to have multiplied
the various faces or masks which we present in different contexts. A
brief history of privacy and surveillance follows. Finally, the paper
ends with an affirmation of the importance of private space as an
essential component of our spiritual and emotional well-being in
today-s wired world.
Abstract: Climate change could lead to changes in cultural
environments and landscapes as we know them.Climate change
presents an immediate and significant threat to our natural and built
environments and to the ways of life which co-exist with these
environments. In most traditional buildings, the harmony of texture
with nature and environment has been ever considered; so houses and
cities have been mixed with their natural environment so
astonishingly and the selection and usage of materials have been in
such a way that they have provided the utmost conformity with the
environment, as the result the created areas have a unique beauty and
attraction.The extent to which climate change contributes to
destruction procedure on Iran-s historic buildings.is a subject of
current discussion. Cities, towns and built-up areas also have their
own characteristics that might make them particularly vulnerable to
climate change.
Abstract: The growing interest on national heritage
preservation has led to intensive efforts on digital documentation of
cultural heritage knowledge. Encapsulated within this effort is the
focus on ontology development that will help facilitate the
organization and retrieval of the knowledge. Ontologies surrounding
cultural heritage domain are related to archives, museum and library
information such as archaeology, artifacts, paintings, etc. The growth
in number and size of ontologies indicates the well acceptance of its
semantic enrichment in many emerging applications. Nowadays,
there are many heritage information systems available for access.
Among others is community-based e-museum designed to support the
digital cultural heritage preservation. This work extends previous
effort of developing the Traditional Malay Textile (TMT) Knowledge
Model where the model is designed with the intention of auxiliary
mapping with CIDOC CRM. Due to its internal constraints, the
model needs to be transformed in advance. This paper addresses the
issue by reviewing the previous harmonization works with CIDOC
CRM as exemplars in refining the facets in the model particularly
involving TMT-Artifact class. The result is an extensible model
which could lead to a common view for automated mapping with
CIDOC CRM. Hence, it promotes integration and exchange of
textile information especially batik-related between communities in
e-museum applications.
Abstract: This paper discusses the issue of tribal development,
displacement, rehabilitation and resettlement policies, and
implementation in the agency (scheduled / tribal) areas of the West
Godavari District, Andhra Pradesh State, India. This study is based
on action anthropological approach, conducted among the displaced
tribal communities i.e. Konda Reddis and Nayakapods of this region,
under the 'Kovvada Reservoir' Project. These groups are
traditionally shifting cultivators and popularly known as the
Primitive Tribal Groups (PTGs) in the government records. This
paper also focuses on the issues of tribal displacement and land
alienation due to construction of the Kovvada reservoir, without
proper rehabilitation and resettlement, although there are well
defined guidelines, procedures and norms for the rehabilitation of
Project Affected Persons (PAPs). It is necessary to begin with, to
provide an overview of the issues in tribal development and policies
related to displacement and rehabilitation in the Indian context as a
background to the Kovvada Reservoir Project, the subject of this
study.
Abstract: In the hardening energy context, the transport sector
which constitutes a large worldwide energy demand has to be
improving for decrease energy demand and global warming impacts.
In a controversial situation where subsists an increasing demand for
long-distance and high-speed travels, high-speed trains offer many
advantages, as consuming significantly less energy than road or air
transports.
At the project phase of new rail infrastructures, it is nowadays
important to characterize accurately the energy that will be induced
by its operation phase, in addition to other more classical criteria as
construction costs and travel time.
Current literature consumption models used to estimate railways
operation phase are obsolete or not enough accurate for taking into
account the newest train or railways technologies.
In this paper, an updated model of consumption for high-speed is
proposed, based on experimental data obtained from full-scale tests
performed on a new high-speed line. The assessment of the model
is achieved by identifying train parameters and measured power
consumptions for more than one hundred train routes. Perspectives
are then discussed to use this updated model for accurately assess
the energy impact of future railway infrastructures.
Abstract: In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.
Abstract: Semantic query optimization consists in restricting the
search space in order to reduce the set of objects of interest for a
query. This paper presents an indexing method based on UB-trees
and a static analysis of the constraints associated to the views of the
database and to any constraint expressed on attributes. The result of
the static analysis is a partitioning of the object space into disjoint
blocks. Through Space Filling Curve (SFC) techniques, each
fragment (block) of the partition is assigned a unique identifier,
enabling the efficient indexing of fragments by UB-trees. The search
space corresponding to a range query is restricted to a subset of the
blocks of the partition. This approach has been developed in the
context of a KB-DBMS but it can be applied to any relational
system.
Abstract: Searching similar documents and document
management subjects have important place in text mining. One of the
most important parts of similar document research studies is the
process of classifying or clustering the documents. In this study, a
similar document search approach that includes discussion of out the
case of belonging to multiple categories (multiple categories
problem) has been carried. The proposed method that based on Fuzzy
Similarity Classification (FSC) has been compared with Rocchio
algorithm and naive Bayes method which are widely used in text
mining. Empirical results show that the proposed method is quite
successful and can be applied effectively. For the second stage,
multiple categories vector method based on information of categories
regarding to frequency of being seen together has been used.
Empirical results show that achievement is increased almost two
times, when proposed method is compared with classical approach.
Abstract: Monitored 3-Dimensional (3D) video experience can be utilized as “feedback information” to fine tune the service parameters for providing a better service to the demanding 3D service customers. The 3D video experience which includes both video quality and depth perception is influenced by several contextual and content related factors (e.g., ambient illumination condition, content characteristics, etc) due to the complex nature of the 3D video. Therefore, effective factors on this experience should be utilized while assessing it. In this paper, structural information of the depth map sequences of the 3D video is considered as content related factor effective on the depth perception assessment. Cartoon-like filter is utilized to abstract the significant depth levels in the depth map sequences to determine the structural information. Moreover, subjective experiments are conducted using 3D videos associated with cartoon-like depth map sequences to investigate the effectiveness of ambient illumination condition, which is a contextual factor, on depth perception. Using the knowledge gained through this study, 3D video experience metrics can be developed to deliver better service to the 3D video service users.
Abstract: In this paper, a two-channel secure communication
using fractional chaotic systems is presented. Conditions for chaos
synchronization have been investigated theoretically by using Laplace
transform. To illustrate the effectiveness of the proposed scheme, a
numerical example is presented. The keys, key space, key selection
rules and sensitivity to keys are discussed in detail. Results show that
the original plaintexts have been well masked in the ciphertexts yet
recovered faithfully and efficiently by the present schemes.
Abstract: Content-Based Image Retrieval (CBIR) has been
one on the most vivid research areas in the field of computer vision
over the last 10 years. Many programs and tools have been
developed to formulate and execute queries based on the visual or
audio content and to help browsing large multimedia repositories.
Still, no general breakthrough has been achieved with respect to
large varied databases with documents of difering sorts and with
varying characteristics. Answers to many questions with respect to
speed, semantic descriptors or objective image interpretations are
still unanswered. In the medical field, images, and especially
digital images, are produced in ever increasing quantities and used
for diagnostics and therapy. In several articles, content based
access to medical images for supporting clinical decision making
has been proposed that would ease the management of clinical data
and scenarios for the integration of content-based access methods
into Picture Archiving and Communication Systems (PACS) have
been created. This paper gives an overview of soft computing
techniques. New research directions are being defined that can
prove to be useful. Still, there are very few systems that seem to be
used in clinical practice. It needs to be stated as well that the goal
is not, in general, to replace text based retrieval methods as they
exist at the moment.
Abstract: This paper examines the students’ self-concept among 16- and 17- year- old adolescents in Malaysian secondary schools. Previous studies have shown that positive self-concept played an important role in student adjustment and academic performance during schooling. This study attempts to investigate the factors influencing students’ perceptions toward their own self-concept. A total of 1168 students participated in the survey. This study utilized the CoPs (UM) instrument to measure self-concept. Principal Component Analysis (PCA) revealed three factors: academic selfconcept, physical self-concept and social self-concept. This study confirmed that students perceived certain internal context factors, and revealed that external context factor also have an impact on their self-concept.
Abstract: Development of levels of service in municipal context
is a flexible vehicle to assist in performing quality-cost trade-off
analysis for municipal services. This trade-off depends on the
willingness of a community to pay as well as on the condition of the
assets. Community perspective of the performance of an asset from
service point of view may be quite different from the municipality
perspective of the performance of the same asset from condition
point of view. This paper presents a three phased level of service
based methodology for water mains that consists of :1)development
of an Analytical Hierarchy model of level of service 2) development
of Fuzzy Weighted Sum model of water main condition index and 3)
deriving a Fuzzy logic based function that maps level of service to
asset condition index. This mapping will assist asset managers in
quantifying condition improvement requirement to meet service
goals and to make more informed decisions on interventions and
relayed priorities.
Abstract: This paper proposes different methods for estimation
of the harmonic currents of the single-phase diode bridge rectifier. Both simple and advanced methods are compared and the models are
put into a context of practical use for calculating the harmonic distortion in a typical application. Finally, the different models are
compared to measurements of a real application and convincing results are achieved.
Abstract: Clustering unstructured text documents is an
important issue in data mining community and has a number of
applications such as document archive filtering, document
organization and topic detection and subject tracing. In the real
world, some of the already clustered documents may not be of
importance while new documents of more significance may evolve.
Most of the work done so far in clustering unstructured text
documents overlooks this aspect of clustering. This paper, addresses
this issue by using the Fading Function. The unstructured text
documents are clustered. And for each cluster a statistics structure
called Cluster Profile (CP) is implemented. The cluster profile
incorporates the Fading Function. This Fading Function keeps an
account of the time-dependent importance of the cluster. The work
proposes a novel algorithm Clustering n-ary Merge Algorithm
(CnMA) for unstructured text documents, that uses Cluster Profile
and Fading Function. Experimental results illustrating the
effectiveness of the proposed technique are also included.
Abstract: This paper proposes a novel approach that combines statistical models and support vector machines. A hybrid scheme which appropriately incorporates the advantages of both the generative and discriminant model paradigms is described and evaluated. Support vector machines (SVMs) are trained to divide the whole speakers' space into small subsets of speakers within a hierarchical tree structure. During testing a speech token is assigned to its corresponding group and evaluation using gaussian mixture models (GMMs) is then processed. Experimental results show that the proposed method can significantly improve the performance of text independent speaker identification task. We report improvements of up to 50% reduction in identification error rate compared to the baseline statistical model.
Abstract: Citizens are increasingly are provided with choice and
customization in public services and this has now also become a key
feature of higher education in terms of policy roll-outs on personal
development planning (PDP) and more generally as part of the
employability agenda. The goal here is to transform people, in this
case graduates, into active, responsible citizen-workers. A key part of
this rhetoric and logic is the inculcation of graduate attributes within
students. However, there has also been a concern with the issue of
student lack of engagement and perseverance with their studies. This
paper sets out to explore some of these conceptions that link graduate
attributes with citizenship as well as the notion of how identity is
forged through the higher education process. Examples are drawn
from a quality enhancement project that is being operated within the
context of the Scottish higher education system. This is further
framed within the wider context of competing and conflicting
demands on higher education, exacerbated by the current worldwide
economic climate. There are now pressures on students to develop
their employability skills as well as their capacity to engage with
global issues such as behavioural change in the light of
environmental concerns. It is argued that these pressures, in effect,
lead to a form of personalization that is concerned with how
graduates develop their sense of identity as something that is
engineered and re-engineered to meet these demands.
Abstract: An approach is offered for more precise definition of base lines- borders in handwritten cursive text and general problems of handwritten text segmentation have also been analyzed. An offered method tries to solve problems arose in handwritten recognition with specific slant or in other words, where the letters of the words are not on the same vertical line. As an informative features, some recognition systems use ascending and descending parts of the letters, found after the word-s baseline detection. In such recognition systems, problems in baseline detection, impacts the quality of the recognition and decreases the rate of the recognition. Despite other methods, here borders are found by small pieces containing segmentation elements and defined as a set of linear functions. In this method, separate borders for top and bottom border lines are found. At the end of the paper, as a result, azerbaijani cursive handwritten texts written in Latin alphabet by different authors has been analyzed.
Abstract: In this paper, we propose an approach for the classification of fingerprint databases. It is based on the fact that a fingerprint image is composed of regular texture regions that can be successfully represented by co-occurrence matrices. So, we first extract the features based on certain characteristics of the cooccurrence matrix and then we use these features to train a neural network for classifying fingerprints into four common classes. The obtained results compared with the existing approaches demonstrate the superior performance of our proposed approach.
Abstract: Cellular automata have been used for design of cryptosystems. Recently some secret sharing schemes based on linear memory cellular automata have been introduced which are used for both text and image. In this paper, we illustrate that these secret sharing schemes are vulnerable to dishonest participants- collusion. We propose a cheating model for the secret sharing schemes based on linear memory cellular automata. For this purpose we present a novel uniform model for representation of all secret sharing schemes based on cellular automata. Participants can cheat by means of sending bogus shares or bogus transition rules. Cheaters can cooperate to corrupt a shared secret and compute a cheating value added to it. Honest participants are not aware of cheating and suppose the incorrect secret as the valid one. We prove that cheaters can recover valid secret by removing the cheating value form the corrupted secret. We provide methods of calculating the cheating value.