Abstract: For a long time as a result of accommodating car
traffic, planning ideologies in the past put a low priority on public
space, pedestrianism and the role of city space as a meeting place for
urban dwellers. In addition, according to authors such as Jan Gehl,
market forces and changing architectural perceptions began to shift
the focus of planning practice from the integration of public space in
various pockets around the contemporary city to individual buildings.
Eventually, these buildings have become increasingly more isolated
and introverted and have turned their backs to the realm of the public
space adjoining them. As a result of this practice, the traditional
function of public space as a social forum for city dwellers has in
many cases been reduced or even phased out. Author Jane Jacobs
published her seminal book “The Death and Life of Great American
Cities" more than fifty years ago, but her observations and
predictions at the time still ring true today, where she pointed out
how the dramatic increase in car traffic and its accommodation by the
urban planning ideology that was brought about by the Modern
movement has prompted a separation of the uses of the city. At the
same time it emphasizes free standing buildings that threaten urban
space and city life and result in underutilized and lifeless urban cores.
In this discussion context, the aim of this paper is to showcase a
reversal of just such a situation in the case of the Dasoupolis
neighborhood in Strovolos, Cyprus, where enlightened urban design
practice has see the reclamation of pedestrian space in a car
dominated area.
Abstract: Ontology-based modelling of multi-formatted
software application content is a challenging area in content
management. When the number of software content unit is huge and
in continuous process of change, content change management is
important. The management of content in this context requires
targeted access and manipulation methods. We present a novel
approach to deal with model-driven content-centric information
systems and access to their content. At the core of our approach is an
ontology-based semantic annotation technique for diversely
formatted content that can improve the accuracy of access and
systems evolution. Domain ontologies represent domain-specific
concepts and conform to metamodels. Different ontologies - from
application domain ontologies to software ontologies - capture and
model the different properties and perspectives on a software content
unit. Interdependencies between domain ontologies, the artifacts and
the content are captured through a trace model. The annotation traces
are formalised and a graph-based system is selected for the
representation of the annotation traces.
Abstract: The charnockitic and associated granitic rocks of Akure area were studied for their field and petrographic relationship's. The outcrops locations were plotted in Surfer 8. The granitic rock exhibits a porphyritic texture and outcrops in the north-eastern side of the study area while the charnockitics outcrop in the central/western part. An essentially dark coloured and fine grained intrusive exhibiting xenoliths and xenocrysts (plagioclase phenocrysts) of the granite outcrops between the granitic and charnockitic rocks. Mineralogically, the central rock combines the content of the other two indicating that it is most likely a product of their hybridization. The charnockitic magma is believed to have intruded and assimilated the granite substantially thereby contaminating itself and consequently emplacing the hybrid. The presented model of emplacement elucidates the hybridization proposal. Conclusively, the charnockitics are believed to be (a) younger than the granite, (b) of Pan-African age and (c) of igneous origin.
Abstract: An accurate procedure to determine free vibrations of
beams and plates is presented.
The natural frequencies are exact solutions of governing vibration
equations witch load to a nonlinear homogeny system.
The bilinear and linear structures considered simulate a bridge.
The dynamic behavior of this one is analyzed by using the theory of
the orthotropic plate simply supported on two sides and free on the
two others. The plate can be excited by a convoy of constant or
harmonic loads. The determination of the dynamic response of the
structures considered requires knowledge of the free frequencies and
the shape modes of vibrations. Our work is in this context. Indeed,
we are interested to develop a self-consistent calculation of the Eigen
frequencies.
The formulation is based on the determination of the solution of
the differential equations of vibrations. The boundary conditions
corresponding to the shape modes permit to lead to a homogeneous
system. Determination of the noncommonplace solutions of this
system led to a nonlinear problem in Eigen frequencies.
We thus, develop a computer code for the determination of the
eigenvalues. It is based on a method of bisection with interpolation
whose precision reaches 10 -12. Moreover, to determine the
corresponding modes, the calculation algorithm that we develop uses
the method of Gauss with a partial optimization of the "pivots"
combined with an inverse power procedure. The Eigen frequencies
of a plate simply supported along two opposite sides while
considering the two other free sides are thus analyzed. The results
could be generalized with the case of a beam by regarding it as a
plate with low width.
We give, in this paper, some examples of treated cases. The
comparison with results presented in the literature is completely
satisfactory.
Abstract: Content-Based Image Retrieval has been a major area
of research in recent years. Efficient image retrieval with high
precision would require an approach which combines usage of both
the color and texture features of the image. In this paper we propose
a method for enhancing the capabilities of texture based feature
extraction and further demonstrate the use of these enhanced texture
features in Texture-Based Color Image Retrieval.
Abstract: The paper shows how the CASMAS modeling language,
and its associated pervasive computing architecture, can be
used to facilitate continuity of care by providing members of patientcentered
communities of care with a support to cooperation and
knowledge sharing through the usage of electronic documents and
digital devices. We consider a scenario of clearly fragmented care to
show how proper mechanisms can be defined to facilitate a better
integration of practices and information across heterogeneous care
networks. The scenario is declined in terms of architectural components
and cooperation-oriented mechanisms that make the support
reactive to the evolution of the context where these communities
operate.
Abstract: This paper discusses the investigation of a wearable
textile monopole antenna on specific absorption rate (SAR) for bodycentric
wireless communication applications at 2.45 GHz. The
antenna is characterized on a realistic 8 x 8 x 8 mm3 resolution
truncated Hugo body model in CST Microwave Studio software. The
result exhibited that the simulated SAR values were reduced
significantly by 83.5% as the position of textile monopole was
varying between 0 mm and 15 mm away from the human upper arm.
A power absorption reduction of 52.2% was also noticed as the
distance of textile monopole increased.
Abstract: Performance of any continuous speech recognition system is highly dependent on performance of the acoustic models. Generally, development of the robust spoken language technology relies on the availability of large amounts of data. Common way to cope with little data for training each state of Markov models is treebased state tying. This tying method applies contextual questions to tie states. Manual procedure for question generation suffers from human errors and is time consuming. Various automatically generated questions are used to construct decision tree. There are three approaches to generate questions to construct HMMs based on decision tree. One approach is based on misrecognized phonemes, another approach basically uses feature table and the other is based on state distributions corresponding to context-independent subword units. In this paper, all these methods of automatic question generation are applied to the decision tree on FARSDAT corpus in Persian language and their results are compared with those of manually generated questions. The results show that automatically generated questions yield much better results and can replace manually generated questions in Persian language.
Abstract: As a popular rank-reduced vector space approach,
Latent Semantic Indexing (LSI) has been used in information
retrieval and other applications. In this paper, an LSI-based content
vector model for text classification is presented, which constructs
multiple augmented category LSI spaces and classifies text by their
content. The model integrates the class discriminative information
from the training data and is equipped with several pertinent feature
selection and text classification algorithms. The proposed classifier
has been applied to email classification and its experiments on a
benchmark spam testing corpus (PU1) have shown that the approach
represents a competitive alternative to other email classifiers based
on the well-known SVM and naïve Bayes algorithms.
Abstract: Although, all high school students in Japan are required to learn informatics, many of them do not learn this topic sufficiently. In response to this situation, we propose a support package for high school informatics classes. To examine what students learned and if they sufficiently understood the context of the lessons, a questionnaire survey was distributed to 186 students. We analyzed the results of the questionnaire and determined the weakest units, which were “basic computer configuration” and “memory and secondary storage”. We then developed a package for teaching these units. We propose that our package be applied in high school classrooms.
Abstract: A simple but effective digital watermarking scheme
utilizing a context adaptive variable length coding (CAVLC) method
is presented for wireless communication system. In the proposed
approach, the watermark bits are embedded in the final non-zero
quantized coefficient of each DCT block, thereby yielding a potential
reduction in the length of the coded block. As a result, the
watermarking scheme not only provides the means to check the
authenticity and integrity of the video stream, but also improves the
compression ratio and therefore reduces both the transmission time
and the storage space requirements of the coded video sequence. The
results confirm that the proposed scheme enables the detection of
malicious tampering attacks and reduces the size of the coded H.264
file. Therefore, the current study is feasible to apply in the video
applications of wireless communication such as 3G system
Abstract: In this paper, we present a novel approach to accurately
detect text regions including shop name in signboard images with
complex background for mobile system applications. The proposed
method is based on the combination of text detection using edge
profile and region segmentation using fuzzy c-means method. In the
first step, we perform an elaborate canny edge operator to extract all
possible object edges. Then, edge profile analysis with vertical and
horizontal direction is performed on these edge pixels to detect
potential text region existing shop name in a signboard. The edge
profile and geometrical characteristics of each object contour are
carefully examined to construct candidate text regions and classify the
main text region from background. Finally, the fuzzy c-means
algorithm is performed to segment and detected binarize text region.
Experimental results show that our proposed method is robust in text
detection with respect to different character size and color and can
provide reliable text binarization result.
Abstract: This paper describes the design process and the realtime validation of an innovative autonomous mid-air flight and landing system developed by the Italian Aerospace Research Center in the framework of the Italian national funded project TECVOL (Technologies for the Autonomous Flight). In the paper it is provided an insight of the whole development process of the system under study. In particular, the project framework is illustrated at first, then the functional context and the adopted design and testing approach are described, and finally the on-ground validation test rig on purpose designed is addressed in details. Furthermore, the hardwarein- the-loop validation of the autonomous mid-air flight and landing system by means of the real-time test rig is described and discussed.
Abstract: This study was conducted in Malaysia to discover how
meaning and appreciation were construed among 35 Form Five
students. Panofsky-s theory was employed to discover the levels of
reasoning among students when various types of posters were
displayed. The independent variables used were posters that carried
explicit and implicit meanings; the moderating variable was students-
visual literacy levels while the dependent variable was the implicit
interpretation level. One-way ANOVA was applied for the data
analysis. The data showed that before students were exposed to
Panofsky-s theory, there were differences in thinking between boys,
who did not think abstractly or implicit in comparison to girls. The
study showed that students- visual literacy in posters depended on the
use of visual texts and illustration. This paper discuss further on
posters with text only have a tendency to be too abstract as opposed
to posters with visuals plus text.
Abstract: Crypto System Identification is one of the challenging tasks in Crypt analysis. The paper discusses the possibility of employing Neural Networks for identification of Cipher Systems from cipher texts. Cascade Correlation Neural Network and Back Propagation Network have been employed for identification of Cipher Systems. Very large collection of cipher texts were generated using a Block Cipher (Enhanced RC6) and a Stream Cipher (SEAL). Promising results were obtained in terms of accuracy using both the Neural Network models but it was observed that the Cascade Correlation Neural Network Model performed better compared to Back Propagation Network.
Abstract: Ability of accurate and reliable location estimation in
indoor environment is the key issue in developing great number of
context aware applications and Location Based Services (LBS).
Today, the most viable solution for localization is the Received
Signal Strength (RSS) fingerprinting based approach using wireless
local area network (WLAN). This paper presents two RSS
fingerprinting based approaches – first we employ widely used
WLAN based positioning as a reference system and then investigate
the possibility of using GSM signals for positioning. To compare
them, we developed a positioning system in real world environment,
where realistic RSS measurements were collected. Multi-Layer
Perceptron (MLP) neural network was used as the approximation
function that maps RSS fingerprints and locations. Experimental
results indicate advantage of WLAN based approach in the sense of
lower localization error compared to GSM based approach, but GSM
signal coverage by far outreaches WLAN coverage and for some
LBS services requiring less precise accuracy our results indicate that
GSM positioning can also be a viable solution.
Abstract: The supply chains (SCs) have to appeal to new management paradigms to improve their ability to respond rapidly and cost effectively to unpredictable changes in markets and increasing levels of environmental turbulence, both in terms of volume and variety. In this highly demanded context, the Agile paradigm provides the capabilities to SC quickly adapt to changes in the market requirements. The purpose of this paper is to suggest an Agile Index to assess the agility of the automotive companies and corresponding SCs. The proposed integrated assessment model incorporates Agile practices weighted according to their importance to the automotive SC competitiveness and obtained from the Delphi technique.
Abstract: Image clustering is a process of grouping images
based on their similarity. The image clustering usually uses the color
component, texture, edge, shape, or mixture of two components, etc.
This research aims to explore image clustering using color
composition. In order to complete this image clustering, three main
components should be considered, which are color space, image
representation (feature extraction), and clustering method itself. We
aim to explore which composition of these factors will produce the
best clustering results by combining various techniques from the
three components. The color spaces use RGB, HSV, and L*a*b*
method. The image representations use Histogram and Gaussian
Mixture Model (GMM), whereas the clustering methods use KMeans
and Agglomerative Hierarchical Clustering algorithm. The
results of the experiment show that GMM representation is better
combined with RGB and L*a*b* color space, whereas Histogram is
better combined with HSV. The experiments also show that K-Means
is better than Agglomerative Hierarchical for images clustering.
Abstract: Real world Speaker Identification (SI) application
differs from ideal or laboratory conditions causing perturbations that
leads to a mismatch between the training and testing environment
and degrade the performance drastically. Many strategies have been
adopted to cope with acoustical degradation; wavelet based Bayesian
marginal model is one of them. But Bayesian marginal models
cannot model the inter-scale statistical dependencies of different
wavelet scales. Simple nonlinear estimators for wavelet based
denoising assume that the wavelet coefficients in different scales are
independent in nature. However wavelet coefficients have significant
inter-scale dependency. This paper enhances this inter-scale
dependency property by a Circularly Symmetric Probability Density
Function (CS-PDF) related to the family of Spherically Invariant
Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain
and corresponding joint shrinkage estimator is derived by Maximum
a Posteriori (MAP) estimator. A framework is proposed based on
these to denoise speech signal for automatic speaker identification
problems. The robustness of the proposed framework is tested for
Text Independent Speaker Identification application on 100 speakers
of POLYCOST and 100 speakers of YOHO speech database in three
different noise environments. Experimental results show that the
proposed estimator yields a higher improvement in identification
accuracy compared to other estimators on popular Gaussian Mixture
Model (GMM) based speaker model and Mel-Frequency Cepstral
Coefficient (MFCC) features.
Abstract: Fishbone of Nile Tilapia (Tilapia nilotica), waste from the frozen Nile Tilapia fillet factory, is one of calcium sources. In order to increase fish bone powder value, this study aimed to investigate the effect of Tilapia bone flour (TBF) addition (5, 10, 15% by flour weight) on cooking quality, texture and sensory attributes of noodles. The results indicated that tensile strength, color value (a*) and water absorption of noodles significantly decreased (p£0.05) as the levels of TBF increased from 0-15%. While cooking loss, cooking time and color values (L* and b*) of noodles significantly increased (p£0.05). Sensory evaluation indicated that noodles with 5% TBF received the highest overall acceptability score.