Abstract: In this work we will present a new approach for shot transition auto-detection. Our approach is based on the analysis of Spatio-Temporal Video Slice (STVS) edges extracted from videos. The proposed approach is capable to efficiently detect both abrupt shot transitions 'cuts' and gradual ones such as fade-in, fade-out and dissolve. Compared to other techniques, our method is distinguished by its high level of precision and speed. Those performances are obtained due to minimizing the problem of the boundary shot detection to a simple 2D image partitioning problem.
Abstract: A numerical study is made of laminar, unsteady flow
behind a rotationally oscillating circular cylinder using a recently
developed higher order compact (HOC) scheme. The stream function
vorticity formulation of Navier-Stokes (N-S) equations in cylindrical
polar coordinates are considered as the governing equations. The
temporal behaviour of vortex formation and relevant streamline
patterns of the flow are scrutinized over broad ranges of two
externally specified parameters namely dimensionless forced
oscillating frequency Sf and dimensionless peak rotation rate αm for
the Reynolds-s number Re = 200. Excellent agreements are found
both qualitatively and quantitatively with the existing experimental
and standard numerical results.
Abstract: We report in this paper the procedure of a system of
automatic speech recognition based on techniques of the dynamic
programming. The technique of temporal retiming is a technique
used to synchronize between two forms to compare. We will see how
this technique is adapted to the field of the automatic speech
recognition. We will expose, in a first place, the theory of the
function of retiming which is used to compare and to adjust an
unknown form with a whole of forms of reference constituting the
vocabulary of the application. Then we will give, in the second place,
the various algorithms necessary to their implementation on machine.
The algorithms which we will present were tested on part of the
corpus of words in Arab language Arabdic-10 [4] and gave whole
satisfaction. These algorithms are effective insofar as we apply them
to the small ones or average vocabularies.
Abstract: Fractal analyses of successive event of explosion
earthquake and harmonic tremor recorded at Semeru volcano were
carried out to investigate the dynamical system regarding to their
generating mechanism. The explosive eruptions accompanied by
explosion earthquakes and following volcanic tremor which are
generated by continuous emission of volcanic ash. The fractal
dimension of successive event of explosion and harmonic tremor was
estimated by Critical Exponent Method (CEM). It was found that the
method yield a higher fractal dimension of explosion earthquakes and
gradually decrease during the occurrence of harmonic tremor, and can
be considerably as correlated complexity of the source mechanism
from the variance of fractal dimension.
Abstract: Investigation of soil properties like Cation Exchange
Capacity (CEC) plays important roles in study of environmental
reaserches as the spatial and temporal variability of this property
have been led to development of indirect methods in estimation of
this soil characteristic. Pedotransfer functions (PTFs) provide an
alternative by estimating soil parameters from more readily available
soil data. 70 soil samples were collected from different horizons of
15 soil profiles located in the Ziaran region, Qazvin province, Iran.
Then, multivariate regression and neural network model (feedforward
back propagation network) were employed to develop a
pedotransfer function for predicting soil parameter using easily
measurable characteristics of clay and organic carbon. The
performance of the multivariate regression and neural network model
was evaluated using a test data set. In order to evaluate the models,
root mean square error (RMSE) was used. The value of RMSE and
R2 derived by ANN model for CEC were 0.47 and 0.94 respectively,
while these parameters for multivariate regression model were 0.65
and 0.88 respectively. Results showed that artificial neural network
with seven neurons in hidden layer had better performance in
predicting soil cation exchange capacity than multivariate regression.
Abstract: Extensive rainfall disaggregation approaches have been developed and applied in climate change impact studies such as flood risk assessment and urban storm water management.In this study, five rainfall models that were capable ofdisaggregating daily rainfall data into hourly one were investigated for the rainfall record in theChangi Airport, Singapore. The objectives of this study were (i) to study the temporal characteristics of hourly rainfall in Singapore, and (ii) to evaluate the performance of variousdisaggregation models. The used models included: (i) Rectangular pulse Poisson model (RPPM), (ii) Bartlett-Lewis Rectangular pulse model (BLRPM), (iii) Bartlett-Lewis model with 2 cell types (BL2C), (iv) Bartlett-Lewis Rectangular with cell depth distribution dependent on duration (BLRD), and (v) Neyman-Scott Rectangular pulse model (NSRPM). All of these models werefitted using hourly rainfall data ranging from 1980 to 2005 (which was obtained from Changimeteorological station).The study results indicated that the weight scheme of inversely proportional variance could deliver more accurateoutputs for fitting rainfall patterns in tropical areas, and BLRPM performedrelatively better than other disaggregation models.
Abstract: Ontologies play an important role in semantic web applications and are often developed by different groups and continues to evolve over time. The knowledge in ontologies changes very rapidly that make the applications outdated if they continue to use old versions or unstable if they jump to new versions. Temporal frames using frame versioning and slot versioning are used to take care of dynamic nature of the ontologies. The paper proposes new tags and restructured OWL format enabling the applications to work with the old or new version of ontologies. Gene Ontology, a very dynamic ontology, has been used as a case study to explain the OWL Ontology with Temporal Tags.
Abstract: Decision support systems are usually based on
multidimensional structures which use the concept of hypercube.
Dimensions are the axes on which facts are analyzed and form a
space where a fact is located by a set of coordinates at the
intersections of members of dimensions. Conventional
multidimensional structures deal with discrete facts linked to discrete
dimensions. However, when dealing with natural continuous
phenomena the discrete representation is not adequate. There is a
need to integrate spatiotemporal continuity within multidimensional
structures to enable analysis and exploration of continuous field data.
Research issues that lead to the integration of spatiotemporal
continuity in multidimensional structures are numerous. In this paper,
we discuss research issues related to the integration of continuity in
multidimensional structures, present briefly a multidimensional
model for continuous field data. We also define new aggregation
operations. The model and the associated operations and measures
are validated by a prototype.
Abstract: Hazard rate estimation is one of the important topics
in forecasting earthquake occurrence. Forecasting earthquake
occurrence is a part of the statistical seismology where the main
subject is the point process. Generally, earthquake hazard rate is
estimated based on the point process likelihood equation called the
Hazard Rate Likelihood of Point Process (HRLPP). In this research,
we have developed estimation method, that is hazard rate single
decrement HRSD. This method was adapted from estimation method
in actuarial studies. Here, one individual associated with an
earthquake with inter event time is exponentially distributed. The
information of epicenter and time of earthquake occurrence are used
to estimate hazard rate. At the end, a case study of earthquake hazard
rate will be given. Furthermore, we compare the hazard rate between
HRLPP and HRSD method.
Abstract: A multimedia presentation system refers to the integration of a multimedia database with a presentation manager which has the functionality of content selection, organization and playout of multimedia presentations. It requires high performance of involved system components. Starting from multimedia information capture until the presentation delivery, high performance tools are required for accessing, manipulating, storing and retrieving these segments, for transferring and delivering them in a presentation terminal according to a playout order. The organization of presentations is a complex task in that the display order of presentation contents (in time and space) must be specified. A multimedia presentation contains audio, video, images and text media types. The critical decisions for presentation construction include what the contents are, how the contents are organized, and once the decision is made on the organization of the contents of the presentation, it must be conveyed to the end user in the correct organizational order and in a timely fashion. This paper introduces a framework for specification of multimedia presentations and describes the design of sample presentations using this framework from a multimedia database.
Abstract: In this paper, for the understanding of the phytoplankton dynamics in marine ecosystem, a susceptible and an infected class of phytoplankton population is considered in spatiotemporal domain.
Here, the susceptible phytoplankton is growing logistically and the
growth of infected phytoplankton is due to the instantaneous Holling
type-II infection response function. The dynamics are studied in terms of the local and global stabilities for the system and further
explore the possibility of Hopf -bifurcation, taking the half saturation period as (i.e., ) the bifurcation parameter in temporal domain.
It is also observe that the reaction diffusion system exhibits spatiotemporal
chaos and pattern formation in phytoplankton dynamics,
which is particularly important role play for the spatially extended phytoplankton system. Also the effect of the diffusion coefficient
on the spatial system for both one and two dimensional case is obtained. Furthermore, we explore the higher-order stability analysis
of the spatial phytoplankton system for both linear and no-linear system. Finally, few numerical simulations are carried out for pattern
formation.
Abstract: The purpose of this study is to derive optimal shapes of
a body located in viscous flows by the finite element method using the
acoustic velocity and the four-step explicit scheme. The formulation
is based on an optimal control theory in which a performance function
of the fluid force is introduced. The performance function should be
minimized satisfying the state equation. This problem can be transformed
into the minimization problem without constraint conditions
by using the adjoint equation with adjoint variables corresponding to
the state equation. The performance function is defined by the drag
and lift forces acting on the body. The weighted gradient method
is applied as a minimization technique, the Galerkin finite element
method is used as a spatial discretization and the four-step explicit
scheme is used as a temporal discretization to solve the state equation
and the adjoint equation. As the interpolation, the orthogonal basis
bubble function for velocity and the linear function for pressure
are employed. In case that the orthogonal basis bubble function is
used, the mass matrix can be diagonalized without any artificial
centralization. The shape optimization is performed by the presented
method.
Abstract: A Picard-Newton iteration method is studied to accelerate the numerical solution procedure of a class of two-dimensional nonlinear coupled parabolic-hyperbolic system. The Picard-Newton iteration is designed by adding higher-order terms of small quantity to an existing Picard iteration. The discrete functional analysis and inductive hypothesis reasoning techniques are used to overcome difficulties coming from nonlinearity and coupling, and theoretical analysis is made for the convergence and approximation properties of the iteration scheme. The Picard-Newton iteration has a quadratic convergent ratio, and its solution has second order spatial approximation and first order temporal approximation to the exact solution of the original problem. Numerical tests verify the results of the theoretical analysis, and show the Picard-Newton iteration is more efficient than the Picard iteration.
Abstract: The paper shows some ability to manage two-phase
flows arising from the use of unsteady effects. In one case, we
consider the condition of fragmentation of the interface between the
two components leads to the intensification of mixing. The problem
is solved when the temporal and linear scale are small for the
appearance of the developed mixing layer. Showing that exist such
conditions for unsteady flow velocity at the surface of the channel,
which will lead to the creation and fragmentation of vortices at Re
numbers of order unity. Also showing that the Re is not a criterion of
similarity for this type of flows, but we can introduce a criterion that
depends on both the Re, and the frequency splitting of the vortices. It
turned out that feature of this situation is that streamlines behave
stable, and if we analyze the behavior of the interface between the
components it satisfies all the properties of unstable flows. The other
problem we consider the behavior of solid impurities in the extensive
system of channels. Simulated unsteady periodic flow modeled
breaths. Consider the behavior of the particles along the trajectories.
It is shown that, depending on the mass and diameter of the particles,
they can be collected in a caustic on the channel walls, stop in a
certain place or fly back. Of interest is the distribution of particle
velocity in frequency. It turned out that by choosing a behavior of the
velocity field of the carrier gas can affect the trajectory of individual
particles including force them to fly back.
Abstract: Spatial and mobile computing evolves. This paper
describes a smart modeling platform called “GeoSEMA". This
approach tends to model multidimensional GeoSpatial Evolutionary
and Mobile Agents. Instead of 3D and location-based issues, there
are some other dimensions that may characterize spatial agents, e.g.
discrete-continuous time, agent behaviors. GeoSEMA is seen as a
devoted design pattern motivating temporal geographic-based
applications; it is a firm foundation for multipurpose and
multidimensional special-based applications. It deals with
multipurpose smart objects (buildings, shapes, missiles, etc.) by
stimulating geospatial agents.
Formally, GeoSEMA refers to geospatial, spatio-evolutive and
mobile space constituents where a conceptual geospatial space model
is given in this paper. In addition to modeling and categorizing
geospatial agents, the model incorporates the concept of inter-agents
event-based protocols. Finally, a rapid software-architecture
prototyping GeoSEMA platform is also given. It will be
implemented/ validated in the next phase of our work.
Abstract: Petri Net being one of the most useful graphical tools for modelling complex asynchronous systems, we have used Petri Net to model multi-track railway level crossing system. The roadway has been augmented with four half-size barriers. For better control, a three stage control mechanism has been introduced to ensure that no road-vehicle is trapped on the level crossing. Timed Petri Net is used to include the temporal nature of the signalling system. Safeness analysis has also been included in the discussion section.
Abstract: Emotion recognition is an important research field that finds lots of applications nowadays. This work emphasizes on recognizing different emotions from speech signal. The extracted features are related to statistics of pitch, formants, and energy contours, as well as spectral, perceptual and temporal features, jitter, and shimmer. The Artificial Neural Networks (ANN) was chosen as the classifier. Working on finding a robust and fast ANN classifier suitable for different real life application is our concern. Several experiments were carried out on different ANN to investigate the different factors that impact the classification success rate. Using a database containing 7 different emotions, it will be shown that with a proper and careful adjustment of features format, training data sorting, number of features selected and even the ANN type and architecture used, a success rate of 85% or even more can be achieved without increasing the system complicity and the computation time
Abstract: The use of human hand as a natural interface for humancomputer interaction (HCI) serves as the motivation for research in hand gesture recognition. Vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. In this paper, we use the concept of object-based video abstraction for segmenting the frames into video object planes (VOPs), as used in MPEG-4, with each VOP corresponding to one semantically meaningful hand position. Next, the key VOPs are selected on the basis of the amount of change in hand shape – for a given key frame in the sequence the next key frame is the one in which the hand changes its shape significantly. Thus, an entire video clip is transformed into a small number of representative frames that are sufficient to represent a gesture sequence. Subsequently, we model a particular gesture as a sequence of key frames each bearing information about its duration. These constitute a finite state machine. For recognition, the states of the incoming gesture sequence are matched with the states of all different FSMs contained in the database of gesture vocabulary. The core idea of our proposed representation is that redundant frames of the gesture video sequence bear only the temporal information of a gesture and hence discarded for computational efficiency. Experimental results obtained demonstrate the effectiveness of our proposed scheme for key frame extraction, subsequent gesture summarization and finally gesture recognition.
Abstract: The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower
Abstract: Tourism researchers have recently focused on repeat visitation as a part of destination loyalty. Different models have also considered satisfaction as the main determinant of revisit intention, while findings in many studies show it as a continuous issue. This conceptual paper attempts at evaluating recent empirical studies on satisfaction and revisit intention. Based on limitations and gaps in recent studies, the current paper suggests a new model that would be more comprehensive than those in previous studies. The new model offers new relationships between antecedents (destination image, perceived value, specific novelty seeking, and distance to destination) and both of satisfaction and revisit intention. Revisit intention in turn is suggested to be measured in a temporal approach.