Abstract: This work presents an approach for the construction of a hybrid color-texture space by using mutual information. Feature extraction is done by the Laws filter with SVM (Support Vectors Machine) as a classifier. The classification is applied on the VisTex database and a SPOT HRV (XS) image representing two forest areas in the region of Rabat in Morocco. The result of classification obtained in the hybrid space is compared with the one obtained in the RGB color space.
Abstract: In this work, I present a review on Sparse Distributed
Memory for Small Cues (SDMSCue), a variant of Sparse Distributed
Memory (SDM) that is capable of handling small cues. I then conduct
and show some cognitive experiments on SDMSCue to test its
cognitive soundness compared to SDM. Small cues refer to input
cues that are presented to memory for reading associations; but have
many missing parts or fields from them. The original SDM failed to
handle such a problem. SDMSCue handles and overcomes this
pitfall. The main idea in SDMSCue; is the repeated projection of the
semantic space on smaller subspaces; that are selected based on the
input cue length and pattern. This process allows for Read/Write
operations using an input cue that is missing a large portion.
SDMSCue is augmented with the use of genetic algorithms for
memory allocation and initialization. I claim that SDM functionality
is a subset of SDMSCue functionality.
Abstract: On the basis of Bayesian inference using the
maximizer of the posterior marginal estimate, we carry out phase
unwrapping using multiple interferograms via generalized mean-field
theory. Numerical calculations for a typical wave-front in remote
sensing using the synthetic aperture radar interferometry, phase
diagram in hyper-parameter space clarifies that the present method
succeeds in phase unwrapping perfectly under the constraint of
surface- consistency condition, if the interferograms are not corrupted
by any noises. Also, we find that prior is useful for extending a phase
in which phase unwrapping under the constraint of the
surface-consistency condition. These results are quantitatively
confirmed by the Monte Carlo simulation.
Abstract: We present the results of a case study aiming to assess the reflection of the tourism community in the Web and its usability to propose new ways to communicate visually. The wealth of information contained in the Web and the clear facilities to communicate personals points of view makes of the social web a new space of exploration. In this way, social web allow the sharing of information between communities with similar interests. However, the tourism community remains unexplored as is the case of the information covered in travel stories. Along the Web, we find multiples sites allowing the users to communicate their experiences and personal points of view of a particular place of the world. This cultural heritage is found in multiple documents, usually very little supplemented with photos, so they are difficult to explore due to the lack of visual information. This paper explores the possibility of analyzing travel stories to display them visually on maps and generate new knowledge such as patterns of travel routes. This way, travel narratives published in electronic formats can be very important especially to the tourism community because of the great amount of knowledge that can be extracted. Our approach is based on the use of a Geoparsing Web Service to extract geographic coordinates from travel narratives in order to draw the geo-positions and link the documents into a map image.
Abstract: Solar sunspot rotation, latitudinal bands are studied based on intelligent computation methods. A combination of image fusion method with together tree decomposition is used to obtain quantitative values about the latitudes of trajectories on sun surface that sunspots rotate around them. Daily solar images taken with SOlar and Heliospheric (SOHO) satellite are fused for each month separately .The result of fused image is decomposed with Quad Tree decomposition method in order to achieve the precise information about latitudes of sunspot trajectories. Such analysis is useful for gathering information about the regions on sun surface and coordinates in space that is more expose to solar geomagnetic storms, tremendous flares and hot plasma gases permeate interplanetary space and help human to serve their technical systems. Here sunspot images in September, November and October in 2001 are used for studying the magnetic behavior of sun.
Abstract: The aim of this paper is to determine Frenet-Serret invariants of non-null curves in Lorentzian 5-space. First, we define a vector product of four vectors, by this way, we present a method to calculate Frenet-Serret invariants of the non-null curves. Additionally, an algebraic example of presented method is illustrated.
Abstract: Microwave energy can be used for drying purpose. It is unique process. It is distinctly different from conventional drying process. It is advantageous over conventional drying / heating processes. When microwave energy is used for drying purpose, the process can be accelerated with a better control to achieve uniform heating, more conversion efficiency, selective drying and ultimately improved product quality of the output. Also, less floor space and compact system are the added advantages. Existing low power microwave drying system is to be modified with suitable applicator. Appropriate sensors are to be used to measure parameters like moisture, temperature, weight of sample. Suitable high tech controller is to be used to control microwave power continuously from minimum to maximum. Phase - controller, cycle - controller and PWM - controller are some of the advanced power control techniques. It has been proposed to work on turmeric using high-tech phase controller to control the microwave power conveniently. The drying of turmeric with microwave energy employing phase controller gives better results as formulated in this paper and hence new approach of processing turmeric will open future doors of profit making to allied industries and the farmers.
Abstract: This paper deals with the experimental investigations
of the in-cylinder tumble flows in an unfired internal combustion
engine with a flat piston at the engine speeds ranging from 400 to
1000 rev/min., and also with the dome and dome-cavity pistons at an
engine speed of 1000 rev/min., using particle image velocimetry.
From the two-dimensional in-cylinder flow measurements, tumble
flow analysis is carried out in the combustion space on a vertical
plane passing through cylinder axis. To analyze the tumble flows,
ensemble average velocity vectors are used and to characterize it,
tumble ratio is estimated. From the results, generally, we have found
that tumble ratio varies mainly with crank angle position. Also, at the
end of compression stroke, average turbulent kinetic energy is more
at higher engine speeds. We have also found that, at 330 crank angle
position, flat piston shows an improvement of about 85 and 23% in
tumble ratio, and about 24 and 2.5% in average turbulent kinetic
energy compared to dome and dome-cavity pistons respectively
Abstract: The aim of this paper is to introduce and study a new concept of strong double χ2 (M,A, Δ) of fuzzy numbers and also some properties of the resulting sequence spaces of fuzzy numbers were examined.
Abstract: For the past couple of decades Weak signal detection
is of crucial importance in various engineering and scientific
applications. It finds its application in areas like Wireless
communication, Radars, Aerospace engineering, Control systems and
many of those. Usually weak signal detection requires phase sensitive
detector and demodulation module to detect and analyze the signal.
This article gives you a preamble to intrusion detection system which
can effectively detect a weak signal from a multiplexed signal. By
carefully inspecting and analyzing the respective signal, this
system can successfully indicate any peripheral intrusion. Intrusion
detection system (IDS) is a comprehensive and easy approach
towards detecting and analyzing any signal that is weakened and
garbled due to low signal to noise ratio (SNR). This approach
finds significant importance in applications like peripheral security
systems.
Abstract: The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces. In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem and relatively little researched, rather than discovering classification knowledge as usual in the literatures. The proposed method uses the advantage of uniform population method and addresses the task of generalized rule induction that can be regarded as a generalization of the task of classification. Although the task of generalized rule induction requires a lot of computations, which is usually not satisfied with the normal algorithms, it was demonstrated that this method increased the performance of GAs and rapidly found interesting rules.
Abstract: The Canadian aerospace industry faces many
challenges. One of them is the difficulty in estimating costs. In
particular, the design effort required in a project impacts resource
requirements and lead-time, and consequently the final cost. This
paper presents the findings of a case study conducted for recognized
global leader in the design and manufacturing of aircraft engines. The
study models parametric cost estimation relationships to estimate the
design effort of integrated blade-rotor low-pressure compressor fans.
Several effort drivers are selected to model the relationship.
Comparative analyses of three types of models are conducted. The
model with the best accuracy and significance in design estimation is
retained.
Abstract: This paper presents three new methodologies for the
basic operations, which aim at finding new ways of computing union
(maximum) and intersection (minimum) membership values by
taking into effect the entire membership values in a fuzzy set. The
new methodologies are conceptually simple and easy from the
application point of view and are illustrated with a variety of
problems such as Cartesian product of two fuzzy sets, max –min
composition of two fuzzy sets in different product spaces and an
application of an inverted pendulum to determine the impact of the
new methodologies. The results clearly indicate a difference based on
the nature of the fuzzy sets under consideration and hence will be
highly useful in quite a few applications where different values have
significant impact on the behavior of the system.
Abstract: Autofluorescence (AF) bronchoscopy is an
established method to detect dysplasia and carcinoma in situ (CIS).
For this reason the “Sotiria" Hospital uses the Karl Storz D-light
system. However, in early tumor stages the visualization is not that
obvious. With the help of a PC, we analyzed the color images we
captured by developing certain tools in Matlab®. We used statistical
methods based on texture analysis, signal processing methods based
on Gabor models and conversion algorithms between devicedependent
color spaces. Our belief is that we reduced the error made
by the naked eye. The tools we implemented improve the quality of
patients' life.
Abstract: This paper presents design and implements the
T-DOF PI controller design for a speed control of induction motor.
The voltage source inverter type space vector pulse width modulation
technique is used the drive system. This scheme leads to be able to
adjust the speed of the motor by control the frequency and amplitude
of the input voltage. The ratio of input stator voltage to frequency
should be kept constant. The T-DOF PI controller design by root
locus technique is also introduced to the system for regulates and
tracking speed response. The experimental results in testing the 120
watt induction motor from no-load condition to rated condition show
the effectiveness of the proposed control scheme.
Abstract: In this paper we study some numerical methods to solve a model one-dimensional convection–diffusion equation. The semi-discretisation of the space variable results into a system of ordinary differential equations and the solution of the latter involves the evaluation of a matrix exponent. Since the calculation of this term is computationally expensive, we study some methods based on Krylov subspace and on Restrictive Taylor series approximation respectively. We also consider the Chebyshev Pseudospectral collocation method to do the spatial discretisation and we present the numerical solution obtained by these methods.
Abstract: Eigenvector methods are gaining increasing acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals with real decay constants buried in noise. In particular, MUSIC (Multiple Signal Classification) and minimum-norm techniques are examined. It is shown that these methods perform almost equally well on multiexponential signals with MUSIC displaying better defined peaks.
Abstract: Lately there has been a significant boost of interest in
music digital libraries, which constitute an attractive area of research
and development due to their inherent interesting issues and
challenging technical problems, solutions to which will be highly
appreciated by enthusiastic end-users. We present here a DL that we
have developed to support users in their quest for classical music
pieces within a particular collection of 18,000+ audio recordings.
To cope with the early DL model limitations, we have used a refined
socio-semantic and contextual model that allows rich bibliographic
content description, along with semantic annotations, reviewing,
rating, knowledge sharing etc. The multi-layered service model
allows incorporation of local and distributed information,
construction of rich hypermedia documents, expressing the complex
relationships between various objects and multi-dimensional spaces,
agents, actors, services, communities, scenarios etc., and facilitates
collaborative activities to offer to individual users the needed
collections and services.
Abstract: Historic preservation areas are extremely vulnerable to disasters because they are home to many vulnerable people and contain many closely spaced wooden houses. However, the narrow streets in these regions have historic meaning, which means that they cannot be widened and can become blocked easily during large disasters. Here, we describe our efforts to establish a methodology for the planning of evacuation route sin such historic preservation areas. In particular, this study aims to clarify the effectiveness of measures intended to secure two-way evacuation routes for vulnerable people during large disasters in a historic area preserved under the Cultural Properties Protection Law, Japan.
Abstract: Swarm principles are increasingly being used to design controllers for the coordination of multi-robot systems or, in general, multi-agent systems. This paper proposes a two-dimensional Lagrangian swarm model that enables the planar agents, modeled as point masses, to swarm whilst effectively avoiding each other and obstacles in the environment. A novel method, based on an extended Lyapunov approach, is used to construct the model. Importantly, the Lyapunov method ensures a form of practical stability that guarantees an emergent behavior, namely, a cohesive and wellspaced swarm with a constant arrangement of individuals about the swarm centroid. Computer simulations illustrate this basic feature of collective behavior. As an application, we show how multiple planar mobile unicycle-like robots swarm to eventually form patterns in which their velocities and orientations stabilize.