Abstract: The scope of this paper is to describe a real electrical
installation of renewable energy using photovoltaic cells. The
displayed power grid connected network was established in 2007 at
area of Northern Greece. The photovoltaic park is composed of 6120
photovoltaic cells able to deliver a total power of 1.101.600 Wp. For
the transformation of DC voltage to AC voltage have been used 25
stand alone three phases inverters and for the connection at the
medium voltage network of Greek Power Authority have been
installed two oil immersed transformer of 630 kVA each one. Due to
the wide space area of installation a specific external lightning
protection system has been designed. Additionally, due to the
sensitive electronics of the control and protection systems of park,
surge protection, equipotent bonding and shielding were also of
major importance.
Abstract: In this study, the use of silicon NAM (Non-Audible
Murmur) microphone in automatic speech recognition is presented.
NAM microphones are special acoustic sensors, which are attached
behind the talker-s ear and can capture not only normal (audible)
speech, but also very quietly uttered speech (non-audible murmur).
As a result, NAM microphones can be applied in automatic speech
recognition systems when privacy is desired in human-machine communication.
Moreover, NAM microphones show robustness against
noise and they might be used in special systems (speech recognition,
speech conversion etc.) for sound-impaired people. Using a small
amount of training data and adaptation approaches, 93.9% word
accuracy was achieved for a 20k Japanese vocabulary dictation
task. Non-audible murmur recognition in noisy environments is also
investigated. In this study, further analysis of the NAM speech has
been made using distance measures between hidden Markov model
(HMM) pairs. It has been shown the reduced spectral space of NAM
speech using a metric distance, however the location of the different
phonemes of NAM are similar to the location of the phonemes
of normal speech, and the NAM sounds are well discriminated.
Promising results in using nonlinear features are also introduced,
especially under noisy conditions.
Abstract: The purpose of this study is to review representative
cases of green space development in order to compare the Garden City
concept and Green Belt concept as applied and to examine its direction
in major Asian and Oceanic cities. The results of previous studies and
this study show that there are two major directions in such
green-oriented city planning. One direction is toward Multi-Regional
Development, and the other focuses on an Environmentally Symbiotic
City based on the Garden City concept. In large cities and the suburbs
where extremely strong pressure to urbanize makes it impossible to
keep Green Belts, it is essential to strictly control land use and adopt
the Garden City concept to conserve the urban environment.
Abstract: Knowledge is indispensable but voluminous knowledge becomes a bottleneck for efficient processing. A great challenge for data mining activity is the generation of large number of potential rules as a result of mining process. In fact sometimes result size is comparable to the original data. Traditional data mining pruning activities such as support do not sufficiently reduce the huge rule space. Moreover, many practical applications are characterized by continual change of data and knowledge, thereby making knowledge voluminous with each change. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. Michalski & Winston proposed Censored Production Rules (CPRs), as an extension of production rules, that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence, are tight or there is simply no information available as to whether it holds or not. Thus the 'If P Then D' part of the CPR expresses important information while the Unless C part acts only as a switch changes the polarity of D to ~D. In this paper a scheme based on Dempster-Shafer Theory (DST) interpretation of a CPR is suggested for discovering CPRs from the discovered flat PRs. The discovery of CPRs from flat rules would result in considerable reduction of the already discovered rules. The proposed scheme incrementally incorporates new knowledge and also reduces the size of knowledge base considerably with each episode. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested cumulative learning scheme would be useful in mining data streams.
Abstract: The uniform Roe C*-algebra (also called uniform translation)C^*- algebra provides a link between coarse geometry and C^*- algebra theory. The uniform Roe algebra has a great importance in geometry, topology and analysis. We consider some of the elementary concepts associated with coarse spaces.
Abstract: Evolutionary robotics is concerned with the design of
intelligent systems with life-like properties by means of simulated
evolution. Approaches in evolutionary robotics can be categorized
according to the control structures that represent the behavior and the
parameters of the controller that undergo adaptation. The basic idea
is to automatically synthesize behaviors that enable the robot to
perform useful tasks in complex environments. The evolutionary
algorithm searches through the space of parameterized controllers
that map sensory perceptions to control actions, thus realizing a
specific robotic behavior. Further, the evolutionary algorithm
maintains and improves a population of candidate behaviors by
means of selection, recombination and mutation. A fitness function
evaluates the performance of the resulting behavior according to the
robot-s task or mission. In this paper, the focus is in the use of
genetic algorithms to solve a multi-objective optimization problem
representing robot behaviors; in particular, the A-Compander Law is
employed in selecting the weight of each objective during the
optimization process. Results using an adaptive fitness function show
that this approach can efficiently react to complex tasks under
variable environments.
Abstract: The paper presents the applications of artificial
intelligence technique called adaptive tabu search to design the
controller of a buck converter. The averaging model derived from the
DQ and generalized state-space averaging methods is applied to
simulate the system during a searching process. The simulations
using such averaging model require the faster computational time
compared with that of the full topology model from the software
packages. The reported model is suitable for the work in the paper in
which the repeating calculation is needed for searching the best
solution. The results will show that the proposed design technique
can provide the better output waveforms compared with those
designed from the classical method.
Abstract: Heuristics-based search methodologies normally
work on searching a problem space of possible solutions toward
finding a “satisfactory" solution based on “hints" estimated from the
problem-specific knowledge. Research communities use different
types of methodologies. Unfortunately, most of the times, these hints
are immature and can lead toward hindering these methodologies by
a premature convergence. This is due to a decrease of diversity in
search space that leads to a total implosion and ultimately fitness
stagnation of the population. In this paper, a novel Decision Maturity
framework (DMF) is introduced as a solution to this problem. The
framework simply improves the decision on the direction of the
search by materializing hints enough before using them. Ideas from
this framework are injected into the particle swarm optimization
methodology. Results were obtained under both static and dynamic
environment. The results show that decision maturity prevents
premature converges to a high degree.
Abstract: A wireless power transfer system can attribute to the
fields in robot, aviation and space in which lightening the weight of
device and improving the movement play an important role. A
wireless power transfer system was investigated to overcome the
inconvenience of using power cable. Especially a wireless power
transfer technology is important element for mobile robots. We
proposed the wireless power transfer system of the half-bridge
resonant converter with the frequency tracking and optimized
power transfer control unit. And the possibility of the application
and development system was verified through the experiment with
LED loads.
Abstract: In this paper; we are interested in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation and new control scheme. We present after the development and the synthesis of a stabilizing control laws design based on sliding mode in order to perform best tracking results. It ensures locally asymptotic stability and desired tracking trajectories. Nonlinear observer is then synthesized in order to estimate the unmeasured states and the effects of the external disturbances such as wind and noise. Finally simulation results are also provided in order to illustrate the performances of the proposed controllers.
Abstract: An automatic method for the extraction of feature points for face based applications is proposed. The system is based upon volumetric feature descriptors, which in this paper has been extended to incorporate scale space. The method is robust to noise and has the ability to extract local and holistic features simultaneously from faces stored in a database. Extracted features are stable over a range of faces, with results indicating that in terms of intra-ID variability, the technique has the ability to outperform manual landmarking.
Abstract: We developed a vision interface immersive projection system, CAVE in virtual rea using hand gesture recognition with computer vis background image was subtracted from current webcam and we convert the color space of the imag Then we mask skin regions using skin color range t a noise reduction operation. We made blobs fro gestures were recognized using these blobs. Using recognition, we could implement an effective bothering devices for CAVE. e framework for an reality research field vision techniques. ent image frame age into HSV space. e threshold and apply from the image and ing our hand gesture e interface without
Abstract: The approaches to make an agent generate intelligent actions in the AI field might be roughly categorized into two ways–the classical planning and situated action system. It is well known that each system have its own strength and weakness. However, each system also has its own application field. In particular, most of situated action systems do not directly deal with the logical problem. This paper first briefly mentions the novel action generator to situatedly extract a set of actions, which is likely to help to achieve the goal at the current situation in the relaxed logical space. After performing the action set, the agent should recognize the situation for deciding the next likely action set. However, since the extracted action is an approximation of the action which helps to achieve the goal, the agent could be caught into the deadlock of the problem. This paper proposes the newly developed hybrid architecture to solve the problem, which combines the novel situated action generator with the conventional planner. The empirical result in some planning domains shows that the quality of the resultant path to the goal is mostly acceptable as well as deriving the fast response time, and suggests the correlation between the structure of problems and the organization of each system which generates the action.
Abstract: The Continuously Adaptive Mean-Shift (CamShift)
algorithm, incorporating scene depth information is combined with
the l1-minimization sparse representation based method to form a
hybrid kernel and state space-based tracking algorithm. We take
advantage of the increased efficiency of the former with the
robustness to occlusion property of the latter. A simple interchange
scheme transfers control between algorithms based upon drift and
occlusion likelihood. It is quantified by the projection of target
candidates onto a depth map of the 2D scene obtained with a low cost
stereo vision webcam. Results are improved tracking in terms of drift
over each algorithm individually, in a challenging practical outdoor
multiple occlusion test case.
Abstract: This paper presents a system for tracking the movement of laparoscopic instruments which is based on an orthogonal system of webcams and video image processing. The movements are captured with two webcams placed orthogonally inside of the physical trainer. On the image, the instruments were detected by using color markers placed on the distal tip of each instrument. The 3D position of the tip of the instrument within the work space was obtained by linear triangulation method. Preliminary results showed linearity and repeatability in the motion tracking with a resolution of 0.616 mm in each axis; the accuracy of the system showed a 3D instrument positioning error of 1.009 ± 0.101 mm. This tool is a portable and low-cost alternative to traditional tracking devices and a trustable method for the objective evaluation of the surgeon’s surgical skills.
Abstract: Space exploration is a highly visible endeavour of
humankind to seek profound answers to questions about the origins
of our solar system, whether life exists beyond Earth, and how we
could live on other worlds. Different platforms have been utilized in
planetary exploration missions, such as orbiters, landers, rovers, and
penetrators.
Having low mass, good mechanical contact with the surface,
ability to acquire high quality scientific subsurface data, and ability to
be deployed in areas that may not be conducive to landers or rovers,
Penetrators provide an alternative and complimentary solution that
makes possible scientific exploration of hardly accessible sites (icy
areas, gully sites, highlands etc.).
The Canadian Space Agency (CSA) has put space exploration as
one of the pillars of its space program, and established ExCo program
to prepare Canada for future international planetary exploration.
ExCo sets surface mobility as its focus and priority, and invests
mainly in the development of rovers because of Canada's niche space
robotics technology. Meanwhile, CSA is also investigating how
micro-penetrators can help Canada to fulfill its scientific objectives
for planetary exploration.
This paper presents a review of the micro-penetrator technologies,
past missions, and lessons learned. It gives a detailed analysis of the
technical challenges of micro-penetrators, such as high impact
survivability, high precision guidance navigation and control, thermal
protection, communications, and etc. Then, a Canadian perspective of
a possible micro-penetrator mission is given, including Canadian
scientific objectives and priorities, potential instruments, and flight
opportunities.
Abstract: This paper presents a method for determining the
uniaxial tensile properties such as Young-s modulus, yield strength
and the flow behaviour of a material in a virtually non-destructive
manner. To achieve this, a new dumb-bell shaped miniature
specimen has been designed. This helps in avoiding the removal of
large size material samples from the in-service component for the
evaluation of current material properties. The proposed miniature
specimen has an advantage in finite element modelling with respect
to computational time and memory space. Test fixtures have been
developed to enable the tension tests on the miniature specimen in a
testing machine. The studies have been conducted in a chromium
(H11) steel and an aluminum alloy (AR66). The output from the
miniature test viz. load-elongation diagram is obtained and the finite
element simulation of the test is carried out using a 2D plane stress
analysis. The results are compared with the experimental results. It is
observed that the results from the finite element simulation
corroborate well with the miniature test results. The approach seems
to have potential to predict the mechanical properties of the
materials, which could be used in remaining life estimation of the
various in-service structures.
Abstract: This paper describes new computer vision algorithms
that have been developed to track moving objects as part of a
long-term study into the design of (semi-)autonomous vehicles. We
present the results of a study to exploit variable kernels for tracking in
video sequences. The basis of our work is the mean shift
object-tracking algorithm; for a moving target, it is usual to define a
rectangular target window in an initial frame, and then process the data
within that window to separate the tracked object from the background
by the mean shift segmentation algorithm. Rather than use the
standard, Epanechnikov kernel, we have used a kernel weighted by the
Chamfer distance transform to improve the accuracy of target
representation and localization, minimising the distance between the
two distributions in RGB color space using the Bhattacharyya
coefficient. Experimental results show the improved tracking
capability and versatility of the algorithm in comparison with results
using the standard kernel. These algorithms are incorporated as part of
a robot test-bed architecture which has been used to demonstrate their
effectiveness.
Abstract: Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.
Abstract: Traffic density, an indicator of traffic
conditions, is one of the most critical characteristics to
Intelligent Transport Systems (ITS). This paper investigates
recursive traffic density estimation using the information
provided from inductive loop detectors. On the basis of the
phenomenological relationship between speed and density, the
existing studies incorporate a state space model and update the
density estimate using vehicular speed observations via the
extended Kalman filter, where an approximation is made
because of the linearization of the nonlinear observation
equation. In practice, this may lead to substantial estimation
errors. This paper incorporates a suitable transformation to
deal with the nonlinear observation equation so that the
approximation is avoided when using Kalman filter to
estimate the traffic density. A numerical study is conducted. It
is shown that the developed method outperforms the existing
methods for traffic density estimation.