Abstract: This paper investigates the problem of automated defect
detection for textile fabrics and proposes a new optimal filter design
method to solve this problem. Gabor Wavelet Network (GWN) is
chosen as the major technique to extract the texture features from
textile fabrics. Based on the features extracted, an optimal Gabor filter
can be designed. In view of this optimal filter, a new semi-supervised
defect detection scheme is proposed, which consists of one real-valued
Gabor filter and one smoothing filter. The performance of the scheme
is evaluated by using an offline test database with 78 homogeneous
textile images. The test results exhibit accurate defect detection with
low false alarm, thus showing the effectiveness and robustness of the
proposed scheme. To evaluate the detection scheme comprehensively,
a prototyped detection system is developed to conduct a real time test.
The experiment results obtained confirm the efficiency and
effectiveness of the proposed detection scheme.
Abstract: This paper presents a mean for reducing the torque
variation during the revolution of a vertical-axis wind turbine
(VAWT) by increasing the blade number. For this purpose, twodimensional
CDF analysis have been performed on a straight-bladed
Darreius-type rotor. After describing the computational model, a
complete campaign of simulations based on full RANS unsteady
calculations is proposed for a three, four and five-bladed rotor
architecture characterized by a NACA 0025 airfoil. For each
proposed rotor configuration, flow field characteristics are
investigated at several values of tip speed ratio, allowing a
quantification of the influence of blade number on flow geometric
features and dynamic quantities, such as rotor torque and power.
Finally, torque and power curves are compared for the analyzed
architectures, achieving a quantification of the effect of blade number
on overall rotor performance.
Abstract: In this study, the problem of discriminating between interictal epileptic and non- epileptic pathological EEG cases, which present episodic loss of consciousness, investigated. We verify the accuracy of the feature extraction method of autocross-correlated coefficients which extracted and studied in previous study. For this purpose we used in one hand a suitable constructed artificial supervised LVQ1 neural network and in other a cross-correlation technique. To enforce the above verification we used a statistical procedure which based on a chi- square control. The classification and the statistical results showed that the proposed feature extraction is a significant accurate method for diagnostic discrimination cases between interictal and non-interictal EEG events and specifically the classification procedure showed that the LVQ neural method is superior than the cross-correlation one.
Abstract: This paper presents an on-going research work on the
implementation of feature-based machining via macro programming.
Repetitive machining features such as holes, slots, pockets etc can
readily be encapsulated in macros. Each macro consists of methods
on how to machine the shape as defined by the feature. The macro
programming technique comprises of a main program and
subprograms. The main program allows user to select several
subprograms that contain features and define their important
parameters. With macros, complex machining routines can be
implemented easily and no post processor is required. A case study
on machining of a part that comprised of planar face, hole and pocket
features using the macro programming technique was carried out. It
is envisaged that the macro programming technique can be extended
to other feature-based machining fields such as the newly developed
STEP-NC domain.
Abstract: We develop a new interface for Bus-Net which is
optimized for a smartphone. We are continuing to develop the shortest
path planning system of public transportation called "Bus-Net" in
Tottori prefecture as web application to improve the usability of
public transportation. Recent trend of computing platform, however
has shifted to an advanced mobile device called a smartphone such as
iPhone and Android in Japan. A smartphone has different characters
with existing feature phone in terms of OS, large touche panel, and
several other features. We derive a guideline to design the new interface
for a smartphone to full use of the functionality. The guideline is
about simplicity of user-s operation, location awareness and usability.
We developed the new interface for “Bus-Net" on iPhone referring
to the guideline. Due to the evaluation, the application interface we
developed is better than the existing web-based interface in terms of
the usability.
Abstract: This paper aims to propose a novel, robust, and simple method for obtaining a human 3D face model and camera pose (position and orientation) from a video sequence. Given a video sequence of a face recorded from an off-the-shelf digital camera, feature points used to define facial parts are tracked using the Active- Appearance Model (AAM). Then, the face-s 3D structure and camera pose of each video frame can be simultaneously calculated from the obtained point correspondences. This proposed method is primarily based on the combined approaches of Gradient Descent and Powell-s Multidimensional Minimization. Using this proposed method, temporarily occluded point including the case of self-occlusion does not pose a problem. As long as the point correspondences displayed in the video sequence have enough parallax, these missing points can still be reconstructed.
Abstract: The theatre-auditorium under investigation following
the highly reflective characteristics of materials used in it (marble,
painted wood, smooth plaster, etc), architectural and structural
features of the Protocol and its intended use (very multifunctional:
Auditorium, theatre, cinema, musicals, conference room) from the
analysis of the statement of fact made by the acoustic simulation
software Ramsete and supported by data obtained through a
campaign of acoustic measurements of the state of fact made on the
spot by a Fonomet Svantek model SVAN 957, appears to be
acoustically inadequate. After the completion of the 3D model
according to the specifications necessary software used forecast in
order to be recognized by him, have made three simulations, acoustic
simulation of the state of and acoustic simulation of two design
solutions.
Improved noise characteristics found in the first design solution,
compared to the state in fact consists therefore in lowering
Reverberation Time that you turn most desirable value, while the
Indicators of Clarity, the Baricentric Time, the Lateral Efficiency,
Ratio of Low Tmedia BR and defined the Speech Intelligibility
improved significantly. Improved noise characteristics found instead
in the second design solution, as compared to first design solution, is
finally mostly in a more uniform distribution of Leq and in lowering
Reverberation Time that you turn the optimum values. Indicators of
Clarity, and the Lateral Efficiency improve further but at the expense
of a value slightly worse than the BR. Slightly vary the remaining
indices.
Abstract: In the present study, a support vector machine (SVM) learning approach to character recognition is proposed. Simple
feature detectors, similar to those found in the human visual system, were used in the SVM classifier. Alphabetic characters were rotated
to 8 different angles and using the proposed cognitive model, all characters were recognized with 100% accuracy and specificity.
These same results were found in psychiatric studies of human character recognition.
Abstract: With increasing data in medical databases, medical
data retrieval is growing in popularity. Some of this analysis
including inducing propositional rules from databases using many
soft techniques, and then using these rules in an expert system.
Diagnostic rules and information on features are extracted from
clinical databases on diseases of congenital anomaly. This paper
explain the latest soft computing techniques and some of the
adaptive techniques encompasses an extensive group of methods
that have been applied in the medical domain and that are used for
the discovery of data dependencies, importance of features,
patterns in sample data, and feature space dimensionality
reduction. These approaches pave the way for new and interesting
avenues of research in medical imaging and represent an important
challenge for researchers.
Abstract: A set of Artificial Neural Network (ANN) based methods
for the design of an effective system of speech recognition of
numerals of Assamese language captured under varied recording
conditions and moods is presented here. The work is related to
the formulation of several ANN models configured to use Linear
Predictive Code (LPC), Principal Component Analysis (PCA) and
other features to tackle mood and gender variations uttering numbers
as part of an Automatic Speech Recognition (ASR) system in
Assamese. The ANN models are designed using a combination of
Self Organizing Map (SOM) and Multi Layer Perceptron (MLP)
constituting a Learning Vector Quantization (LVQ) block trained in a
cooperative environment to handle male and female speech samples
of numerals of Assamese- a language spoken by a sizable population
in the North-Eastern part of India. The work provides a comparative
evaluation of several such combinations while subjected to handle
speech samples with gender based differences captured by a microphone
in four different conditions viz. noiseless, noise mixed, stressed
and stress-free.
Abstract: Temperature is one of the most principle factors affects aquaculture system. It can cause stress and mortality or superior environment for growth and reproduction. This paper presents the control of pond water temperature using artificial intelligence technique. The water temperature is very important parameter for shrimp growth. The required temperature for optimal growth is 34oC, if temperature increase up to 38oC it cause death of the shrimp, so it is important to control water temperature. Solar thermal water heating system is designed to supply an aquaculture pond with the required hot water in Mersa Matruh in Egypt. Neural networks are massively parallel processors that have the ability to learn patterns through a training experience. Because of this feature, they are often well suited for modeling complex and non-linear processes such as those commonly found in the heating system. Artificial neural network is proposed to control water temperature due to Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques. They have been used to solve complicated practical problems. Moreover this paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the aquaculture system. The simulation results indicate that, the control unit success in keeping water temperature constant at the desired temperature by controlling the hot water flow rate.
Abstract: As a result of the daily workflow in the design
development departments of companies, databases containing huge
numbers of 3D geometric models are generated. According to the
given problem engineers create CAD drawings based on their design
ideas and evaluate the performance of the resulting design, e.g. by
computational simulations. Usually, new geometries are built either
by utilizing and modifying sets of existing components or by adding
single newly designed parts to a more complex design.
The present paper addresses the two facets of acquiring
components from large design databases automatically and providing
a reasonable overview of the parts to the engineer. A unified
framework based on the topographic non-negative matrix
factorization (TNMF) is proposed which solves both aspects
simultaneously. First, on a given database meaningful components
are extracted into a parts-based representation in an unsupervised
manner. Second, the extracted components are organized and
visualized on square-lattice 2D maps. It is shown on the example of
turbine-like geometries that these maps efficiently provide a wellstructured
overview on the database content and, at the same time,
define a measure for spatial similarity allowing an easy access and
reuse of components in the process of design development.
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: For identifying the discriminative sequence features between exons and introns, a new paradigm, rescaled-range frameshift analysis (RRFA), was proposed. By RRFA, two new
sequence features, the frameshift sensitivity (FS) and the accumulative
penta-mer complexity (APC), were discovered which
were further integrated into a new feature of larger scale, the persistency in anti-mutation (PAM). The feature-validation experiments
were performed on six model organisms to test the power
of discrimination. All the experimental results highly support that FS, APC and PAM were all distinguishing features between exons
and introns. These identified new sequence features provide new insights into the sequence composition of genes and they have
great potentials of forming a new basis for recognizing the exonintron boundaries in gene sequences.
Abstract: Speeded-Up Robust Feature (SURF) is commonly used for feature matching in stereovision because of their robustness towards scale changes and rotational changes. However, SURF feature cannot cope with large viewpoint changes or skew distortion. This paper introduces a method which can help to improve the wide baseline-s matching performance in term of accuracy by rectifying the image using two vanishing points. Simplified orientation correction was used to remove the false matching..
Abstract: XML is an important standard of data exchange and
representation. As a mature database system, using relational database
to support XML data may bring some advantages. But storing XML in
relational database has obvious redundancy that wastes disk space,
bandwidth and disk I/O when querying XML data. For the efficiency
of storage and query XML, it is necessary to use compressed XML
data in relational database. In this paper, a compressed relational
database technology supporting XML data is presented. Original
relational storage structure is adaptive to XPath query process. The
compression method keeps this feature. Besides traditional relational
database techniques, additional query process technologies on
compressed relations and for special structure for XML are presented.
In this paper, technologies for XQuery process in compressed
relational database are presented..
Abstract: Ambiguities in effects of earthquake on various
structures in all earthquake codes would necessitate more study and
research concerning influential factors on dynamic behavior.
Previous studies which were done on different features in different
buildings play a major role in the type of response a structure makes
to lateral vibrations. Diagnosing each of these irregularities can help
structure designers in choosing appropriate setbacks for decreasing
possible damages. Therefore vertical setback is one of the irregularity
factors in the height of the building where can be seen in skyscrapers
and hotels. Previous researches reveal notable changes in the place of
these setbacks showing dynamic response of the structure.
Consequently analyzing 48 models of concrete frames for 3, 6 and 9
stories heights with three different bays in general shape of a surface
decline by height have been constructed in ETABS2000 software,
and then the shape effect of each and every one of these frames in
period scale has been discussed. The result of this study reveals that
not only mass, stiffness and height but also shape of the frame is
influential.
Abstract: This paper presents a novel method that allows an
agent host to delegate its signing power to an anonymous mobile
agent in such away that the mobile agent does not reveal any information about its host-s identity and, at the same time, can be authenticated by the service host, hence, ensuring fairness of service
provision. The solution introduces a verification server to verify the
signature generated by the mobile agent in such a way that even if colluding with the service host, both parties will not get more information than what they already have. The solution incorporates
three methods: Agent Signature Key Generation method, Agent
Signature Generation method, Agent Signature Verification method.
The most notable feature of the solution is that, in addition to allowing secure and anonymous signature delegation, it enables
tracking of malicious mobile agents when a service host is attacked. The security properties of the proposed solution are analyzed, and the solution is compared with the most related work.
Abstract: Recognition of characters greatly depends upon the features used. Several features of the handwritten Arabic characters are selected and discussed. An off-line recognition system based on the selected features was built. The system was trained and tested with realistic samples of handwritten Arabic characters. Evaluation of the importance and accuracy of the selected features is made. The recognition based on the selected features give average accuracies of 88% and 70% for the numbers and letters, respectively. Further improvements are achieved by using feature weights based on insights gained from the accuracies of individual features.
Abstract: In this study we propose a novel monitor hydraulic
automatic gauge control (HAGC) system based on fuzzy feedforward
controller. This is used in the development of cold rolling
mill automation system to improve the quality of cold strip. According to features/ properties of entry steel strip like its average
yield stress, width of strip, and desired exit thickness, this controller realizes the compensation for the exit thickness error. The traditional methods of adjusting the roller position, can-t tolerate the variance in
the entry steel strip. The proposed method uses a mathematical model
of the system together with the expert knowledge to perform this adjustment while minimizing the effect of the stated problem. In
order to improve the speed of the controller in rejecting disturbances
introduced by entry strip thickness variations, expert knowledge is added as a feed-forward term to the HAGC system. Simulation
results for the application of the proposed controller to a real cold mill show that the exit strip quality is highly improved.