Abstract: This paper describes a platform that faces the main
research areas for e-learning educational contents. Reusability tackles
the possibility to use contents in different courses reducing costs and
exploiting available data from repositories. In our approach the
production of educational material is based on templates to reuse
learning objects. In terms of interoperability the main challenge lays
on reaching the audience through different platforms. E-learning
solution must track social consumption evolution where nowadays
lots of multimedia contents are accessed through the social networks.
Our work faces it by implementing a platform for generation of
multimedia presentations focused on the new paradigm related to
social media. The system produces videos-courses on top of web
standard SMIL (Synchronized Multimedia Integration Language)
ready to be published and shared. Regarding interfaces it is
mandatory to satisfy user needs and ease communication. To
overcome it the platform deploys virtual teachers that provide natural
interfaces while multimodal features remove barriers to pupils with
disabilities.
Abstract: In this paper, a TSK-type Neuro-fuzzy Inference
System that combines the features of fuzzy sets and neural networks
has been applied for the identification of MIMO systems. The procedure of adapting parameters in TSK model employs a Shuffled
Frog Leaping Algorithm (SFLA) which is inspired from the memetic evolution of a group of frogs when seeking for food. To demonstrate
the accuracy and effectiveness of the proposed controller, two nonlinear systems have been considered as the MIMO plant, and results have been compared with other learning methods based on
Particle Swarm Optimization algorithm (PSO) and Genetic
Algorithm (GA).
Abstract: Cavitation, usually known as a destructive
phenomenon, involves turbulent unsteady two-phase flow. Having
such features, cavitating flows have been turned to a challenging
topic in numerical studies and many researches are being done for
better understanding of bubbly flows and proposing solutions to
reduce its consequent destructive effects. Aeration may be regarded
as an effective protection against cavitation erosion in many
hydraulic structures, like gated tunnels. The paper concerns
numerical simulation of flow in discharge gated tunnel of a dam
using ing RNG k -ε model coupled with the volume of fluid (VOF)
method and the zone which is susceptible of cavitation inception in
the tunnel is predicted. In the second step, a vent is considered in the
mentioned zone for aeration and the numerical simulation is done
again to study the effects of aeration. The results show that aeration
is an impressively useful method to exclude cavitation in mentioned
tunnels.
Abstract: This work discusses an innovative methodology for
deployment of service quality characteristics. Four groups of organizational features that may influence the quality of services are identified: human resource, technology, planning, and organizational
relationships. A House of Service Quality (HOSQ) matrix is built to
extract the desired improvement in the service quality characteristics
and to translate them into a hierarchy of important organizational
features. The Mean Square Error (MSE) criterion enables the
pinpointing of the few essential service quality characteristics to be
improved as well as selection of the vital organizational features. The
method was implemented in an engineering supply enterprise and
provides useful information on its vital service dimensions.
Abstract: Narratives are invaluable assets of human lives. Due to
the distinct features of narratives, they are useful for supporting human
reasoning processes. However, many useful narratives become
residuals in organizations or human minds nowadays. Researchers
have contributed effort to investigate and improve narrative generation
processes. This paper attempts to contemplate essential components in
narratives and explore a computational approach to acquire and extract
knowledge to generate narratives. The methodology and significant
benefit for decision support are presented.
Abstract: This paper describes a novel and effective approach to content-based image retrieval (CBIR) that represents each image in the database by a vector of feature values called “Standard deviation of mean vectors of color distribution of rows and columns of images for CBIR". In many areas of commerce, government, academia, and hospitals, large collections of digital images are being created. This paper describes the approach that uses contents as feature vector for retrieval of similar images. There are several classes of features that are used to specify queries: colour, texture, shape, spatial layout. Colour features are often easily obtained directly from the pixel intensities. In this paper feature extraction is done for the texture descriptor that is 'variance' and 'Variance of Variances'. First standard deviation of each row and column mean is calculated for R, G, and B planes. These six values are obtained for one image which acts as a feature vector. Secondly we calculate variance of the row and column of R, G and B planes of an image. Then six standard deviations of these variance sequences are calculated to form a feature vector of dimension six. We applied our approach to a database of 300 BMP images. We have determined the capability of automatic indexing by analyzing image content: color and texture as features and by applying a similarity measure Euclidean distance.
Abstract: Utilizing echoic intension and distribution from different organs and local details of human body, ultrasonic image can catch important medical pathological changes, which unfortunately may be affected by ultrasonic speckle noise. A feature preserving ultrasonic image denoising and edge enhancement scheme is put forth, which includes two terms: anisotropic diffusion and edge enhancement, controlled by the optimum smoothing time. In this scheme, the anisotropic diffusion is governed by the local coordinate transformation and the first and the second order normal derivatives of the image, while the edge enhancement is done by the hyperbolic tangent function. Experiments on real ultrasonic images indicate effective preservation of edges, local details and ultrasonic echoic bright strips on denoising by our scheme.
Abstract: The Automatic Speech Recognition (ASR) applied to
Arabic language is a challenging task. This is mainly related to the
language specificities which make the researchers facing multiple
difficulties such as the insufficient linguistic resources and the very
limited number of available transcribed Arabic speech corpora. In
this paper, we are interested in the development of a HMM-based
ASR system for Standard Arabic (SA) language. Our fundamental
research goal is to select the most appropriate acoustic parameters
describing each audio frame, acoustic models and speech recognition
unit. To achieve this purpose, we analyze the effect of varying frame
windowing (size and period), acoustic parameter number resulting
from features extraction methods traditionally used in ASR, speech
recognition unit, Gaussian number per HMM state and number of
embedded re-estimations of the Baum-Welch Algorithm. To evaluate
the proposed ASR system, a multi-speaker SA connected-digits
corpus is collected, transcribed and used throughout all experiments.
A further evaluation is conducted on a speaker-independent continue
SA speech corpus. The phonemes recognition rate is 94.02% which is
relatively high when comparing it with another ASR system
evaluated on the same corpus.
Abstract: This paper proposes a novel feature extraction method,
based on Discrete Wavelet Transform (DWT) and K-L Seperability
(KLS), for the classification of Functional Data (FD). This method
combines the decorrelation and reduction property of DWT and the
additive independence property of KLS, which is helpful to extraction
classification features of FD. It is an advanced approach of the
popular wavelet based shrinkage method for functional data reduction
and classification. A theory analysis is given in the paper to prove the
consistent convergence property, and a simulation study is also done
to compare the proposed method with the former shrinkage ones. The
experiment results show that this method has advantages in improving
classification efficiency, precision and robustness.
Abstract: In this study, Friction Stir Processing (FSP) a recent grain refinement technique was employed to disperse micron-sized (2 *m) SiCp particles into aluminum alloy AA6063. The feasibility to fabricate bulk composites through FSP was analyzed and experiments were conducted at different traverse speeds and wider volumes of the specimens. Micro structural observation were carried out by employing optical microscopy test of the cross sections in both parallel and perpendicular to the tool traverse direction. Mechanical property including micro hardness was evaluated in detail at various regions on the specimen. The composites had an excellent bonding with aluminum alloy substrate and a significant increase of 30% in the micro hardness value of metal matrix composite (MMC) as to that of the base metal has observed. The observations clearly indicate that SiC particles were uniformly distributed within the aluminum matrix.
Abstract: Titanium alloys like the modern alloy Ti 6Al 2Sn 4Zr 6Mo (Ti-6246) combine excellent specific mechanical properties and corrosion resistance. On the other hand,due to their material characteristics, machining of these alloys is difficult to perform. The aim of the current study is the analyses of wear mechanisms of coated cemented carbide tools applied in orthogonal cutting experiments of Ti-6246 alloy. Round bars were machined with standard coated tools in dry conditions on a CNC latheusing a wide range of cutting speeds and cutting depths. Tool wear mechanisms were afterwards investigated by means of stereo microscopy, optical microscopy, confocal microscopy and scanning electron microscopy. Wear mechanisms included fracture of the tool tip (total failure) and abrasion. Specific wear features like crater wear, micro cracks and built-up edgeformation appeared depending of the mechanical and thermal conditions generated in the workpiece surface by the cutting action.
Abstract: In this paper we present a new approach to detecting a
flaw in T.O.F.D (Time Of Flight Diffraction) type ultrasonic image
based on texture features. Texture is one of the most important
features used in recognizing patterns in an image. The paper
describes texture features based on 2D Gabor functions, i.e.,
Gaussian shaped band-pass filters, with dyadic treatment of the radial
spatial frequency range and multiple orientations, which represent an
appropriate choice for tasks requiring simultaneous measurement in
both space and frequency domains. The most relevant features are
used as input data on a Fuzzy c-mean clustering classifier. The
classes that exist are only two: 'defects' or 'no defects'. The proposed
approach is tested on the T.O.F.D image achieved at the laboratory
and on the industrial field.
Abstract: Chicken feathers were used as biosorbent for Pb
removal from aqueous solution. In this paper, the kinetics and
equilibrium studies at several pH, temperature, and metal
concentration values are reported. For tested conditions, the Pb
sorption capacity of this poultry waste ranged from 0.8 to 8.3 mg/g.
Optimal conditions for Pb removal by chicken feathers have been
identified. Pseudo-first order and pseudo-second order equations
were used to analyze the experimental data. In addition, the sorption
isotherms were fitted to classical Langmuir and Freundlich models.
Finally, thermodynamic parameters for the sorption process have
been determined. In summary, the results showed that chicken
feathers are an alternative and promising sorbent for the treatment of
effluents polluted by Pb ions.
Abstract: In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.
Abstract: The improvement of quality of life is the main visible
integrated indicator of state well-being. More and more states pay
attention to define and to achieve social standards of quality of life as
social-economic strategy of development. These standards are
determinate by state features, complex of needs and interests of
individual, family and society.
It still remains in open question: “What is middle class" in
contemporary Kazakhstan. Appearance of new social standards of
quality of life is important indicator of its successful establishment.
The middle class as agent of social, politic and economic reforms
promotes to improve the quality of life of the country. But if consider
a low and a middle stratums of middle class, we can see that high
social expectations and real achievements are still significantly
different.
The article relies on the sociological data, collected during of
search of household-s standards of living in Almaty city and Almaty
region, and case-study of cottage city “Jana Kuat".
Abstract: We introduce an effective approach for automatic offline au- thentication of handwritten samples where the forgeries are skillfully done, i.e., the true and forgery sample appearances are almost alike. Subtle details of temporal information used in online verification are not available offline and are also hard to recover robustly. Thus the spatial dynamic information like the pen-tip pressure characteristics are considered, emphasizing on the extraction of low density pixels. The points result from the ballistic rhythm of a genuine signature which a forgery, however skillful that may be, always lacks. Ten effective features, including these low density points and den- sity ratio, are proposed to make the distinction between a true and a forgery sample. An adaptive decision criteria is also derived for better verification judgements.
Abstract: Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.
Abstract: In this paper, a class of recurrent neural networks (RNNs) with variable delays are studied on almost periodic time scales, some sufficient conditions are established for the existence and global exponential stability of the almost periodic solution. These results have important leading significance in designs and applications of RNNs. Finally, two examples and numerical simulations are presented to illustrate the feasibility and effectiveness of the results.
Abstract: We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also control the alteration of the compressed data. We have noticed a deviation of the entropy of the compressed data after a first embedding. This deviation is greater when the image is a cover medium than when the image is a stego image. To observe this deviation, we pointed out new statistic features and combined them with the Multiple Embedding Method. This approach is motivated by the Avalanche Criterion of the JPEG lossless compression step. This criterion makes possible the design of detectors whose detection rates are independent of the payload. Finally, we designed a Fisher discriminant based classifier for well known steganographic algorithms, Outguess, F5 and Hide and Seek. The experiemental results we obtained show the efficiency of our classifier for these algorithms. Moreover, it is also designed to work with low embedding rates (< 10-5) and according to the avalanche criterion of RLE and Huffman compression step, its efficiency is independent of the quantity of hidden information.
Abstract: This article presents a resistorless current-mode firstorder allpass filter based on second generation current controlled current conveyors (CCCIIs). The features of the circuit are that: the pole frequency can be electronically controlled via the input bias current: the circuit description is very simple, consisting of 2 CCCIIs and single grounded capacitor, without any external resistors and component matching requirements. Consequently, the proposed circuit is very appropriate to further develop into an integrated circuit. Low input and high output impedances of the proposed configuration enable the circuit to be cascaded in current-mode without additional current buffers. The PSpice simulation results are depicted. The given results agree well with the theoretical anticipation. The application example as a current-mode quadrature oscillator is included.