Search results for: Multi class Classification

Authors: Pricillia Priska Sianita

Abstract:

An aesthetic facial profile is one of the goals in Orthodontics treatment. However, this is not easily achieved, especially in patients with Class II Division 1 malocclusion who have the clinical characteristics of convex profile and significant skeletal discrepancy due to mandibular growth deficiency. Malocclusion with skeletal problems require proper treatment timing for growth stimulation, and it must be done in early age and in need of good cooperation from the patient. If this is not done and the patient has passed the growth period, the ideal treatment is orthognathic surgery which is more complicated and more painful. The growth stimulation of skeletal malocclusion requires a careful cephalometric evaluation ranging from diagnosis to determine the parts that require stimulation to post-treatment evaluation to see the success achieved through changes in the measurement of the skeletal parameters shown in the cephalometric analysis. This case report aims to describe skeletal changes cephalometrically that were achieved through orthodontic treatment in growing period. Material and method: Lateral Cephalograms, pre-treatment, and post-treatment of cases of Class II Division 1 malocclusion is selected from a collection of cephalometric radiographic in a private clinic. The Cephalogram is then traced and measured for the skeletal parameters. The result is noted as skeletal condition data of pre-treatment and post-treatment. Furthermore, superimposition is done to see the changes achieved. The results show that growth stimulation through orthodontic treatment can solve the skeletal problem of Class II Division 1 malocclusion and the skeletal changes that occur can be verified through cephalometric analysis. The skeletal changes have an impact on the improvement of patient's facial profile. To sum up, the treatment timing on a skeletal malocclusion is very important to obtain satisfactory results for the improvement of the aesthetic facial profile, and skeletal changes can be verified through cephalometric evaluation of pre- and post-treatment.

Keywords: Cephalometric evaluation, Class II Division 1 malocclusion, growth stimulation, skeletal changes, skeletal problems.

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Authors: I. Khabbazi, R. Ghasemi

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This paper presents a combination of both robust nonlinear controller and nonlinear controller for a class of nonlinear 4Y Octorotor UAV using Back-stepping and sliding mode controller. The robustness against internal and external disturbance and decoupling control are the merits of the proposed paper. The proposed controller decouples the Octorotor dynamical system. The controller is then applied to a 4Y Octortor UAV and its feature will be shown.

Keywords: Backstepping, Decoupling, Octorotor UAV, sliding mode.

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Authors: Somkait Udomhunsakul

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In this paper, a multi-focus image fusion method using Spatial Frequency Measurements (SFM) and Wavelet Packet was proposed. The proposed fusion approach, firstly, the two fused images were transformed and decomposed into sixteen subbands using Wavelet packet. Next, each subband was partitioned into sub-blocks and each block was identified the clearer regions by using the Spatial Frequency Measurement (SFM). Finally, the recovered fused image was reconstructed by performing the Inverse Wavelet Transform. From the experimental results, it was found that the proposed method outperformed the traditional SFM based methods in terms of objective and subjective assessments.

Keywords: Multi-focus image fusion, Wavelet Packet, Spatial Frequency Measurement.

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Authors: Willem Waegeman, Luc Boullart

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Instead of traditional (nominal) classification we investigate the subject of ordinal classification or ranking. An enhanced method based on an ensemble of Support Vector Machines (SVM-s) is proposed. Each binary classifier is trained with specific weights for each object in the training data set. Experiments on benchmark datasets and synthetic data indicate that the performance of our approach is comparable to state of the art kernel methods for ordinal regression. The ensemble method, which is straightforward to implement, provides a very good sensitivity-specificity trade-off for the highest and lowest rank.

Keywords: Ordinal regression, support vector machines, ensemblelearning.

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Authors: Zaineb Ben Messaoud, Dorra Gargouri, Saida Zribi, Ahmed Ben Hamida

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This paper presents a formant-tracking linear prediction (FTLP) model for speech processing in noise. The main focus of this work is the detection of formant trajectory based on Hidden Markov Models (HMM), for improved formant estimation in noise. The approach proposed in this paper provides a systematic framework for modelling and utilization of a time- sequence of peaks which satisfies continuity constraints on parameter; the within peaks are modelled by the LP parameters. The formant tracking LP model estimation is composed of three stages: (1) a pre-cleaning multi-band spectral subtraction stage to reduce the effect of residue noise on formants (2) estimation stage where an initial estimate of the LP model of speech for each frame is obtained (3) a formant classification using probability models of formants and Viterbi-decoders. The evaluation results for the estimation of the formant tracking LP model tested in Gaussian white noise background, demonstrate that the proposed combination of the initial noise reduction stage with formant tracking and LPC variable order analysis, results in a significant reduction in errors and distortions. The performance was evaluated with noisy natual vowels extracted from international french and English vocabulary speech signals at SNR value of 10dB. In each case, the estimated formants are compared to reference formants.

Keywords: Formants Estimation, HMM, Multi Band Spectral Subtraction, Variable order LPC coding, White Gauusien Noise.

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Authors: Anusua Ghosh, Andrew Nafalski, Jeffery Tweedale, Maureen Dollard

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This paper presents anapproach of hybridizing two or more artificial intelligence (AI) techniques which arebeing used to fuzzify the workstress level ranking and categorize the rating accordingly. The use of two or more techniques (hybrid approach) has been considered in this case, as combining different techniques may lead to neutralizing each other-s weaknesses generating a superior hybrid solution. Recent researches have shown that there is a need for a more valid and reliable tools, for assessing work stress. Thus artificial intelligence techniques have been applied in this instance to provide a solution to a psychological application. An overview about the novel and autonomous interactive model for analysing work-stress that has been developedusing multi-agent systems is also presented in this paper. The establishment of the intelligent multi-agent decision analyser (IMADA) using hybridized technique of neural networks and fuzzy logic within the multi-agent based framework is also described.

Keywords: Fuzzy logic, intelligent agent, multi-agent systems, neural network, workplace stress.

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Authors: Hao-Hsiang Ku, Ching-Ho Chi

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Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, backpropagation neural network, and high distributed file system.

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Authors: Turgay Temel, John Hallam

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A recent neurospiking coding scheme for feature extraction from biosonar echoes of various plants is examined with avariety of stochastic classifiers. Feature vectors derived are employedin well-known stochastic classifiers, including nearest-neighborhood,single Gaussian and a Gaussian mixture with EM optimization.Classifiers' performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifers perform equivalently and that the modified preprocessing configuration yields considerably improved results.

Keywords: Classification, neuro-spike coding, non-parametricmodel, parametric model, Gaussian mixture, EM algorithm.

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Authors: M. Vogiatzis, K. Perakis

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Spatial-explicit and up-to-date land use/land cover information is fundamental for spatial planning, land management, sustainable development, and sound decision-making. In the last decade, many satellite-derived land cover products at different spatial, spectral, and temporal resolutions have been developed, such as the European Copernicus Land Cover product. However, more efficient and detailed information for land use/land cover is required at the regional or local scale. A typical Mediterranean basin with a complex landscape comprised of various forest types, crops, artificial surfaces, and wetlands was selected to test and develop our approach. In this study, we investigate the improvement of Copernicus Land Cover product (CLC2018) using Landsat 8 and Sentinel-2 pixel-based classification based on all available existing geospatial data (Forest Maps, LPIS, Natura2000 habitats, cadastral parcels, etc.). We examined and compared the performance of the Random Forest classifier for land use/land cover mapping. In total, 10 land use/land cover categories were recognized in Landsat 8 and 11 in Sentinel-2A. A comparison of the overall classification accuracies for 2018 shows that Landsat 8 classification accuracy was slightly higher than Sentinel-2A (82,99% vs. 80,30%). We concluded that the main land use/land cover types of CLC2018, even within a heterogeneous area, can be successfully mapped and updated according to CLC nomenclature. Future research should be oriented toward integrating spatiotemporal information from seasonal bands and spectral indexes in the classification process.

Keywords: land use/land cover, random forest, Landsat-8 OLI, Sentinel-2A MSI, Corine land cover

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Authors: Padmanabhan Balasubramanian, R. Chinnadurai

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This paper deals with a power-conscious ANDEXOR- Inverter type logic implementation for a complex class of Boolean functions, namely Achilles- heel functions. Different variants of the above function class have been considered viz. positive, negative and pure horn for analysis and simulation purposes. The proposed realization is compared with the decomposed implementation corresponding to an existing standard AND-EXOR logic minimizer; both result in Boolean networks with good testability attribute. It could be noted that an AND-OR-EXOR type logic network does not exist for the positive phase of this unique class of logic function. Experimental results report significant savings in all the power consumption components for designs based on standard cells pertaining to a 130nm UMC CMOS process The simulations have been extended to validate the savings across all three library corners (typical, best and worst case specifications).

Keywords: Achilles' heel functions, AND-EXOR-Inverter logic, CMOS technology, low power design.

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Authors: Hammad T. Janjuhah, Josep Sanjuan, Mohamed K. Salah

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Biological and chemical activities in carbonates are responsible for the complexity of the pore system. Primary porosity is generally of natural origin while secondary porosity is subject to chemical reactivity through diagenetic processes. To understand the integrated part of hydrocarbon exploration, it is necessary to understand the carbonate pore system. However, the current porosity classification scheme is limited to adequately predict the petrophysical properties of different reservoirs having various origins and depositional environments. Rock classification provides a descriptive method for explaining the lithofacies but makes no significant contribution to the application of porosity and permeability (poro-perm) correlation. The Central Luconia carbonate system (Malaysia) represents a good example of pore complexity (in terms of nature and origin) mainly related to diagenetic processes which have altered the original reservoir. For quantitative analysis, 32 high-resolution images of each thin section were taken using transmitted light microscopy. The quantification of grains, matrix, cement, and macroporosity (pore types) was achieved using a petrographic analysis of thin sections and FESEM images. The point counting technique was used to estimate the amount of macroporosity from thin section, which was then subtracted from the total porosity to derive the microporosity. The quantitative observation of thin sections revealed that the mouldic porosity (macroporosity) is the dominant porosity type present, whereas the microporosity seems to correspond to a sum of 40 to 50% of the total porosity. It has been proven that these Miocene carbonates contain a significant amount of microporosity, which significantly complicates the estimation and production of hydrocarbons. Neglecting its impact can increase uncertainty about estimating hydrocarbon reserves. Due to the diversity of geological parameters, the application of existing porosity classifications does not allow a better understanding of the poro-perm relationship. However, the classification can be improved by including the pore types and pore structures where they can be divided into macro- and microporosity. Such studies of microporosity identification/classification represent now a major concern in limestone reservoirs around the world.

Keywords: Carbonate reservoirs, microporosity, overview of porosity classification, reservoir characterization.

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Authors: Abdelouahab Moussaoui, Nabila Ferahta, Victor Chen

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The development of aid's systems for the medical diagnosis is not easy thing because of presence of inhomogeneities in the MRI, the variability of the data from a sequence to the other as well as of other different source distortions that accentuate this difficulty. A new automatic, contextual, adaptive and robust segmentation procedure by MRI brain tissue classification is described in this article. A first phase consists in estimating the density of probability of the data by the Parzen-Rozenblatt method. The classification procedure is completely automatic and doesn't make any assumptions nor on the clusters number nor on the prototypes of these clusters since these last are detected in an automatic manner by an operator of mathematical morphology called skeleton by influence zones detection (SKIZ). The problem of initialization of the prototypes as well as their number is transformed in an optimization problem; in more the procedure is adaptive since it takes in consideration the contextual information presents in every voxel by an adaptive and robust non parametric model by the Markov fields (MF). The number of bad classifications is reduced by the use of the criteria of MPM minimization (Maximum Posterior Marginal).

Keywords: Clustering, Automatic Classification, SKIZ, MarkovFields, Image segmentation, Maximum Posterior Marginal (MPM).

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Authors: Houda Bdiri Gabbouj, Néjib Hassen, Kamel Besbes

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This paper presents a low-voltage low-power differential linear transconductor with near rail-to-rail input swing. Based on the current-mirror OTA topology, the proposed transconductor combines the Flipped Voltage Follower (FVF) technique to linearize the transconductor behavior that leads to class- AB linear operation and the virtual transistor technique to lower the effective threshold voltages of the transistors which offers an advantage in terms of low supply requirement. Design of the OTA has been discussed. It operates at supply voltages of about ±0.8V. Simulation results for 0.18μm TSMC CMOS technology show a good input range of 1Vpp with a high DC gain of 81.53dB and a total harmonic distortion of -40dB at 1MHz for an input of 1Vpp. The main aim of this paper is to present and compare new OTA design with high transconductance, which has a potential to be used in low voltage applications.

Keywords: Amplifier class AB, current mirror, flipped voltage follower, low voltage.

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Authors: S.M. Bahri, F.T. Bendimerad

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We propose a downlink multiple-input multipleoutput (MIMO) multi-carrier code division multiple access (MCCDMA) system with adaptive beamforming algorithm for smart antennas. The algorithm used in this paper is based on the Least Mean Square (LMS), with pilot channel estimation (PCE) and the zero forcing equalizer (ZFE) in the receiver, requiring reference signal and no knowledge channel. MC-CDMA is studied in a multiple antenna context in order to efficiently exploit robustness against multipath effects and multi-user flexibility of MC-CDMA and channel diversity offered by MIMO systems for radio mobile channels. Computer simulations, considering multi-path Rayleigh Fading Channel, interference inter symbol and interference are presented to verify the performance. Simulation results show that the scheme achieves good performance in a multi-user system.

Keywords: Adaptive Beamforming, LMS Algorithm, MCCDMA, MIMO System, Smart Antenna.

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Authors: Surinder Singh, Adish Bindal

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The effects of the pumping wavelength and their power on the gain flattening of a fiber Raman amplifier (FRA) are investigated. The multi-wavelength pumping scheme is utilized to achieve gain flatness in FRA. It is proposed that gain flatness becomes better with increase in number of pumping wavelengths applied. We have achieved flat gain with 0.27 dB fluctuation in a spectral range of 1475-1600 nm for a Raman fiber length of 10 km by using six pumps with wavelengths with in the 1385-1495 nm interval. The effect of multi-wavelength pumping scheme on gain saturation in FRA is also studied. It is proposed that gain saturation condition gets improved by using this scheme and this scheme is more useful for higher spans of Raman fiber length.

Keywords: FRA, gain, pumping, WDM.

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Authors: Andrea Macruz

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This paper explores computation as a process for design by examining how computers can become more than an operative strategy in a designer's toolkit. It documents this, building upon concepts of neuroscience and Antonio Damasio's Homeostasis Theory, which is the control of bodily states through feedback intended to keep conditions favorable for life. To do this, it follows a methodology through algorithmic drawing and discusses the outcomes of three multi-sensory design installations, which culminated from a course in an academic setting. It explains both the studio process that took place to create the installations and the computational process that was developed, related to the fields of algorithmic design and tangible computing. It discusses how designers can use computational range to achieve homeostasis related to sensory data in a multi-sensory installation. The outcomes show clearly how people and computers interact with different sensory modalities and affordances. They propose using computers as meta-physical stabilizers rather than tools.

Keywords: Antonio Damasio, emotional feedback, algorithmic drawing, homeostasis, multi-sensory installation, neuroscience.

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Authors: Atefeh Saljooghi Khoshkar, Jafar Hassanpour

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One of the main problems of design stage relating to many tunneling projects is the lack of an appropriate standard for the provision of engineering geological data in a predefined format. In particular, this is more reflected in highway and railroad tunnels projects in which there is a number of tunnels and different professional teams involved. In this regard, a comprehensive software needs to be designed using the accepted methods in order to help engineering geologists to prepare standard reports, which contain sufficient input data for the design stage. Regarding this necessity, an applied software has been designed using macro capabilities and Visual Basic programming language (VBA) through Microsoft Excel. In this software, all of the engineering geological input data, which are required for designing different parts of tunnels such as discontinuities properties, rock mass strength parameters, rock mass classification systems, boreability classification, the penetration rate and so forth can be calculated and reported in a standard format.

Keywords: Engineering geology, rock mass classification, rock mechanic, tunnel.

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Authors: Jürgen Geiser, Robert Röhle

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In this paper we present modeling and simulation for physical vapor deposition for metallic bipolar plates. In the models we discuss the application of different models to simulate the transport of chemical reactions of the gas species in the gas chamber. The so called sputter process is an extremely sensitive process to deposit thin layers to metallic plates. We have taken into account lower order models to obtain first results with respect to the gas fluxes and the kinetics in the chamber. The model equations can be treated analytically in some circumstances and complicated multi-dimensional models are solved numerically with a software-package (UG unstructed grids, see [1]). Because of multi-scaling and multi-physical behavior of the models, we discuss adapted schemes to solve more accurate in the different domains and scales. The results are discussed with physical experiments to give a valid model for the assumed growth of thin layers.

Keywords: Convection-diffusion equations, multi-scale problem, physical vapor deposition, reaction equations, splitting methods.

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Authors: Hadi Farhadian, Homayoon Katibeh

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In this paper, groundwater seepage into Amirkabir tunnel has been estimated using analytical and numerical methods for 14 different sections of the tunnel. Site Groundwater Rating (SGR) method also has been performed for qualitative and quantitative classification of the tunnel sections. The obtained results of above mentioned methods were compared together. The study shows reasonable accordance with results of the all methods unless for two sections of tunnel. In these two sections there are some significant discrepancies between numerical and analytical results mainly originated from model geometry and high overburden. SGR and the analytical and numerical calculations, confirm high concentration of seepage inflow in fault zones. Maximum seepage flow into tunnel has been estimated 0.425 lit/sec/m using analytical method and 0.628 lit/sec/m using numerical method occured in crashed zone. Based on SGR method, six sections of 14 sections in Amirkabir tunnel axis are found to be in "No Risk" class that is supported by the analytical and numerical seepage value of less than 0.04 lit/sec/m.

Keywords: Water Seepage, Amirkabir Tunnel, Analytical Method, DEM, SGR.

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Authors: Javad Abdalkhani

Abstract:

Convergence of power series solutions for a class of non-linear Abel type equations, including an equation that arises in nonlinear cooling of semi-infinite rods, is very slow inside their small radius of convergence. Beyond that the corresponding power series are wildly divergent. Implementation of nonlinear sequence transformation allow effortless evaluation of these power series on very large intervals..

Keywords: Nonlinear transformation, Abel Volterra Equations, Mathematica

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Authors: B. A. Parate, C. P. Shetty

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This research article describes the evaluation methodology of an internal ballistics of multi-perforated grain in a closed vessel (CV). The propellant testing in a CV is conducted to characterize the propellants and to ascertain the various internal ballistic parameters. The assessment of an internal ballistics plays a very crucial role for suitability of its use in the selection for a given particular application. The propellant used in defense sectors has to satisfy the user requirements as per laid down specifications. The outputs from CV evaluation of multi-propellant grain are maximum pressure of 226.75 MPa, differentiation of pressure with respect to time of 36.99 MPa/ms, average vivacity of 9.990×10-4/MPa ms, force constant of 933.9 J/g, rise time of 9.85 ms, pressure index of 0.878 including burning coefficient of 0.2919. This paper addresses an internal ballistic of multi-perforated grain, propellant selection, its calculation, and evaluation of various parameters in a CV testing. For the current analysis, the propellant is evaluated in 100 cc CV with propellant mass 20 g. The loading density of propellant is 0.2 g/cc. The method for determination of internal ballistic properties consists of burning of propellant mass under constant volume.

Keywords: Burning rate, closed vessel, force constant, internal ballistic, loading density, maximum pressure, multi-propellant grain, propellant, rise time, vivacity.

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Authors: T. Parra, R. Z. Szasz, C. Duwig, R. Pérez, V. Mendoza, F. Castro

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The POD makes possible to reduce the complete high-dimensional acoustic field to a low-dimensional subspace where different modes are identified and let reconstruct in a simple way a high percentage of the variance of the field.

Rotating modes are instabilities which are commonly observed in swirling flows. Such modes can appear under both cold and reacting conditions but that they have different sources: while the cold flow rotating mode is essentially hydrodynamic and corresponds to the wellknown PVC (precessing vortex core) observed in many swirled unconfined flows, the rotating structure observed for the reacting case inside the combustion chamber might be not hydrodynamically but acoustically controlled. The two transverse acoustic modes of the combustion chamber couple and create a rotating motion of the flame which leads to a self-sustained turning mode which has the features of a classical PVC but a very different source (acoustics and not hydrodynamics).

Keywords: Acoustic field, POD, swirling flames.

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Authors: Victoria Konidari, Yvan Abernot

Abstract:

This paper seeks to explore the actual classroom setting, to examine its role for students- learning, and attitude in the class. It presents a theoretical approach of the classroom as system to be explored and examines the concrete reality of Greek secondary education students, under the light of the above approach. Based on the findings of a quantitative and qualitative research, authors propose a rather ontological approach of the classroom and underline what the key-elements for such approach should be. The paper explores extensively the theoretical dimensions for the change of paradigm required and addresses the new issues to be considered.

Keywords: Group, class, collective subject, field, temporality, ontology.

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Authors: Zuzana Dideková, Beata Mikovičová

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Characterization of radio communication signals aims at automatic recognition of different characteristics of radio signals in order to detect their modulation type, the central frequency, and the level. Our purpose is to apply techniques used in image processing in order to extract pertinent characteristics. To the single analysis, we add several rules for checking the consistency of hypotheses using fuzzy logic. This allows taking into account ambiguity and uncertainty that may remain after the extraction of individual characteristics. The aim is to improve the process of radio communications characterization.

Keywords: fuzzy classification, fuzzy inference system, radio communication signals, telecommunications

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Authors: Puntani Pongsumpun, I-Ming Tang

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The most Malaria cases are occur along Thai-Mynmar border. Mathematical model for the transmission of Plasmodium falciparum and Plasmodium vivax malaria in a mixed population of Thais and migrant Burmese living along the Thai-Myanmar Border is studied. The population is separated into two groups, Thai and Burmese. Each population is divided into susceptible, infected, dormant and recovered subclasses. The loss of immunity by individuals in the infected class causes them to move back into the susceptible class. The person who is infected with Plasmodium vivax and is a member of the dormant class can relapse back into the infected class. A standard dynamical method is used to analyze the behaviors of the model. Two stable equilibrium states, a disease-free state and an epidemic state, are found to be possible in each population. A disease-free equilibrium state in the Thai population occurs when there are no infected Burmese entering the community. When infected Burmese enter the Thai community, an epidemic state can occur. It is found that the disease-free state is stable when the threshold number is less than one. The epidemic state is stable when a second threshold number is greater than one. Numerical simulations are used to confirm the results of our model.

Keywords: Basic reproduction number, Burmese, local stability, Plasmodium Vivax malaria.

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Kyu Park

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Sound absorbing material is used as automotive interior material. Sound absorption coefficient should be predicted to design it. But it is difficult to predict sound absorbing coefficient because it is comprised of several material layers. So, its targets are achieved through many experimental tunings. It causes a lot of cost and time. In this paper, we propose the process to estimate the sound absorption coefficient with multi-layer structure. In order to estimate the coefficient, physical properties of each material are used. These properties also use predicted values by Foam-X software using the sound absorption coefficient data measured by impedance tube. Since there are many physical properties and the measurement equipment is expensive, the values predicted by software are used. Through the measurement of the sound absorption coefficient of each material, its physical properties are calculated inversely. The properties of each material are used to calculate the sound absorption coefficient of the multi-layer material. Since the absorption coefficient of multi-layer can be calculated, optimization design is possible through simulation. Then, we will compare and analyze the calculated sound absorption coefficient with the data measured by scaled reverberation chamber and impedance tubes for a prototype. If this method is used when developing automotive interior materials with multi-layer structure, the development effort can be reduced because it can be optimized by simulation. So, cost and time can be saved.

Keywords: Optimization design, multi-layer nonwoven, sound absorption coefficient, scaled reverberation chamber, impedance tubes.

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Authors: Xiaomin Zhang

Abstract:

In this paper, the class of weakly left C-wrpp semigroups which includes the class of weakly left C-rpp semigroups as a subclass is introduced. To particularly show that the spined product of a left C-wrpp semigroup and a right normal band which is a weakly left C-wrpp semifroup by virtue of left C-full Ehremann cyber groups recently obtained by authors Li-Shum, results obtained by Tang and Du-Shum are extended and strengthened.

Keywords: Left C-semigroup, left C-wrpp semigroup, left quasinormal band, weakly left C-wrpp semigroup

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Authors: Sorin Soviany, Cristina Soviany, Mariana Jurian

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The paper presents a multimodal approach for biometric authentication, based on multiple classifiers. The proposed solution uses a post-classification biometric fusion method in which the biometric data classifiers outputs are combined in order to improve the overall biometric system performance by decreasing the classification error rates. The paper shows also the biometric recognition task improvement by means of a carefully feature selection, as much as not all of the feature vectors components support the accuracy improvement.

Keywords: biometric fusion, multiple classifiers

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Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze

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Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The MP is based on making the product of the speech wavelet transform coefficients (WTC). We have estimated our method on the Keele database. The results show the effectiveness of our method. It indicates that the two features can find word boundaries, and extracted the segments of the clean speech.

Keywords: Speech segmentation, Multi-scale product, Spectral centroid, Zero crossings rate.

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Authors: Sozon H. Papavlasopoulos, Marios S. Poulos, George D. Bokos, Angelos M. Evangelou

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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.

Keywords: Cross-Correlation Methods, Diagnostic Test, Interictal Epileptic, LVQ1 neural network, Auto-Cross-Correlation Methods, chi-square test.

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