Search results for: lattice model

Authors: Adji Achmad Rinaldo Fernandes

Abstract:

SEM analysis is a complex multivariate analysis because it involves a number of exogenous and endogenous variables that are interconnected to form a model. The measurement model is divided into two, namely, the reflective model (reflecting) and the formative model (forming). Before carrying out further tests on SEM, there are assumptions that must be met, namely the linearity assumption, to determine the form of the relationship. There are three modeling approaches to path analysis, including parametric, nonparametric and semiparametric approaches. The aim of this research is to develop semiparametric SEM and obtain the best model. The data used in the research is secondary data as the basis for the process of obtaining simulation data. Simulation data was generated with various sample sizes of 100, 300, and 500. In the semiparametric SEM analysis, the form of the relationship studied was determined, namely linear and quadratic and determined one and two knot points with various levels of error variance (EV=0.5; 1; 5). There are three levels of closeness of relationship for the analysis process in the measurement model consisting of low (0.1-0.3), medium (0.4-0.6) and high (0.7-0.9) levels of closeness. The best model lies in the form of the relationship X1Y1 linear, and. In the measurement model, a characteristic of the reflective model is obtained, namely that the higher the closeness of the relationship, the better the model obtained. The originality of this research is the development of semiparametric SEM, which has not been widely studied by researchers.

Keywords: semiparametric SEM, measurement model, structural model, reflective model, formative model

Procedia PDF Downloads 19

Authors: María Magdalena Méndez-González, Miguel García Rocha, Carlos Manuel Yermo De la Cruz

Abstract:

Calcium phosphate (Ca5(PO4)3(X)) is widely used in orthopedic applications and is widely used as powder and granules. However, their presence in bone is in the form of nanometric needles 60 nm in length with a non-stoichiometric phase of apatite contains CO3-2, Na+, OH-, F-, and other ions in a matrix of collagen fibers. The crystal size, morphology control and interaction with cells are essential for the development of nanotechnology. The structural results of calcium phosphate, synthesized by chemical precipitation with crystal size of 22.85 nm are presented in this paper. The calcium phosphate powders were analyzed by X-ray diffraction, energy dispersive spectroscopy (EDS), infrared spectroscopy and FT-IR transmission electron microscopy. Network parameters, atomic positions, the indexing of the planes and the calculation of FWHM (full width at half maximum) were obtained. The crystal size was also calculated using the Scherer equation d (hkl) = cλ/βcosѲ. Where c is a constant related to the shape of the crystal, the wavelength of the radiation used for a copper anode is 1.54060Å, Ѳ is the Bragg diffraction angle, and β is the width average peak height of greater intensity. Diffraction pattern corresponding to the calcium phosphate called hydroxyapatite phase of a hexagonal crystal system was obtained. It belongs to the space group P63m with lattice parameters a = 9.4394 Å and c = 6.8861 Å. The most intense peak is obtained 2Ѳ = 31.55 (FWHM = 0.4798), with a preferred orientation in 121. The intensity difference between the experimental data and the calculated values is attributable to the temperature at which the sintering was performed. The intensity of the highest peak is at angle 2Ѳ = 32.11. The structure of calcium phosphate obtained was a hexagonal configuration. The intensity changes in the peaks of the diffraction pattern, in the lattice parameters at the corners, indicating the possible presence of a dopant. That each calcium atom is surrounded by a tetrahedron of oxygen and hydrogen was observed by infrared spectra. The unit cell pattern corresponds to hydroxyapatite and transmission electron microscopic crystal morphology corresponding to the hexagonal phase with a preferential growth along the c-plane was obtained.

Keywords: structure, nanoparticles, calcium phosphate, metallurgical and materials engineering

Procedia PDF Downloads 490

Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

Abstract:

In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

Procedia PDF Downloads 241

Authors: Alan Wan

Abstract:

In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

Procedia PDF Downloads 353

Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

Abstract:

We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

Procedia PDF Downloads 551

Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

Abstract:

The e-government emerging concept transforms the way in which the citizens are dealing with their governments. Thus, the citizens can execute the intended services online anytime and anywhere. This results in great benefits for both the governments (reduces the number of officers) and the citizens (more flexibility and time saving). Therefore, building a maturity model to assess the e-government portals becomes desired to help in the improvement process of such portals. This paper aims at proposing an e-government maturity model based on the measurement of the best practices’ presence. The main benefit of such maturity model is to provide a way to rank an e-government portal based on the used best practices, and also giving a set of recommendations to go to the higher stage in the maturity model.

Keywords: best practices, e-government portal, maturity model, quality model

Procedia PDF Downloads 319

Authors: Hamza Rekab Djabri, Salah Daoud

Abstract:

The present paper deals with the computational of structural and electronic properties of ThC and ThN compounds using density functional theory within generalized-gradient (GGA) apraximation and local density approximation (LDA). We employ the full potential linear muffin-tin orbitals (FP-LMTO) as implemented in the Lmtart code. We have used to examine structure parameter in eight different structures such as in NaCl (B1), CsCl (B2), ZB (B3), NiAs (B8), PbO (B10), Wurtzite (B4) , HCP (A3) βSn (A5) structures . The equilibrium lattice parameter, bulk modulus, and its pressure derivative were presented for all calculated phases. The calculated ground state properties are in good agreement with available experimental and theoretical results.

Keywords: DFT, GGA, LDA, properties structurales, ThC, ThN

Procedia PDF Downloads 82

Authors: I. C. Tolias, A. G. Venetsanos, N. Markatos

Abstract:

In the present work, CFD simulations of a large scale open deflagration experiment are performed. Stoichiometric hydrogen-air mixture occupies a 20 m hemisphere. Two combustion models are compared and are evaluated against the experiment. The Eddy Dissipation Model and a Multi-physics combustion model which is based on Yakhot’s equation for the turbulent flame speed. The values of models’ critical parameters are investigated. The effect of the turbulence model is also examined. k-ε model and LES approach were tested.

Keywords: CFD, deflagration, hydrogen, combustion model

Procedia PDF Downloads 481

Authors: J. Rhodes, V. Cheng, P. Lok

Abstract:

The aim of this study is to develop a parsimonious model that explains the effect of different stimulus on a tourist’s intention to visit a new destination. The model consists of destination trust and interest as the mediating variables. The model was tested using two different types of stimulus; both studies empirically supported the proposed model. Furthermore, the first study revealed that advertising has a stronger effect than positive online reviews. The second study found that the peripheral route of the elaboration likelihood model has a stronger influence power than the central route in this context.

Keywords: advertising, electronic word-of-mouth, elaboration likelihood model, intention to visit, trust

Procedia PDF Downloads 442

Authors: Ahmad Sarfaraz, Raiyad Herwies

Abstract:

In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

Procedia PDF Downloads 364

Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

Abstract:

In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

Procedia PDF Downloads 231

Authors: Ádám Vass, István Bakos, Irina Borbáth, Zoltán Pászti, István Sajó, András Tompos

Abstract:

Important requirements for the anode side electrocatalysts of polymer electrolyte membrane (PEM) fuel cells are CO-tolerance, stability and corrosion resistance. Carbon is still the most common material for electrocatalyst supports due to its low cost, high electrical conductivity and high surface area, which can ensure good dispersion of the Pt. However, carbon becomes degraded at higher potentials and it causes problem during application. Therefore it is important to explore alternative materials with improved stability. Molybdenum-oxide can improve the CO-tolerance of the Pt/C catalysts, but it is prone to leach in acidic electrolyte. The Mo was stabilized by isovalent substitution of molybdenum into the rutile phase titanium-dioxide lattice, achieved by a modified multistep sol-gel synthesis method optimized for preparation of Ti0.7Mo.3O2-C composite. High degree of Mo incorporation into the rutile lattice was developed. The conductivity and corrosion resistance across the anticipated potential/pH window was ensured by mixed oxide – activated carbon composite. Platinum loading was carried out using NaBH4 and ethylene glycol; platinum content was 40 wt%. The electrocatalyst was characterized by both material investigating methods (i.e. XRD, TEM, EDS, XPS techniques) and electrochemical methods (cyclic-voltammetry, COads stripping voltammetry, hydrogen oxidation reaction on rotating disc electrode). The electrochemical activity of the sample was compared to commercial 40 wt% Pt/C (Quintech) and PtRu/C (Quintech, Pt= 20 wt%, Ru= 10 wt%) references. Enhanced CO tolerance of the electrocatalyst prepared using the Ti0.7Mo.3O2-C composite material was evidenced by the appearance of a CO-oxidation related 'pre-peak' and by the pronounced shift of the maximum of the main CO oxidation peak towards less positive potential compared to Pt/C. Fuel cell polarization measurements were also carried out using Bio-Logic and Paxitech FCT-150S test device. All details on the design, preparation, characterization and testing by both electrochemical measurements and fuel cell test device of electrocatalyst supported on Ti0.7Mo.3O2-C composite material will be presented and discussed.

Keywords: anode electrocatalyst, composite material, CO-tolerance, TiMoOx

Procedia PDF Downloads 283

Authors: Coskun Serefoglu

Abstract:

The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

Procedia PDF Downloads 136

Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

Abstract:

The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

Procedia PDF Downloads 505

Authors: Michael Shandalov, Tzvi Templeman, Michael Schmidt, Itzhak Kelson, Eyal Yahel

Abstract:

We present a new method to produce a model system for the study of radiation damage in non-radioactive materials. The method is based on homogeneously incorporating 228Th ions in PbS thin films using a small volume chemical bath deposition (CBD) technique. The common way to alloy metals with radioactive elements is by melting pure elements, which requires considerable amounts of radioactive material with its safety consequences such as high sample activity. Controlled doping of the thin films with (very) small amounts (100-200ppm) of radioactive elements such as thorium is expected to provide a unique path for studying radiation damage in materials due to decay processes without the need of sealed enclosure. As a first stage, we developed CBD process for controlled doping of PbS thin films (~100 nm thick) with the stable isotope (t1/2~106 years), 232Th. Next, we developed CBD process for controlled doping of PbS thin films with active 228Th isotope. This was achieved by altering deposition parameters such as temperature, pH, reagent concentrations and time. The 228Th-doped films were characterized using X-ray diffraction, which indicated a single phase material. Film morphology and thickness were determined using scanning electron microscopy (SEM). Energy dispersive spectroscopy (EDS) mapping in the analytical transmission electron microscope (A-TEM), X-ray photoelectron spectroscopy (XPS) depth profiles and autoradiography indicated that the Th ions were homogeneously distributed throughout the films, suggesting Pb substitution by Th ions in the crystal lattice. The properties of the PbS (228Th) film activity were investigated by using alpha-spectroscopy and gamma spectroscopy. The resulting films are applicable for isochronal annealing of resistivity measurements and currently under investigation. This work shows promise as a model system for the analysis of dilute defect systems in semiconductor thin films.

Keywords: thin films, doping, radiation damage, chemical bath deposition

Procedia PDF Downloads 378

Authors: Okyu Kwon, Dongho Kang, Byungsik Kim, Seungkwon Jung

Abstract:

We propose a technique to measure the impact of loss of traffic function in a particular area to surrounding areas. The proposed method is applied to the city of Seoul, which is the capital of South Korea, with a population of about ten million. Based on the actual road network in Seoul, we construct an abstract road network between 1kmx1km grid cells. The link weight of the abstract road network is re-adjusted considering traffic volume measured at several survey points. On the modified abstract road network, we evaluate the traffic vulnerability by calculating a network measure of betweenness centrality (BC) for every single grid cells. This study analyzes traffic impacts caused by road dysfunction due to heavy rainfall in urban areas. We could see the change of the BC value in all other grid cells by calculating the BC value once again when the specific grid cell lost its traffic function, that is, when the node disappeared on the grid-based road network. The results show that it is appropriate to use the sum of the BC variation of other cells as the influence index of each lattice cell on traffic. This research was supported by a grant (2017-MOIS31-004) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety (MOIS).

Keywords: vulnerability, road network, beweenness centrality, heavy rainfall, road impact

Procedia PDF Downloads 80

Authors: Min Shi

Abstract:

State of the art research with Artificial Neural Networks for the downscaling of General Circulation Models (GCMs) mainly uses back-propagation algorithm as a training approach. This paper introduces another training approach of ANNs, Evolutionary Algorithm. The combined algorithm names neuroevolutionary (NE) algorithm. We investigate and evaluate the use of the NE algorithms in statistical downscaling by generating temperature estimates at interior points given information from a lattice of surrounding locations. The results of our experiments indicate that NE algorithms can be efficient alternative downscaling methods for daily temperatures.

Keywords: temperature, downscaling, artificial neural networks, evolutionary algorithms

Procedia PDF Downloads 336

Authors: D. Ravinder, K. S. Nagaraju

Abstract:

Ni–Al ferrite with composition of NiAlxFe2-xO4 (x=0.2, 0.4 0.6, and 0.8, ) were prepared by citrate gel method. The dielectric properties for all the samples were investigated at room temperature as a function of frequency. The dielectric constant shows dispersion in the lower frequency region and remains almost constant at higher frequencies. The frequency dependence of dielectric loss tangent (tanδ) is found to be abnormal, giving a peak at certain frequency for mixed Ni-Al ferrites. A qualitative explanation is given for the composition and frequency dependence of the dielectric loss tangent.

Keywords: ferrites, citrate method, lattice parameter, dielectric constant

Procedia PDF Downloads 285

Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

Abstract:

Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

Procedia PDF Downloads 623

Authors: H. Namazi, H. T. N. Kuan

Abstract:

It is known that in humans, the adaptation to a given odor occurs within a quite short span of time (typically one minute) after the odor is presented to the brain. Different models of human olfaction have been developed by scientists but none of these models consider the diffusion phenomenon in olfaction. A novel microscopic model of the human olfaction is presented in this paper. We develop this model by incorporating the transient diffusivity. In fact, the mathematical model is written based on diffusion of the odorant within the mucus layer. By the use of the model developed in this paper, it becomes possible to provide quantification of the objective strength of odor.

Keywords: diffusion, microscopic model, mucus layer, olfaction

Procedia PDF Downloads 491

Authors: Yanshuang Zhang, Byungho Jeong

Abstract:

There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

Procedia PDF Downloads 638

Authors: Zainab Magaji Musa, Nordin M. A. Rahman, Julaily Aida Jusoh

Abstract:

The web services applications for digital reference service (WSDRS) of LIS model is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient way of satisfying users’ needs in the reference section of libraries. The formal WSDRS model consists of the Z specifications of all the informal specifications of the model. This paper discusses the formal validation of the Z specifications of WSDRS model. The authors formally verify and thus validate the properties of the model using Z/EVES theorem prover.

Keywords: validation, verification, formal, theorem prover

Procedia PDF Downloads 496

Authors: M. Benhamida, Kh. Bouamama, P. Djemia

Abstract:

We investigate by first-principles pseudo-potential calculations the composition dependence of lattice parameter, hardness and elastic properties of ternary disordered solid solutions Ti(1-x)Ta(x)N (1>=x>=0) with B1-rocksalt structure. Calculations use the coherent potential approximation with the exact muffin-tin orbitals (EMTO) and hardness formula for multicomponent covalent solid solution proposed. Bulk modulus B shows a nearly linear behaviour whereas not C44 and C’=(C11-C12)/2 that are not monotonous. Influences of vacancies on hardness of off-stoichiometric transition-metal nitrides TiN(1−x) and TaN(1−x) are also considered.

Keywords: transition metal nitride materials, elastic constants, hardness, EMTO

Procedia PDF Downloads 412

Authors: Matthew C. Best

Abstract:

Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

Procedia PDF Downloads 577

Authors: B. Bahloul, K. Babesse, A. Dkhira, Y. Bahloul, L. Amirouche

Abstract:

Structural and electronic properties of the rock-salt BaxSr1−xS are calculated using the first-principles calculations based on the density functional theory (DFT) within the generalized gradient approximation (GGA), the local density approximation (LDA) and the virtual-crystal approximation (VCA). The calculated lattice parameters at equilibrium volume for x=0 and x=1 are in good agreement with the literature data. The BaxSr1−xS alloys are found to be an indirect band gap semiconductor. Moreoever, for the composition (x) ranging between [0-1], we think that our results are well discussed and well predicted.

Keywords: semiconductor, Ab initio calculations, rocksalt, band structure, BaxSr1−xS

Procedia PDF Downloads 382

Authors: Tejush Badal, Sanaa Alwidian

Abstract:

Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

Procedia PDF Downloads 56

Authors: D. Thawinkarn, S. Wongbutlee

Abstract:

The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

Procedia PDF Downloads 401

Authors: Ashna Babu, Deepshikha Jaiswal Nagar

Abstract:

Cuprate high-temperature superconductors (HTSCs) have been immensely studied during the past few decades because of their structure which is described as a superlattice of superconducting CuO₂ layers. In particular, YBa₂Cu₃O₆₊δ (YBCO), with its critical temperature of 93 K, has received the most attention due to its well-defined metal stoichiometry and variable oxygen content that determines the carrier doping level. Substitution of metal ions at the Cu site is known to increase the critical current density without destroying superconductivity in YBCO. The construction of vortex phase diagrams is very important for such doped YBCO materials both from a fundamental perspective as well as from a technological perspective. By measuring field-dependent magnetization on annealed single crystals of Al-doped YBCO, YBa₂Cu₃₋ₓAlₓO₆₊δ (Al-YBCO), we were able to observe a second magnetization peak anomaly (SMP) in a very large part of the phase diagram. We were also able to observe the SMP anomaly in temperature-dependent magnetization measurements, the first observation to our knowledge. Critical current densities were calculated using Bean’s critical state model, flux jumps associated with symmetry reorientation of vortex lattice were studied, the oxygen cluster distribution was also analysed, and by incorporating all observations, we made a vortex phase diagram for oxygenated Al-YBCO single crystal.

Keywords: oxygen deficient clusters, second magnetization peak anomaly, flux jumps, vortex phase diagram

Procedia PDF Downloads 51

Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

Abstract:

Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

Procedia PDF Downloads 325

Authors: A. Lakrim, D. Tahri

Abstract:

This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS diode, electro-thermal, SPICE model, behavioral macro-model

Procedia PDF Downloads 395