Artigos

URI Permanente para esta coleção

https://repositorio.fei.edu.br/handle/FEI/798

Navegar

Agora exibindo 1 - 20 de 740

3D simulation of Triple-Gate MOSFETs
(2010-05-19) CONDE, J.; CERDEIRA, A.; Marcelo Antonio Pavanello; KILCHYTSKA, V.; FLANDRE, D.
In this paper we present a new approach of analyzing 3D structure for Triple-Gate MOSFETs with three different mesh regions, one at the top and two in the sidewalls of the fin, which allows the consideration of different carrier mobility at each region due to the crystalline orientation and technological processing. A procedure for the extraction of the mobility parameters in each region is developed. Validation of the proposed structure was made for a FinFET arrays with fixed channel length and different fin widths, obtaining a very good coincidence between experimental and simulated characteristics. © 2010 IEEE.
3D simulation of triple-gate MOSFETs with different mobility regions
(2011-07-05) CONDE, J.; CERDEIRA, A.; Marcelo Antonio Pavanello; KILCHYTSKA, V.; FLANDRE, D.
In this paper we present a new approach for analyzing 3D structure triple-gate MOSFETs using three different regions, one at the top and two in the sidewalls of the fin, which allows for considering different carrier mobilities in each region due to crystalline orientation and technological processing. A procedure for the extraction of the mobility parameters in each region is developed. Robustness of the proposed structure is validated by experimental data obtained on FinFETs. A very good agreement is obtained between experimental and simulated characteristics. © 2011 Elsevier B.V. All rights reserved.
3D triple-gate simulation considering the crystallographic orientations
(2008-09-04) CONDE, J. E.; CERDEIRA, A.; Marcelo Antonio Pavanello
Current in FinFET's transistors flows along two different crystallographic orientations, since, typically the FIN top region orientation is <100>, while the sidewalls have <110> orientation. In this paper we present how to represent the mesh structure for these devices, in order to simulate in 3-D, considering different mobility values for each orientation. Results of 3-D simulation considering also the effect of the series resistance are shown and compared with experimental results. © The Electrochemical Society.
A charge-based continuous model for submicron graded-channel nMOSFET for analog circuit simulation
(2005) De Souza M.; Pavanello M.A.; Iniguez B.; Flandre D.
In this work a continuous analytical model for analog simulation of submicron asymmetrically doped silicon-on-insulator (SOI) nMOSFET using the graded-channel (GC) architecture, valid from weak to strong inversion regimes, is proposed. Analytical models accounting for mobility degradation due to the vertical field, channel length modulation, drain induced barrier lowering and velocity saturation effects have been included in the model formulation. Also the action of parasitic bipolar transistor intrinsic to the SOI MOSFET has been considered. The proposed model considers the highly doped part of the GC transistor acting as a 'main' transistor, whose drain voltage is modulated by the remaining part of the channel. Experimental results and two-dimensional simulated data were used to test the model, by comparing the drain current and some important characteristics for analog circuit design, such as the transconductance over the drain current ratio and output conductance, achieving a good agreement in both cases. © 2005 Elsevier Ltd. All rights reserved.
A compact model and an extraction method for the FinFET spreading resistance
(2011-09-02) Marcelo Parada; MALHEIRO, C. T.; AGOPIAN, P. G. D.; Renato Giacomini
This work presents a study of the FinFET series resistance focused on the spreading component. A new simple analytical expression is proposed to easily estimate and model this parasitic parameter. The extraction method departs from the drain current versus gate voltage curves of several channel and source/drain lengths. The resistance values extracted from simulated devices are compared to the outputs of the analytic model and a very good agreement is achieved. The proposed model showed accurate estimative for a wider range of devices then previously published models. © The Electrochemical Society.
A continuous authentication system based on user behavior analysis
(2010-02-15) BROSSO, I.; LA NEVE, A.; BRESSAN, G.; RUGGIERO, W. V.
This paper presents a continuous authentication system based on user behavior analysis that makes use of environmental context information, users' behavior analysis and Neuro-Fuzzy Logic. This system must be able to acquire information in context, making them into a computational environment. This information is the basis of user behavior. The System, based on the evidences of the behavior, establishes if it can trust the user or not. According to the user behavior, levels of trust are released, to access the application software. Weights are attributed in the fuzzyfication process, according to the rules that were previously established for the parameters which help to establish the evidences of behavioral trust, in its different degrees. The neuro-fuzzy logic allows that the user behavioral database be continuously updated, interacting with the fuzzyfication mechanism, so as to keep trust levels updated according to the user behavior, in a more accurate and faithful way. © 2010 IEEE.
A Convolutional Neural Network-based Mobile Application to Bedside Neonatal Pain Assessment
(2021-10-18) CARLINI, L. P.; FERREIRA, L. A.; COUTRIN, G. A. S.; VAROTO, V. V.; HEIDERICH, T. M.; BALDA R. C. X.; BARROS, M. C. M.; GUINSBURG R.; Carlos E. Thomaz
More than 500 painful interventions are carried out during the hospitalisation of a newborn baby in a neonatal intensive care unit. Since neonates are not able to verbally communicate pain, some studies have been done to identify the presence and intensity of pain by behavioural analysis, mainly by facial expression. These studies allow a better understanding of this painful experience faced by the neonate. In this context, this work proposes and implements a mobile application for smartphones that uses Artificial Intelligence (AI) techniques to automatically identify the facial expression of pain in neonates, presenting feasibility in real clinical situations. Firstly, a Convolutional Neural Network architecture was adapted and trained with face images captured before and after painful clinical procedures carried out routinely. Then, this computational model was optimised to a mobile environment to make it practical for everyday use. Moreover, we used an explainable AI method to identify facial regions that might be relevant to pain assessment. Our results showed that is possible to classify the facial expression of the pain of neonates with high accuracy. Additionally, our methodology presented novel results highlighting as well sound facial regions that agree with pain scales used by neonatologists and with the visual perception of adults when assessing pain in neonates, whether they are health professionals or not.
A hybrid approach to learn, retrieve and reuse qualitative cases
(2017-11-10) HOMEM, T. P. D.; PERICO, D. H.; SANTOS, P. E.; COSTA, A. H. R.; Reinaldo Bianchi; DE MANTARAS, R. L.
© 2017 IEEE.The application of Artificial Intelligence methods is becoming indispensable in several domains, for instance in credit card fraud detection, voice recognition, autonomous cars and robotics. However, some methods fail in performances or solving some problems, and hybrid approaches can outperform the results when compared to traditional ones. In this paper we present a hybrid approach, named qualitative case-based reasoning and learning (QCBRL), that integrates three well-known AI methods: Qualitative Spatial Reasoning, Case-Based Reasoning and Reinforcement Learning. QCBRL system was designed to allow an agent to learn, retrieve and reuse qualitative cases in the robot soccer domain. We applied our method in the Half-Field Offense and we have obtained promising results.
A low cost retrofitting technique for mechanical presses
(2015-09-28) MORTAIO, L. A.; RIASCOS, L. A. M.
© 2015 IEEE.The mechanical press is a machine which applies forming force on materials, mainly on metals. A die is placed into the press to mold the material during the stamping process. The eccentric mechanical presses with driving crank has a simple operation, but the slide upstroke and down stroke speeds are fixes and determined by the impact reduced speed on the material (the blank). However, these machines can be retrofitted attaching a servo-drive and PID controls to improve productivity. The objective of this work is to present a hybrid drive approach for controlling and improving the press speed and the stroke rate for eccentric presses, but keeping a die impact reduced speed on the metal sheet. The cost for transforming into a hybrid servo-press is around 20% of a direct drive servo-press.
A maximum uncertainty LDA-based approach for limited sample size problems — with application to face recognition
(2006-01-01) Carlos E. Thomaz; Kitani E.C.; Gillies D.F.
© 2007, The Brazilian Computer Society.A critical issue of applying Linear Discriminant Analysis (LDA) is both the singularity and instability of the within-class scatter matrix. In practice, particularly in image recognition applications such as face recognition, there are often a large number of pixels or pre-processed features available, but the total number of training patterns is limited and commonly less than the dimension of the feature space. In this study, a new LDA-based method is proposed. It is based on a straightforward stabilisation approach for the within-class scatter matrix. In order to evaluate its effectiveness, experiments on face recognition using the well-known ORL and FERET face databases were carried out and compared with other LDA-based methods. The classification results indicate that our method improves the LDA classification performance when the within-class scatter matrix is not only singular but also poorly estimated, with or without a Principal Component Analysis intermediate step and using less linear discriminant features. Since statistical discrimination methods are suitable not only for classification but also for characterisation of differences between groups of patterns, further experiments were carried out in order to extend the new LDA-based method to visually analyse the most discriminating hyper-plane separating two populations. The additional results based on frontal face images indicate that the new LDA-based mapping provides an intuitive interpretation of the two-group classification tasks performed, highlighting the group differences captured by the multivariate statistical approach proposed.
A method for the online construction of the set of states of a Markov decision process using answer set programming
(2018-06-28) FERREIRA, L. A.; Reinaldo Bianchi; SANTOS, P. E.; DE MANTARAS, R. L.
© 2018, Springer International Publishing AG, part of Springer Nature.Non-stationary domains, that change in unpredicted ways, are a challenge for agents searching for optimal policies in sequential decision-making problems. This paper presents a combination of Markov Decision Processes (MDP) with Answer Set Programming (ASP), named Online ASP for MDP (oASP(MDP)), which is a method capable of constructing the set of domain states while the agent interacts with a changing environment. oASP(MDP) updates previously obtained policies, learnt by means of Reinforcement Learning (RL), using rules that represent the domain changes observed by the agent. These rules represent a set of domain constraints that are processed as ASP programs reducing the search space. Results show that oASP(MDP) is capable of finding solutions for problems in non-stationary domains without interfering with the action-value function approximation process.
A multi-linear discriminant analysis of 2D frontal face images
(2009-10-11) Carlos E. Thomaz; DO AMARAL, V.; GIRALDI, G. A.; KITANI, E. C.; SATO, J. R.; GILLES, D. F.
We have designed and implemented a multi-linear discriminant method of constructing and quantifying statistically significant changes on human identity photographs. The method is based on a general multivariate two-stage linear framework that addresses the small sample size problem in high-dimensional spaces. Starting with a 2D face data set of well framed images, we determine a most characteristic direction of change by organizing the data according to the features of interest. Our goal here is to use all the facial image features simultaneously rather than separate models for texture and shape information. Our experiments show that the method does produce plausible unseen views for gender, facial expression and ageing changes. We believe that this method could be widely applied for normalization in face recognition and in identifying subjects after a lapse of time. © 2009 IEEE.
A Multivariate Correlation Assessment of Chess Proficiency Using Brain Signals
(2019-09-05) SILVA, L.; Carlos E. Thomaz THOMAZ, C. E.
© 2019 IEEE.Chess game has attracted the interest of many academic works with several experiments carried out to address the differences in brain activation on proficients and non-proficients chess players. However, none of these works takes into account explicitly the cognitive patterns of the chess players to rank and classify them. In our work, we aim to present a cognitive model, using EEG and multivariate statistical methods, to assess chess volunteers and compare their performance to the traditional metric based on accuracy and response time. In total, 32 volunteers have participated in this study based on visual stimuli computationally generated. Our main results show that it is important not only to top rank the volunteers with high accuracy and low response time, but also understand how the main brain processes occur to a chess expert to achieve such top performance.
A multivariate statistical analysis of the developing human brain in preterm infants
(2007) Thomaz C.E.; Boardman J.P.; Counsell S.; Hill D.L.G.; Hajnal J.V.; Edwards A.D.; Rutherford M.A.; Gillies D.F.; Rueckert D.
Preterm delivery accounts for 5% of all deliveries and its consequences contribute to significant individual, medical, and social problems. The neuroanatomical substrates of these disorders are not known, but are essential for understanding mechanisms of causation, and developing strategies for intervention. In the recent years, multivariate pattern recognition methods that analyse all voxels simultaneously have been proposed to characterise the neuroanatomical differences between a reference group of magnetic resonance (MR) images and the population under investigation. Most of these techniques have overcome the difficulty of dealing with the inherent high dimensionality of 3D MR brain image data by using pre-processed segmented images or a small number of specific features. However, an intuitive way of mapping the classification results back into the original image domain for further interpretation remains challenging. In this paper, we propose the idea of using Principal Components Analysis (PCA) plus the maximum uncertainty Linear Discriminant Analysis (MLDA) approach to classify and analyse MR brain images that have been aligned with either affine or non-rigid registration techniques. This approach avoids the computation costs intrinsic to commonly used covariance-based optimisation processes for solving small sample size problems, resulting in a simple and efficient implementation for the maximisation and interpretation of the Fisher's classification results. In order to demonstrate the effectiveness of the approach, we have used a neonatal MR brain data set that contains images of 93 preterm infants at term equivalent age and 20 term controls. Our results indicate that the two-stage linear framework makes clear the statistical differences between the control and preterm samples, showing a classification accuracy of 95.0% and 97.8% for the controls and preterms samples, respectively, using the leave-one-out method. Moreover, it provides a simple and intuitive method of visually analysing the differences between preterm infants at term equivalent age and the control group, such as differences in cerebrospinal fluid spaces, structure of the corpus callosum, and subtle differences in myelination. © 2006 Elsevier B.V. All rights reserved.
A new analytic model for double gate FinFETs parasitic resistance
(2012-09-02) PEREIRA, A. S. N.; Renato Giacomini
A new analytic model for Parasitic Resistance of Double Gate FinFETs is proposed in this work. The model was developed considering the current distribution observed in three-dimensional simulations. The contact resistance was modeled using a variable impedance transmission line model, to approximate source and drain geometries to the real shapes of these regions. The model has a closed expression, without adjustment parameters and is very accurate when compared to simulation results and published experimental data. © The Electrochemical Society.
A New Method for Series Resistance Extraction of Nanometer MOSFETs
(2017-07-05) TREVISOLI, R.; Rodrido Doria; Michelly De Souza; BARRAUD, S.; VINET, M.; CASSE, M.; REIMBOLD, G.; FAYNOT, O.; GHIBAUDO, G.; Marcelo Antonio Pavanello
This paper presents a new method for the series resistance extraction in ultimate MOSFETs using a single drain current versus gate voltage characteristic curve. The method is based on the Y-function curve, such that the series resistance is obtained through the curve of the total resistance as a function of the inverse of the Y-function. It includes both first-and second-order mobility degradation factors. To validate the proposed method, numerical simulations have been performed for devices of different characteristics. Besides, the method applicability has been demonstrated for experimental silicon nanowires and FinFETs. Apart from that, devices with different channel lengths can be used to estimate the mobility degradation factor influence.
A new method of selecting safe neighbors for the Riemannian Manifold Learning algorithm
(2021-01-05) Carlini L. P.; Miranda Junior G. F.; Giraldi G. A.; Carlos E. Thomaz
© 2003-2012 IEEE.Manifold learning (ML) comprehends a set of nonlinear techniques for mining and representing high-dimensional data. In this work, we approach the well-known and successful ML technique called Riemannian Manifold Learning (RML). Firstly, we present a geometric interpretation of the main steps of selecting visible and safe neighborhoods to reconstruct geometry and topology in the original RML algorithm. Then, we describe and implement a new method of selecting safe neighbors for this algorithm. Our experimental results on synthetic and real data sets, using open source tools and a public face image database, have showed that the new method proposed shows similar results to the original one and reconstructions that favour local rather than holistic similarities described by the data. Additionally, since the new method proposed requires the specification of only one input parameter, its implementation is simpler and more intuitive than the original one.
A new ranking method for principal components analysis and its application to face image analysis
(2010) Thomaz C.E.; Giraldi G.A.
In this work, we investigate a new ranking method for principal component analysis (PCA). Instead of sorting the principal components in decreasing order of the corresponding eigenvalues, we propose the idea of using the discriminant weights given by separating hyperplanes to select among the principal components the most discriminant ones. The method is not restricted to any particular probability density function of the sample groups because it can be based on either a parametric or non-parametric separating hyperplane approach. In addition, the number of meaningful discriminant directions is not limited to the number of groups, providing additional information to understand group differences extracted from high-dimensional problems. To evaluate the discriminant principal components, separation tasks have been performed using face images and three different databases. Our experimental results have shown that the principal components selected by the separating hyperplanes allow robust reconstruction and interpretation of the data, as well as higher recognition rates using less linear features in situations where the differences between the sample groups are subtle and consequently most difficult for the standard and state-of-the-art PCA selection methods. © 2009 Elsevier B.V. All rights reserved.
A new series resistance extraction method for junctionless nanowire transistors
(2016-11-02) TREVISOLI, R.; Rodrido Doria; Michelly De Souza; BARRAUD, S.; VINET, M.; Marcelo Antonio Pavanello
Series resistance can severely affect the electrical behavior of such Junctionless Nanowire Transistors. The aim of this work is to propose a new method for the extraction of the series resistance in Junctionless Nanowire Transistors. The method is validated by means of tridimensional numerical simulations and experimental results, using transistors with different widths and doping concentrations.
A novel asynchronous interface with pausible clock for partitioned synchronous modules
(2015-09-01) OLIVEIRA, D. L.; CURTINHAS, T.; FARIA, L. A.; ROMANO, L.
© 2015 IEEE.Contemporary digital systems must necessarily be based on the 'System-on-Chip - SoC' concept. An interesting style for SoC design is GALS (Globally Asynchronous, Locally Synchronous) paradigm. Currently, the major drawback in the design of a GALS system shows to be the asynchronous interface (asynchronous wrapper - AW), especially when the GALS system is applied to a multi-point topology. The AW interfaces found in literature are always based on controller ports. They are responsible for data communication between locally synchronous modules, where to each point of data communication there is an input or output port. The increasing number of port leads to complex AWs and to a high increase in area. This paper proposes a new asynchronous GALS interface focused on multi-point GALS. For a case study considering a multi-point data communication system, the proposed interface achieved an average reduction in area (products + literals) of 85% and 74%, when compared to two different AWs found in literature.

Navegar

Navegando Artigos por Título

Resultados por página

Opções de Ordenação