Journal articles: 'GMM-EM'

1

Gu, Ming Liang, and Biao Zhang. "Chinese Dialect Identification Using SC-GMM." Advanced Materials Research 433-440 (January 2012): 3292–96. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3292.

Full text

Abstract:

Gaussian mixture model (GMM) is a sort of effective identification method in Chinese dialects identification, estimating GMM parameters is always an important step in building a state-of-the-art speech processing system. One of the most widely used approaches is maximum- likelihood estimation, where parameters of class-specific distributions are estimated using Expectation Maximization algorithm(EM). Initial parameters have great influence on the convergence of EM algorithm, so how to initialize GMM parameters is a key problem. In this paper, we apply spectral clustering(SC) to initialize GMM parameters. Experimental results prove that using spectral clustering algorithm to initialize GMM parameters is superior to traditional K-Means method and identification system has a higher recognition rate.

APA, Harvard, Vancouver, ISO, and other styles

2

Li, Yupeng, Jianhua Zhang, Ruisi He, Lei Tian, and Hewen Wei. "Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath Clustering." International Journal of Antennas and Propagation 2019 (December 27, 2019): 1–10. http://dx.doi.org/10.1155/2019/4639612.

Full text

Abstract:

In this paper, the Gaussian mixture model (GMM) is introduced to the channel multipath clustering. In the GMM field, the expectation-maximization (EM) algorithm is usually utilized to estimate the model parameters. However, the EM widely converges into local optimization. To address this issue, a hybrid differential evolution (DE) and EM (DE-EM) algorithms are proposed in this paper. To be specific, the DE is employed to initialize the GMM parameters. Then, the parameters are estimated with the EM algorithm. Thanks to the global searching ability of DE, the proposed hybrid DE-EM algorithm is more likely to obtain the global optimization. Simulations demonstrate that our proposed DE-EM clustering algorithm can significantly improve the clustering performance.

APA, Harvard, Vancouver, ISO, and other styles

3

Xu, Yanping, Tingcong Ye, Xin Wang, Yuping Lai, Jian Qiu, Lingjun Zhang, and Xia Zhang. "GMM with parameters initialization based on SVD for network threat detection." Journal of Intelligent & Fuzzy Systems 40, no. 1 (January 4, 2021): 477–90. http://dx.doi.org/10.3233/jifs-200066.

Full text

Abstract:

In the field of security, the data labels are unknown or the labels are too expensive to label, so that clustering methods are used to detect the threat behavior contained in the big data. The most widely used probabilistic clustering model is Gaussian Mixture Models(GMM), which is flexible and powerful to apply prior knowledge for modelling the uncertainty of the data. Therefore, in this paper, we use GMM to build the threat behavior detection model. Commonly, Expectation Maximization (EM) and Variational Inference (VI) are used to estimate the optimal parameters of GMM. However, both EM and VI are quite sensitive to the initial values of the parameters. Therefore, we propose to use Singular Value Decomposition (SVD) to initialize the parameters. Firstly, SVD is used to factorize the data set matrix to get the singular value matrix and singular matrices. Then we calculate the number of the components of GMM by the first two singular values in the singular value matrix and the dimension of the data. Next, other parameters of GMM, such as the mixing coefficients, the mean and the covariance, are calculated based on the number of the components. After that, the initialization values of the parameters are input into EM and VI to estimate the optimal parameters of GMM. The experiment results indicate that our proposed method performs well on the parameters initialization of GMM clustering using EM and VI for estimating parameters.

APA, Harvard, Vancouver, ISO, and other styles

4

Tilley, Roger, Hamid Sadjadpour, and Farid Dowla. "GPR Imaging for Deeply Buried Objects: A Comparative Study Based on Compositing of Scanning Frequencies and a Chirp Excitation Function." Geosciences 9, no. 3 (March 18, 2019): 132. http://dx.doi.org/10.3390/geosciences9030132.

Full text

Abstract:

Compositing of ground penetrating radar (GPR) scans of differing frequencies have been found to produce cleaner images at depth using the Gaussian mixture model (GMM) feature of the expectation-maximization (EM) algorithm. GPR scans at various heights (“Stand Off”), as well as ground-based scans, have been studied. In this paper, we compare the GPR response from a chirp excitation function-based radar with the response from the EM GMM algorithm compositing process, using the same mix of frequencies. A chirp excitation pulse was found to be effective in delineating the defined buried object, but the resulting image is less sharp than the GMM EM method.

APA, Harvard, Vancouver, ISO, and other styles

5

Pudurkar, Rahul, Shruti Patil, Gazala Ansari, and Shaikh Phiroj. "Biometric Voice Recognition system using MFCC and GMM with EM." International Journal of Computer Applications 184, no. 26 (August 20, 2022): 5–10. http://dx.doi.org/10.5120/ijca2022922315.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Ma, Bo, Mingyang Wu, Zhilu Wu, Zhendong Yin, and Tao Shen. "GMM-MUD: An Effective Multiuser Detection Algorithm for DS-UWB-Based Space Formation Flying Systems." Mathematical Problems in Engineering 2019 (November 20, 2019): 1–10. http://dx.doi.org/10.1155/2019/4350794.

Full text

Abstract:

In this paper, an effective multiuser detection (MUD) is proposed for direct sequence ultrawideband- (DS-UWB-) based space formation flying systems. The proposed method called GMM-MUD is based on Gaussian mixture models (GMMs) to suppress multiple access interference. The GMM describes probability distributions of the hypothesis testing problem which is used for bit classification. To reveal the difference between correct bits and error bits, the preprocessing operation applies a mapping function based on optimal multiuser detection. The parameters of GMM are estimated by using expectation-maximization (EM) algorithm. EM algorithm employs iterative operation to simplify the complexity of maximum likelihood estimation method and considers the mapping values of received bits as the observations. Simulation results demonstrate that the proposed GMM-MUD algorithm achieves good performances in terms of bit error rate performance, user capacity, and near-far resistance. Moreover, the computational complexity is low enough for space formation flying applications.

APA, Harvard, Vancouver, ISO, and other styles

7

Hashimoto, Juliano Hideo, Claudete Regina Alcalde, Maximiliane Alavarse Zambom, Karina Toledo da Silva, Francisco de Assis Fonseca de Macedo, Elias Nunes Martins, Carlos Eduardo Crispim de Oliveira Ramos, and Gabriella de Oliveira Passianoto. "Desempenho e digestibilidade aparente em cabritos Boer x Saanen em confinamento recebendo rações com casca do grão de soja em substituição ao milho." Revista Brasileira de Zootecnia 36, no. 1 (February 2007): 174–82. http://dx.doi.org/10.1590/s1516-35982007000100021.

Full text

Abstract:

Foram utilizados 27 cabritos Boer x Saanen (15 machos e 12 fêmeas, 25,75 ± 3,80 kg PV) distribuídos em delineamento inteiramente casualizado para avaliar os os efeitos da substituição de casca do grão de soja (CGS) por grão de milho moído (GMM) sobre o desempenho e a digestibilidade aparente dos nutrientes da dieta. As rações foram compostas de feno de grama-estrela (Cynodon spp.), farelo de soja, milho, casca do grão de soja e minerais, sendo os tratamentos constituídos de 0 (GMM), 50 (CGS50) e 100% (CGS100) de substituição do milho pela casca do grão de soja. O período experimental foi de 42 dias e a digestibilidade dos nutrientes foi determinada utilizando-se a FDN indigestível como indicador. Os tratamentos não diferiram quanto às ingestões de MS, MO e PB, ao ganho de peso médio diário e à conversão alimentar. A utilização da CGS resultou em diminuição dos coeficientes de digestibilidade da MS, MO e PB e aumento dos coeficientes de digestibilidade da FDN e do amido. A digestibilidade in vitro da MS foi maior no tratamento GMM, mas a da parede celular não diferiu entre os tratamentos. A casca do grão de soja apresentou 23,87; 0,19; 55,89 e 20,05% das frações A, B1, B2 e C dos carboidratos e 35,22; 8,19; 31,61; 15,46 e 9,52% das frações A, B1, B2, B3 e C da proteína. A casca do grão de soja, quando utilizada em até 100% de substituição ao milho nas rações, não altera o desempenho de cabritos em crescimento, mas diminui a digestibilidade da MS, MO e da proteína e aumenta a da FDN.

APA, Harvard, Vancouver, ISO, and other styles

8

Sun, Qi, Liwen Jiang, and Haitao Xu. "Expectation-Maximization Algorithm of Gaussian Mixture Model for Vehicle-Commodity Matching in Logistics Supply Chain." Complexity 2021 (January 13, 2021): 1–11. http://dx.doi.org/10.1155/2021/9305890.

Full text

Abstract:

A vehicle-commodity matching problem (VCMP) is presented for service providers to reduce the cost of the logistics system. The vehicle classification model is built as a Gaussian mixture model (GMM), and the expectation-maximization (EM) algorithm is designed to solve the parameter estimation of GMM. A nonlinear mixed-integer programming model is constructed to minimize the total cost of VCMP. The matching process between vehicle and commodity is realized by GMM-EM, as a preprocessing of the solution. The design of the vehicle-commodity matching platform for VCMP is designed to reduce and eliminate the information asymmetry between supply and demand so that the order allocation can work at the right time and the right place and use the optimal solution of vehicle-commodity matching. Furthermore, the numerical experiment of an e-commerce supply chain proves that a hybrid evolutionary algorithm (HEA) is superior to the traditional method, which provides a decision-making reference for e-commerce VCMP.

APA, Harvard, Vancouver, ISO, and other styles

9

Pelizza, Cristian Rafael. "UMA ANÁLISE DO CANAL DE TRANSMISSÃO E DA DEMANDA AGREGADA POR CRÉDITO NO BRASIL, DE 2003 A 2012." Revista Cadernos de Economia 21, no. 38 (March 12, 2019): 63–73. http://dx.doi.org/10.46699/rce.v21i38.4299.

Full text

Abstract:

O objetivo do presente artigo é apresentar um modelo, com base no trabalho de Bernanke e Blinder (1988), em que o crédito possui impacto macroeconômico, como canal de transmissão das políticas monetárias, bem como estimar a demanda agregada por crédito, observando o impacto da taxa Selic sobre a mesma. O ajuste do modelo econométrico foi feito utilizando os estimadores de Mínimos Quadrados em Dois Estágios (MQ2E) e Método Generalizado dos Momentos (GMM), sendo as variáveis instrumentais utilizadas relacionadas à oferta agregada de crédito. Os resultados são congruentes com a teoria econômica, com o crescimento de crédito sendo de -0,35% (MQ2E) e -0,55% (GMM) para uma variação de 1% na Selic.

APA, Harvard, Vancouver, ISO, and other styles

10

OSOBA, OSONDE, SANYA MITAIM, and BART KOSKO. "THE NOISY EXPECTATION–MAXIMIZATION ALGORITHM." Fluctuation and Noise Letters 12, no. 03 (September 2013): 1350012. http://dx.doi.org/10.1142/s0219477513500120.

Full text

Abstract:

We present a noise-injected version of the expectation–maximization (EM) algorithm: the noisy expectation–maximization (NEM) algorithm. The NEM algorithm uses noise to speed up the convergence of the EM algorithm. The NEM theorem shows that additive noise speeds up the average convergence of the EM algorithm to a local maximum of the likelihood surface if a positivity condition holds. Corollary results give special cases when noise improves the EM algorithm. We demonstrate these noise benefits on EM algorithms for three data models: the Gaussian mixture model (GMM), the Cauchy mixture model (CMM), and the censored log-convex gamma model. The NEM positivity condition simplifies to a quadratic inequality in the GMM and CMM cases. A final theorem shows that the noise benefit for independent identically distributed additive noise decreases with sample size in mixture models. This theorem implies that the noise benefit is most pronounced if the data is sparse.

APA, Harvard, Vancouver, ISO, and other styles

11

Chen, Chunlei, Chengduan Wang, Jinkui Hou, Ming Qi, Jiangyan Dai, Yonghui Zhang, and Peng Zhang. "Improving Accuracy of Evolving GMM Under GPGPU-Friendly Block-Evolutionary Pattern." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 03 (August 6, 2019): 2050006. http://dx.doi.org/10.1142/s0218001420500068.

Full text

Abstract:

As a classical clustering model, Gaussian Mixture Model (GMM) can be the footstone of dominant machine learning methods like transfer learning. Evolving GMM is an approximation to the classical GMM under time-critical or memory-critical application scenarios. Such applications often have constraints on time-to-answer or high data volume, and raise high computation demand. A prominent approach to address the demand is GPGPU-powered computing. However, the existing evolving GMM algorithms are confronted with a dilemma between clustering accuracy and parallelism. Point-wise algorithms achieve high accuracy but exhibit limited parallelism due to point-evolutionary pattern. Block-wise algorithms tend to exhibit higher parallelism. Whereas, it is challenging to achieve high accuracy under a block-evolutionary pattern due to the fact that it is difficult to track evolving process of the mixture model in fine granularity. Consequently, the existing block-wise algorithm suffers from significant accuracy degradation, compared to its batch-mode counterpart: the standard EM algorithm. To cope with this dilemma, we focus on the accuracy issue and develop an improved block-evolutionary GMM algorithm for GPGPU-powered computing systems. Our algorithm leverages evolving history of the model to estimate the latest model order in each incremental clustering step. With this model order as a constraint, we can perform similarity test in an elastic manner. Finally, we analyze the evolving history of both mixture components and the data points, and propose our method to merge similar components. Experiments on real images show that our algorithm significantly improves accuracy of the original general purpose bock-wise algorithm. The accuracy of our algorithm is at least comparable to that of the standard EM algorithm and even outperforms the latter under certain scenarios.

APA, Harvard, Vancouver, ISO, and other styles

12

Bhuvaneswari, M. "Gaussian mixture model: An application to parameter estimation and medical image classification." Journal of Scientific and Innovative Research 5, no. 3 (June 25, 2016): 100–105. http://dx.doi.org/10.31254/jsir.2016.5308.

Full text

Abstract:

Gaussian mixture model based parameter estimation and classification has recently received great attention in modelling and processin g data. Gaussian Mixture Model (GMM) is the probabilistic model for representing the presence of subpopulations and it works well with the classification and parameter estimation strategy. Here in this work Maximum Likelihood Estimation (MLE) based on Expectation Maximization (EM) is being used for the parameter estimation approach and the estimated parameters are being used for the training and the testing of the images for their normality and the abnormality. With the mean and the covariance calculated as the parameters they are used in the Gaussian Mixture Model (GMM) based training of the classifier. Support Vector Machine a discriminative classifier and the Gaussian Mixture Model a generative model classifier are the two most popular techniques. The performance of the classification strategy of both the classifiers used has a better proficiency when compared to the other classifiers. By combining the SVM and GMM we co uld be able to classify at a better level since estimating the parameters through the GMM has a very few amount of features and hence it is not needed to use any of the feature reduction techniques. In this the GMM classifier and the SVM classifier are trained usin g the parameters and they are to be compared.

APA, Harvard, Vancouver, ISO, and other styles

13

Bandi, Hari, Dimitris Bertsimas, and Rahul Mazumder. "Learning a Mixture of Gaussians via Mixed-Integer Optimization." INFORMS Journal on Optimization 1, no. 3 (July 2019): 221–40. http://dx.doi.org/10.1287/ijoo.2018.0009.

Full text

Abstract:

We consider the problem of estimating the parameters of a multivariate Gaussian mixture model (GMM) given access to n samples that are believed to have come from a mixture of multiple subpopulations. State-of-the-art algorithms used to recover these parameters use heuristics to either maximize the log-likelihood of the sample or try to fit first few moments of the GMM to the sample moments. In contrast, we present here a novel mixed-integer optimization (MIO) formulation that optimally recovers the parameters of the GMM by minimizing a discrepancy measure (either the Kolmogorov–Smirnov or the total variation distance) between the empirical distribution function and the distribution function of the GMM whenever the mixture component weights are known. We also present an algorithm for multidimensional data that optimally recovers corresponding means and covariance matrices. We show that the MIO approaches are practically solvable for data sets with n in the tens of thousands in minutes and achieve an average improvement of 60%–70% and 50%–60% on mean absolute percentage error in estimating the means and the covariance matrices, respectively, over the expectation–maximization (EM) algorithm independent of the sample size n. As the separation of the Gaussians decreases and, correspondingly, the problem becomes more difficult, the edge in performance in favor of the MIO methods widens. Finally, we also show that the MIO methods outperform the EM algorithm with an average improvement of 4%–5% on the out-of-sample accuracy for real-world data sets.

APA, Harvard, Vancouver, ISO, and other styles

14

Muthahharah, Andi Shahifah, Muhammad Arif Tiro, and Aswi Aswi. "Application of Soft-Clustering Analysis Using Expectation Maximization Algorithms on Gaussian Mixture Model." Jurnal Varian 6, no. 1 (November 13, 2022): 71–80. http://dx.doi.org/10.30812/varian.v6i1.2142.

Full text

Abstract:

Research on soft-clustering has not been explored much compared to hard-clustering. Soft-clustering algorithms are important in solving complex clustering problems. One of the soft-clustering methods is the Gaussian Mixture Model (GMM). GMM is a clustering method to classify data points into different clusters based on the Gaussian distribution. This study aims to determine the number of clusters formed by using the GMM method. The data used in this study is synthetic data on water quality indicators obtained from the Kaggle website. The stages of the GMM method are: imputing the Not Available (NA) value (if there is an NA value), checking the data distribution, conducting a normality test, and standardizing the data. The next step is to estimate the parameters with the Expectation Maximization (EM) algorithm. The best number of clusters is based on the biggest value of the Bayesian Information Creation (BIC). The results showed that the best number of clusters from synthetic data on water quality indicators was 3 clusters. Cluster 1 consisted of 1110 observations with low-quality category, cluster 2 consisted of 499 observations with medium quality category, and cluster 3 consisted of 1667 observations with high-quality category or acceptable. The results of this study recommend that the GMM method can be grouped correctly when the variables used are generally normally distributed. This method can be applied to real data, both in which the variables are normally distributed or which have a mixture of Gaussian and non-Gaussian.

APA, Harvard, Vancouver, ISO, and other styles

15

Paulino, Mário Fonseca, Eduardo Henrique Bevitori Kling de Moraes, Joanis Tilemahos Zervoudakis, Emerson Alexandrino, and Darcilene Maria de Figueiredo. "Fontes de energia em suplementos múltiplos de auto-regulação de consumo na recria de novilhos mestiços em pastagens de Brachiaria decumbens durante o período das águas." Revista Brasileira de Zootecnia 34, no. 3 (June 2005): 957–62. http://dx.doi.org/10.1590/s1516-35982005000300029.

Full text

Abstract:

Objetivou-se avaliar o efeito de diferentes fontes energéticas em suplementos múltiplos de auto-regulação de consumo sobre o ganho médio diário (GMD), ganho de peso total (GPT), pH e a concentração de amônia ruminal em novilhos recriados em pastejo no período das águas. Foram avaliados suplementos contendo grão de milho moído (GMM), milho desintegrado com palha e sabugo (MDPS), sorgo moído (SM) e tratamento controle (mistura mineral - MM). Utilizaram-se 16 novilhos mestiços Holandês-Zebu, não-castrados, com 12 meses de idade e peso médio inicial de 265 kg para avaliar o desempenho. Os parâmetros ruminais foram obtidos utilizando-se quatro novilhos mestiços Holandês-Zebu fistulados no rúmen. O pH do líquido ruminal variou de 6,43 a 6,62 (média de 6,55), não sendo influenciado pelas quantidades de sal e de suplemento consumidas. As concentrações de amônia foram de 9,61; 25,71; 24,45 e 26,04 mg/dL, respectivamente para os tratamentos MM, GMM, MDPS, SM. Não se verificou diferença entre os tratamentos, contudo o suplemento MDPS proporcionou ganhos adicionais em torno de 220 g/animal/dia. Maiores concentrações de amônia ruminal foram observadas nos animais suplementados.

APA, Harvard, Vancouver, ISO, and other styles

16

WATANABE, Hidenori, and Shogo MURAMATSU. "Look-Up-Table-Based Exponential Computation and Application to an EM Algorithm for GMM." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E96.A, no. 5 (2013): 935–39. http://dx.doi.org/10.1587/transfun.e96.a.935.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Shi, Wenhua, Xiongwei Zhang, Xia Zou, and Wei Han. "Deep neural network and noise classification-based speech enhancement." Modern Physics Letters B 31, no. 19-21 (July 27, 2017): 1740096. http://dx.doi.org/10.1142/s0217984917400966.

Full text

Abstract:

In this paper, a speech enhancement method using noise classification and Deep Neural Network (DNN) was proposed. Gaussian mixture model (GMM) was employed to determine the noise type in speech-absent frames. DNN was used to model the relationship between noisy observation and clean speech. Once the noise type was determined, the corresponding DNN model was applied to enhance the noisy speech. GMM was trained with mel-frequency cepstrum coefficients (MFCC) and the parameters were estimated with an iterative expectation-maximization (EM) algorithm. Noise type was updated by spectrum entropy-based voice activity detection (VAD). Experimental results demonstrate that the proposed method could achieve better objective speech quality and smaller distortion under stationary and non-stationary conditions.

APA, Harvard, Vancouver, ISO, and other styles

18

Severo, Rodrigo, João Zani, and Carlos A. Diehl. "Estrutura de capital e estratégia em mercados competitivos: uma análise empírica da relação." Revista de Administração da UFSM 8, no. 2 (June 30, 2015): 298. http://dx.doi.org/10.5902/198346597249.

Full text

Abstract:

Um extenso corpo de pesquisa tem identificado diversos determinantes da estrutura de capital. Várias características das empresas têm sido relacionadas como fatores que influenciam a estrutura de capital como, por exemplo, tamanho, oportunidades de crescimento, lucratividade, escudos fiscais e proporção de ativos fixos. Alguns estudos analisaram o uso da estrutura financeira como uma variável estratégica em mercado de produtos competitivos. No entanto, há poucas evidências empíricas sobre o efeito destas condições na estrutura de capital. O objetivo desta investigação foi verificar a interação entre a estrutura de capital e a estratégia competitiva em mercado de produtos e insumos. Para isso, foi estimado um modelo de equação simultânea e a utilização dos métodos dos mínimos quadrados ordinários (OLS), mínimos quadros em dois estágios (2SLS) e o método dos momentos generalizados (GMM). As evidências encontradas neste estudo confirmam a influência da estrutura de capital sobre a estratégia competitiva em mercados de produtos e insumos e vice-versa. Este estudo apresenta, também, uma contribuição do ponto de vista metodológico, visto o ineditismo da aplicação dos métodos de estimação 2SLS e GMM, para testar os determinantes da estrutura de capital no mercado brasileiro. Os resultados são robustos a partir de diferentes definições operacionais e especificações econométricas.

APA, Harvard, Vancouver, ISO, and other styles

19

Mahpolah, Mahpolah, Suharto Suharto, Arief Wibowo, and Bambang Widjanarko Otok. "The Estimation of Generalized Method Moment Poisson Regression Model on the Prevalence of Acute Respiratory Tract Infection (RTI) in South Kalimantan." CAUCHY 5, no. 3 (December 6, 2018): 161. http://dx.doi.org/10.18860/ca.v5i3.5881.

Full text

Abstract:

ACUTE (RTI) is still an important health problem because the cause of the death of infants and children under five high enough, 1 from 4 death that happens. The purpose of this research examines the factors that affect the genesis ACUTE (RTI) using poisson regression approach with estimates of the maximum likelihood estimator (MLE) and generalized method moment (GMM). This research done in the area of Health Clinic in South Kalimantan. The results of the study showed that the estimates of the GMM method on Poisson regression model gives better performance in terms of the significance of the parameters than the MLE method. The factors that affect an increasing number of the prevalence of ACUTE (RTI) a region namely persentase Breast Feeding non-exclusive (0.0279), the percentage of low birth weight (0.0569), the percentage of shelter density (0.028), the percentage of the existence of smoker family members in the house (0.0308), the percentage of immunization is not complete (0.0193). While the factors that affect a downturn in the number of the prevalence of ACUTE (RTI) in a region which is the percentage of the number of infants less than 2 (0.0364), the percentage of normal nutrition status (0.0224), the percentage of Mothers Education on high school (0.0339), and the percentage of social economy (UMP enough to top) (0.0194).

APA, Harvard, Vancouver, ISO, and other styles

20

Chen, Guang Hua, and Gui Zhi Sheng. "Detection of Moving Objects Based on Mixture Gaussian Model." Advanced Materials Research 1039 (October 2014): 274–79. http://dx.doi.org/10.4028/www.scientific.net/amr.1039.274.

Full text

Abstract:

The paper proposes an improved adaptive Gaussian mixture model (GMM) approach with online EM algorithms for updating, which solves the video segmentation problems carried by busy environment and illumination change. Different learning rates are set for foreground district and background district respectively, which improves the convergence speed of background model. A shadow removal scheme is also introduced for extracting complete moving objects. It is based on brightness distortion and chromaticity distortion in RGB color space. Morphological filtering and connected components analysis algorithm are also introduced to process the result of background subtraction. The experiment results show that the improved GMM has good accuracy and high adaptability in video segmentation. It can extract a complete and clear moving object when it is incorporated with shadow removal.

APA, Harvard, Vancouver, ISO, and other styles

21

Somha, Worawit, Hiroyuki Yamauchi, and Yan Zhang. "Fitting Mixtures of Gaussians to Heavy-Tail Distributions to Analyze Fail-Bit Probability of Nano-Scaled Static Random Access Memory." Advanced Materials Research 677 (March 2013): 317–25. http://dx.doi.org/10.4028/www.scientific.net/amr.677.317.

Full text

Abstract:

This paper proposes a fitting method to approximate a heavy-tailed Gamma distribution characterizing the random telegraph noises by simple Gaussian mixtures model (GMM). The concepts central to the proposed method are 1) adaptive segmentation of the long-heavy tailed distributions such that the log-likelihood of GMM in each partition is maximized and 2) copy and paste with an adequate weight into each partition. It is verified that the proposed method can reduce the error of the fail-bit predictions by 2-orders of magnitude while reducing the iterations for EM step convergence to 1/16 at the interest point of the fail probability of 10-12 which corresponds to the design point to realize a 99.9% yield of 1Gbit chips.

APA, Harvard, Vancouver, ISO, and other styles

22

Dun, Yueqin, and Yu Kong. "Efficient Johnson-SB Mixture Model for Segmentation of CT Liver Image." Journal of Healthcare Engineering 2022 (April 14, 2022): 1–21. http://dx.doi.org/10.1155/2022/5654424.

Full text

Abstract:

To overcome the problem that the traditional Gaussian mixture model (GMM) cannot well describe the skewness distribution of the gray-level histogram of a liver CT slice, we propose a novel segmentation method for liver CT images by introducing the Johnson-SB mixture model (JSBMM). The Johnson-SB model not only has a flexible asymmetrical distribution but also covers a variety of other distributions as well. In this article, the parameter optimization formulas for JSBMM were derived by employing the expectation-maximization (EM) algorithm and maximum likelihood. The implementation process of the JSBMM-based segmentation algorithm is provided in detail. To make better use of the skewness of Johnson-SB and improve the segmentation accuracy, we devise an idea to divide the histogram into two parts and calculate the segmentation threshold for each part, respectively, which is called JSBMM-TDH. By analyzing and comparing the segmentation thresholds with different cluster numbers, it is illustrated that the segmentation threshold of JSBMM-TDH will tend to be stable with the increasing of cluster number, while that of GMM is sensitive to different cluster numbers. The proposed JSBMM-TDH is applied to segment four randomly obtained abdominal CT image sequences, and the segmentation results and robustness have been compared between JSBMM-TDH and GMM. It is verified that JSBMM-TDH has preferable segmentation results and better robustness than GMM for the segmentation of liver CT images.

APA, Harvard, Vancouver, ISO, and other styles

23

Huang, Xiaoyi, Haoran Xu, and Jizheng Chu. "Nonlinear Model Order Selection: A GMM Clustering Approach Based on a Genetic Version of EM Algorithm." Mathematical Problems in Engineering 2022 (December 22, 2022): 1–16. http://dx.doi.org/10.1155/2022/9958210.

Full text

Abstract:

Choosing an accurate model order is one of the important sections in system identification. Traditionally, the model order selection of a nonlinear system depends on a predetermined model. However, it requires excess calculation and is impossible to get rid of the trouble of the structural design of the model, once the specific model was determined. A false nearest neighbor (FNN) algorithm that only relies on input-output data to estimate the model order is proposed here. Due to the FNN algorithm is sensitive to its own threshold which is a crucial constant for evaluating the model structure, Gaussian mixture model (GMM) clustering based on a genetic version of the expectation-maximization (EM) algorithm and minimum description length (MDL) criterion is developed in this paper, where the order can be determined without relying on a specific model. The GMM clustering is proposed to calculate the threshold of the FNN. Then, the genetic algorithm and MDL criteria are embedded to optimize the calculation of the EM algorithm as reduce the influence of initial values and not prone to fall into local extreme values as well. Three examples are given here to indicate the superiority of this technique: simulation of a strongly nonlinear system, isothermal polymerization process, and Van der Vusse reaction in relevant reference. Finally, some typical modeling methods are conducted to confirm the validity of this approach.

APA, Harvard, Vancouver, ISO, and other styles

24

Tang, Jin-jun, Jin Hu, Yi-wei Wang, He-lai Huang, and Yin-hai Wang. "Estimating hotspots using a Gaussian mixture model from large-scale taxi GPS trace data." Transportation Safety and Environment 1, no. 2 (November 1, 2019): 145–53. http://dx.doi.org/10.1093/tse/tdz006.

Full text

Abstract:

Abstract The data collected from taxi vehicles using the global positioning system (GPS) traces provides abundant temporal-spatial information, as well as information on the activity of drivers. Using taxi vehicles as mobile sensors in road networks to collect traffic information is an important emerging approach in efforts to relieve congestion. In this paper, we present a hybrid model for estimating driving paths using a density-based spatial clustering of applications with noise (DBSCAN) algorithm and a Gaussian mixture model (GMM). The first step in our approach is to extract the locations from pick-up and drop-off records (PDR) in taxi GPS equipment. Second, the locations are classified into different clusters using DBSCAN. Two parameters (density threshold and radius) are optimized using real trace data recorded from 1100 drivers. A GMM is also utilized to estimate a significant number of locations; the parameters of the GMM are optimized using an expectation-maximum (EM) likelihood algorithm. Finally, applications are used to test the effectiveness of the proposed model. In these applications, locations distributed in two regions (a residential district and a railway station) are clustered and estimated automatically.

APA, Harvard, Vancouver, ISO, and other styles

25

Maciejko, Waldemar. "The Effect of Voice over IP Transmission Degradations on MAP-EM-GMM Speaker Verification Performance." Archives of Acoustics 40, no. 3 (September 1, 2015): 407–17. http://dx.doi.org/10.1515/aoa-2015-0042.

Full text

Abstract:

Abstract Despite the growing importance of packet switching systems, there is still a shortage of thorough analyses of VoIP transmission effect on speech and speaker recognition performance. Voice over IP transmission systems use packet switching. There is no guarantee of delivery. The main disadvantage of VoIP is a packet loss which has a major impact on the performance experienced by the users of the network. There are several techniques to mask the effects of a packet loss, referred to as packet loss concealment. In this study, the effect of voice transmission over IP on automatic speaker verification system performance was investigated. The analyzed system was based on MAP-EM-GMM modelling methods. Four various speech codecs of H.323 standard were investigated with special emphasis placed on the packet loss phenomenon and various packet loss concealment techniques.

APA, Harvard, Vancouver, ISO, and other styles

26

Pal, Samyajoy, and Christian Heumann. "Clustering compositional data using Dirichlet mixture model." PLOS ONE 17, no. 5 (May 18, 2022): e0268438. http://dx.doi.org/10.1371/journal.pone.0268438.

Full text

Abstract:

A model-based clustering method for compositional data is explored in this article. Most methods for compositional data analysis require some kind of transformation. The proposed method builds a mixture model using Dirichlet distribution which works with the unit sum constraint. The mixture model uses a hard EM algorithm with some modification to overcome the problem of fast convergence with empty clusters. This work includes a rigorous simulation study to evaluate the performance of the proposed method over varied dimensions, number of clusters, and overlap. The performance of the model is also compared with other popular clustering algorithms often used for compositional data analysis (e.g. KMeans, Gaussian mixture model (GMM) Gaussian Mixture Model with Hard EM (Hard GMM), partition around medoids (PAM), Clustering Large Applications based on Randomized Search (CLARANS), Density-Based Spatial Clustering of Applications with Noise (DBSCAN) etc.) for simulated data as well as two real data problems coming from the business and marketing domain and physical science domain, respectively. The study has shown promising results exploiting different distributional patterns of compositional data.

APA, Harvard, Vancouver, ISO, and other styles

27

Cunha, Ronan, Fernanda Finotti C. Perobelli, and Eduardo Gonçalves. "Investimento em Intangível e Criação de Valor: uma Análise das Companhias Abertas Brasileiras no Período 2000-2014." Economia Aplicada 22, no. 2 (June 5, 2018): 211–42. http://dx.doi.org/10.11606/1980-5330/ea119149.

Full text

Abstract:

Este artigo analisa a relação entre investimentos em ativos intangíveis e criação de valor das empresas brasileiras de capital aberto no Brasil, medida pelo Q de Tobin. No artigo, aplica-se o system GMM em um painel de dados formado por 208 firmas com ações negociadas na Bolsa de Valores (B3) brasileira no período 2000-2014. Os dados são provenientes da Economática e Instituto Nacional de Propriedade Industrial (INPI). O principal resultado mostra impactos positivos do fluxo de investimento em ativos intangíveis (mas não seu acúmulo) sobre o valor das empresas.

APA, Harvard, Vancouver, ISO, and other styles

28

Guo, Wei, Tianhong Pan, Zhengming Li, and Shan Chen. "Batch process modeling by using temporal feature and Gaussian mixture model." Transactions of the Institute of Measurement and Control 42, no. 6 (December 1, 2019): 1204–14. http://dx.doi.org/10.1177/0142331219887827.

Full text

Abstract:

Multi-model/multi-phase modeling algorithm has been widely used to monitor the product quality in complicated batch processes. Most multi-model/ multi-phase modeling methods hinge on the structure of a linearly separable space or a combination of different sub-spaces. However, it is impossible to accurately separate the overlapping region samples into different operating sub-spaces using unsupervised learning techniques. A Gaussian mixture model (GMM) using temporal features is proposed in the work. First, the number of sub-model is estimated by using the maximum interval process trend analysis algorithm. Then, the GMM parameters constrained with the temporal value are identified by using the expectation maximization (EM) algorithm, which minimizes confusion in overlapping regions of different Gaussian processes. A numerical example and a penicillin fermentation process demonstrate the effectiveness of the proposed algorithm.

APA, Harvard, Vancouver, ISO, and other styles

29

Sverner, Carolina, Andrea Minardi, and Fernando Tassinari Moraes. "impacto do momento ESG no apreçamento de ações." Brazilian Review of Finance 21, no. 1 (March 20, 2023): 77–105. http://dx.doi.org/10.12660/rbfin.v21n1.2023.85688.

Full text

Abstract:

Este artigo investiga se a melhora das práticas ambientais, sociais e de governança (ESG) das empresas, refletida na alteração do rating ESG gera um prêmio positivo e significativo nos retornos de suas ações. Para isso, foram coletados dados das ações que compõem o S&P500 e criado um fator Momento ESG (alto momento menos baixo momento) controlado por tamanho, a partir de um portfólio long-short rebalanceado anualmente, seguindo o procedimento empregado por Fama e French (1993). Os resultados apontaram prêmio de risco positivo e significante para o fator de Momento ESG quando estimados via regressão crosssectional em dois estágios. Esse prêmio, apesar de se manter positivo em todas as regressões, perde significância ao utilizarmos o método dos momentos generalizados (GMM) para a estimação. De forma similar, foi construído um fator ESG, contemplando as notas de forma estática, para validar uma hipótese adicional de que há um prêmio de risco negativo vinculado a esse fator na explicação dos retornos cross section das ações. Os resultados obtidos para o fator ESG indicaram prêmio de risco negativo e significante quando estimados por regressão crosssectional em dois estágios. Esse prêmio, apesar de se manter negativo na maioria das regressões, perde significância ao utilizarmos o GMM para estimação.

APA, Harvard, Vancouver, ISO, and other styles

30

Jia, Kexin, Yuxia Xin, and Ting Cheng. "Gaussian mixture modelling by exploiting competitive stop EM algorithm." Journal of Physics: Conference Series 2234, no. 1 (April 1, 2022): 012003. http://dx.doi.org/10.1088/1742-6596/2234/1/012003.

Full text

Abstract:

Abstract To improve the robustness of order selection and parameter learning for Gaussian mixture model (GMM), this paper proposes a competitive stop expectation-maximization (EM) algorithm, which is based on two stop conditions. The first condition is a Lilliefors test based multivariate (MV) normality criterion, which is used to determine whether to split a component into two different components. The EM algorithm stops splitting when all components have MV normality. The minimum description length (MDL) criterion is used in the second condition, which competes with the first condition to prevent the EM algorithm from over-splitting. Simulation experiments verify the effectiveness of the proposed algorithm.

APA, Harvard, Vancouver, ISO, and other styles

31

Gadelha, Sérgio Ricardo de Brito, and José Angelo Divino. "Uma análise da ciclicidade da política fiscal brasileira." Estudos Econômicos (São Paulo) 43, no. 4 (December 2013): 711–43. http://dx.doi.org/10.1590/s0101-41612013000400004.

Full text

Abstract:

Uma vasta literatura teórica e empírica afirma que a política fiscal nos países em desenvolvimento é pró-cíclica, enquanto que em nações industrializadas a política fiscal é anticíclica ou acíclica. Utilizando dados mensais, macroeconômicos e fiscais, abrangendo o período de março de 2002 a julho de 2011, os resultados obtidos a partir de estimações GMM, em modelos estáticos e dinâmicos, indicam comportamento pró-cíclico da política fiscal brasileira, onde as teorias sobre variabilidade da base tributária, corrupção e economia informal contribuem para explicar esse comportamento. Todavia, a teoria sobre restrição ao crédito internacional não encontra respaldo empírico no período analisado.

APA, Harvard, Vancouver, ISO, and other styles

32

Barcelos Ferreira, Victor, and Evandro Camargos Teixeira. "O impacto da distorção idade-série sobre a criminalidade nos municípios de Minas Gerais." Revista Brasileira de Segurança Pública 12, no. 2 (April 23, 2019): 269–91. http://dx.doi.org/10.31060/rbsp.2018.v12.n2.960.

Full text

Abstract:

O presente trabalho analisa o efeito da distorção idade-série sobre os crimes violentos contra pessoa nos municípios do estado de Minas Gerais. Utilizou-se um modelo com dados em painel com estimador GMM-SYS com objetivo de captar os efeitos intertemporais envolvidos nesse processo. Os resultados permitem concluir que em locais onde há acentuação da referida distorção, haverá maior propensão à incidência de crimes violentos. Por fim, enaltece-se a importância das políticas públicas em educação, orientadas para a diminuição da distorção, compreendida sua influência sobre dinâmica de ingresso dos adolescentes no mundo do crime.

APA, Harvard, Vancouver, ISO, and other styles

33

Castro Junior, Francisco Henrique Figueiredo de, and Claudia Emiko Yoshinaga. "Coassimetria, cocurtose e as taxas de retorno das ações: uma análise com dados em painel." RAM. Revista de Administração Mackenzie 13, no. 1 (February 2012): 110–44. http://dx.doi.org/10.1590/s1678-69712012000100006.

Full text

Abstract:

Modelos de apreçamento de ativos têm sido um tema sob constante investigação em finanças. Desde o capital asset pricing model (CAPM) proposto por Sharpe (1964), tais modelos relacionam, geralmente de maneira linear, a taxa de retorno esperada de um ativo ou carteira de ativos com fatores de risco sistêmico. Esta pesquisa apresenta um teste de um modelo de apreçamento, com dados brasileiros, introduzindo em sua formulação fatores de risco baseados em comomentos estatísticos. O modelo proposto é uma extensão do CAPM original acrescido da coassimetria e da cocurtose entre as taxas de retorno das ações das empresas que compõem a amostra e as taxas de retorno da carteira de mercado. Os efeitos de outras variáveis, como o valor de mercado sobre valor contábil, a alavancagem financeira e um índice de negociabilidade em bolsa, serviram de variáveis de controle. A amostra foi composta de 179 empresas brasileiras não financeiras negociadas na BM&FBovespa e com dados disponíveis entre os anos de 2003 a 2007. A metodologia consistiu em calcular os momentos sistêmicos anuais a partir de taxas de retornos semanais e em seguida testá-los em um modelo de apreçamento, a fim de verificar se há um prêmio pelo risco associado a cada uma dessas medidas de risco. Foi empregada a técnica de análise de dados em painel, estimada pelo método dos momentos generalizado (GMM). O emprego do GMM visa lidar com potenciais problemas de determinação simultânea e endogeneidade nos dados, evitando a ocorrência de viés nas estimações. Os resultados das estimações mostram que a relação das taxas de retorno dos ativos com a covariância e a cocurtose são estatisticamente significantes. Os resultados se mostraram robustos a especificações alternativas do modelo. O artigo contribui para a literatura por apresentar evidências empíricas brasileiras de que há um prêmio pelo risco associado aos momentos sistêmicos.

APA, Harvard, Vancouver, ISO, and other styles

34

Jia, Hui, Guo Hua Geng, and Jian Gang Zhang. "Consistent Mesh Segmentation Based on Shape Diameter Function and EM." Advanced Materials Research 1049-1050 (October 2014): 1417–20. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1417.

Full text

Abstract:

3D model segmentation is a new research focus in the field of computer graphics. The segmentation algorithm of this paper is consistent segmentation which is about a group of 3D model with shape similarity. A volume-based shape-function called the shape diameter function (SDF) is used to on behalf of the characteristics of the model. Gaussian mixture model (GMM) is fitting k Gaussians to the SDF values, and EM algorithm is used to segment 3D models consistently. The experimental results show that this algorithm can effectively segment the 3D models consistently.

APA, Harvard, Vancouver, ISO, and other styles

35

Wu, Weisan. "The Discrete Gaussian Expectation Maximization (Gradient) Algorithm for Differential Privacy." Computational Intelligence and Neuroscience 2021 (December 30, 2021): 1–13. http://dx.doi.org/10.1155/2021/7962489.

Full text

Abstract:

In this paper, we give a modified gradient EM algorithm; it can protect the privacy of sensitive data by adding discrete Gaussian mechanism noise. Specifically, it makes the high-dimensional data easier to process mainly by scaling, truncating, noise multiplication, and smoothing steps on the data. Since the variance of discrete Gaussian is smaller than that of the continuous Gaussian, the difference privacy of data can be guaranteed more effectively by adding the noise of the discrete Gaussian mechanism. Finally, the standard gradient EM algorithm, clipped algorithm, and our algorithm (DG-EM) are compared with the GMM model. The experiments show that our algorithm can effectively protect high-dimensional sensitive data.

APA, Harvard, Vancouver, ISO, and other styles

36

Patel, Pavitra, A. A. Chaudhari, M. A. Pund, and D. H. Deshmukh. "Speech Emotion Recognition System Using Gaussian Mixture Model and Improvement proposed via Boosted GMM." IRA-International Journal of Technology & Engineering (ISSN 2455-4480) 7, no. 2 (S) (July 10, 2017): 56. http://dx.doi.org/10.21013/jte.icsesd201706.

Full text

Abstract:

Speech emotion recognition is an important issue which affects the human machine interaction. Automatic recognition of human emotion in speech aims at recognizing the underlying emotional state of a speaker from the speech signal. Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, GMMs are used to model the class-conditional distributions of acoustic features and their parameters are estimated by the expectation maximization (EM) algorithm based on a training data set. In this paper, we introduce a boosting algorithm for reliably and accurately estimating the class-conditional GMMs. The resulting algorithm is named the Boosted-GMM algorithm. Our speech emotion recognition experiments show that the emotion recognition rates are effectively and significantly boosted by the Boosted-GMM algorithm as compared to the EM-GMM algorithm. During this interaction, human beings have some feelings that they want to convey to their communication partner with whom they are communicating, and then their communication partner may be the human or machine. This work dependent on the emotion recognition of the human beings from their speech signal Emotion recognition from the speaker’s speech is very difficult because of the following reasons: Because of the existence of the different sentences, speakers, speaking styles, speaking rates accosting variability was introduced. The same utterance may show different emotions. Therefore it is very difficult to differentiate these portions of utterance. Another problem is that emotion expression is depending on the speaker and his or her culture and environment. As the culture and environment gets change the speaking style also gets change, which is another challenge in front of the speech emotion recognition system.

APA, Harvard, Vancouver, ISO, and other styles

37

Wang, Kaikai, Chun’an Tang, Ke Ma, Xintang Wang, and Qiang Li. "An Automatic Recognition Method of Microseismic Signals Based on S Transformation and Improved Gaussian Mixture Model." Advances in Civil Engineering 2020 (August 7, 2020): 1–24. http://dx.doi.org/10.1155/2020/8825990.

Full text

Abstract:

The microseismic signals in the coal minefield are very complex because of its special environment with a large number of blast vibration signals, and how to effectively identify the microseismic signals is still a big problem. S transform (ST) and Manifold Learning (ML) methods are introduced to extract the characteristics of the microseismic signals, and Gaussian Mixture Model based on the improved Bee Colony optimization algorithm (IBC-GMM) is established to identify the microseismic signals accurately. Firstly, the time-frequency characteristics of microseismic signals in coal mine are extracted by ST analysis. It is found that there are obvious time-frequency differences between rock-fracturing signals and blast vibration signals. Blast vibration signals have short duration, high frequency, and complex frequency spectrum, and their dominant frequencies are mainly over 100 Hz. However, rock-fracturing signals are relatively slow, with low frequency and stable spectrum change, and their dominant frequencies are generally below 100 Hz. Then, combining with the microseismic data of Xiashinjie coal mine in Tongchuan, China, the feature dimension reduction is carried out by Manifold Learning (ML) method, and the processed feature vectors are automatically recognized by IBC-GMM. Field test results show that the method summarizes the characteristics of the microseismic wave which are difficult to emerge as the learning vector, and the features reflect the key features of microseismic signals well. The identification accuracy is as high as 94%, and its recognition effect is superior to other recognition models (such as traditional Gaussian Mixture Model based on Expectation-Maximum (EM-GMM), Backpropagation (BP) neural network, Random Forests (RF), Bayes (Bayes) methods, and Logistic Regression (LR) method). Therefore, IBC-GMM could be used to mine engineering microseismic monitoring waveform recognition to provide the reference.

APA, Harvard, Vancouver, ISO, and other styles

38

Santos, Sandra Batista dos, Elmiro Rosendo do Nascimento, João Luiz Horacio Faccini, Maria Lúcia Barreto, Juliana Ferreira de Almeida, Virginia Léo de Almeida Pereira, and Carlos Augusto Martino Campos. "Detecção do Grupo Mycoplasma mycoides por imunoperoxidase indireta (IPI) e PCR-REA em conduto auditivo de bovinos." Pesquisa Veterinária Brasileira 30, no. 5 (May 2010): 465–69. http://dx.doi.org/10.1590/s0100-736x2010000500015.

Full text

Abstract:

O Grupo Mycoplasma mycoides (GMM) foi diagnosticado por PCR-REA e imunoperoxidase indireta (IPI) em amostras de lavados de conduto auditivo de bovinos no Estado do Rio de Janeiro, Brasil. 60 bovinos foram selecionados aleatoriamente. As lavagens foram feitas com uso de seringas estéreis contendo um volume de 60 mL de solução salina tamponada (PBS pH 7.2). As amostras obtidas foram estocadas em glicerol (1:2) e congeladas a 20ºC até uso. Estas amostras foram diluídas até 10-5 e repicadas em meio Hayflick modificado, sólido e líquido, sendo incubados a 37ºC por 48-72 horas. As placas foram mantidas em microaerofilia e observadas diariamente, para visualização das colônias típicas em “ovo-frito”. Das 60 amostras cultivadas, 48 (80,00%) foram positivas para Mycoplasma spp. A prevalência obtida para o GMM na IPI foi de 20,0% (12/60) enquanto na PCR-REA foi de 41,7% (25/60). Das cepas tipificadas pela IPI 58,3% (7/12) foram M. mycoides subsp. mycoides LC e 41,7% (5/12) foram M. capricolum. Na PCR-REA o grupo M. mycoides foi confirmado pela visualização de um amplicon de 785bp, compatível com este grupo. O valor encontrado no teste Kappa para associação entre estes testes foi de 0,14 (P>0,05. Na clivagem do produto da PCR com a enzima de restrição AluI, de cepas de referências e dos isolados de ouvido os fragmentos obtidos foram de 81, 98, 186 e 236pb, mas não de 370pb, que é específica para o agente da Pleuropneumonia Contagiosa Bovina. A presença de espécies de micoplasmas no conduto auditivo de bovinos assintomáticos representa um risco para propagação de Mycoplasma spp. entre rebanhos bovinos no Brasil.

APA, Harvard, Vancouver, ISO, and other styles

39

Sant'Ana, Naiara Leite dos Santos, and Paulo Celso Pires Sant'Ana. "PERCEPÇÃO DE CONFIANÇA NA AUDITORIA INDEPENDENTE: ÍNDICE DE QUALIDADE." Contabilidade Vista & Revista 32, no. 2 (July 29, 2021): 258–82. http://dx.doi.org/10.22561/cvr.v32i2.6555.

Full text

Abstract:

A Auditoria Independente representa uma atividade complexa uma vez que envolve fatores internos e externos à auditada assim como características do auditor. Ao considerar tamanha complexidade este trabalho foi realizado com o objetivo de criar um Índice de Qualidade de Auditoria - IQUA 2019. A construção de um índice mostra-se importante para que seja possível compreender os fatores que influenciam na qualidade da auditoria, assim como obter uma percepção das companhias e dos anos nas quais a qualidade foi mais evidente. A composição aconteceu por meio da apreciação de aspectos qualitativos do trabalho do auditor e fatores internos e externos à auditada, tais como: tamanho da firma de auditoria; auditoria, representada pela variação na qualidade do serviço prestado entre as firmas de auditoria; tempo de relacionamento auditor-cliente; especialização; comitê de auditoria; risco, honorários e conservadorismo. Foi utilizada a regressão múltipla com dados em painel, estimada por meio do método dos momentos generalizado (GMM), justificado pela possibilidade de endogeneidade entre as variáveis. A utilização do GMM mostra-se relevante uma vez observada a dificuldade em estudos empíricos de auditoria em se inferir uma relação de causa e efeito entre as variáveis. As variáveis selecionadas foram significativas, o que representa que quanto maior o tamanho da firma, o tempo de relacionamento, a especialização, a alavancagem financeira, os honorários e a precaução com que notícias positivas são contabilizadas, em detrimento das ruins, maior a qualidade de auditoria. O fato da companhia possuir comitê tratou-se de um indício para o incremento da qualidade da auditoria.

APA, Harvard, Vancouver, ISO, and other styles

40

Zeng, Li Wen, Shun Xian Zhang, and Xiao Ning Zhang. "The Research on Aggregate Microstructure Uniformity Image Processing of Asphalt Mixture Based on Computer Scanning Technology." Advanced Materials Research 831 (December 2013): 393–400. http://dx.doi.org/10.4028/www.scientific.net/amr.831.393.

Full text

Abstract:

It has become one of the focus topics that using CT (Computer Technology) to obtain asphalt internal microstructure, but combining CT scan cross-sectional different characteristics to carry out digital image processing is rare at this stage, technical means that distinguishing internal material are still relatively rough and arbitrary large, can not be combined between digital image processing and mixture not damage test together effectively. This paper carried out image segmentation based on EM algorithm of Gaussian mixture model (GMM), analysis microstructure uniformity quality of asphalt mixture, and explores internal volume composition case by testing deeply. The results show that Gaussian Mixture Model (GMM) used in this paper can handle CT scan tomographic images better , judge aggregate distribution of asphalt mixture by sector scan method, and evaluate uniformity distribution of asphalt mixture aggregates through aggregate particles area ratio statistical analysis, the research results of this paper can provide reference significance for asphalt microscopic field study .

APA, Harvard, Vancouver, ISO, and other styles

41

Diniz, Marcelo Bentes, Márcia Jucá Teixeira Diniz, Almir Bittencourt da Silva, and Jorge Eduardo Macedo Simões. "Dinâmica de curto prazo do desmatamento da Amazônia Legal: análise do papel das políticas públicas no período de 2000 a 2010." Economia Aplicada 22, no. 4 (December 1, 2018): 177–206. http://dx.doi.org/10.11606/1980-5330/ea141292.

Full text

Abstract:

Discute-se, em um contexto de um painel dinâmico, GMM-SYSTEM, os determinantes de curto prazo na dinâmica do desmatamento na Amazônia Legal no período de 2000 a 2010, ao encontro de testar o papel das políticas públicas relacionadas ao controle do desmatamento e a política de assentamentos destinados à Reforma Agrária na região. As evidências encontradas confirmam a importância da política regulatória no controle do desmatamento, enquanto a política de assentamentos mostrou-se não significante.

APA, Harvard, Vancouver, ISO, and other styles

42

Gomes, Thiago Geovane Pereira, Cassio da Nóbrega Besarria, and José Alderir da Silva. "Informalidade na América Latina: uma análise por Vetores Autorregressivos em Painel." Cadernos Metrópole 25, no. 58 (December 2023): 1017–49. http://dx.doi.org/10.1590/2236-9996.2023-5811.

Full text

Abstract:

Resumo É fundamental conhecer o tamanho, a dinâmica e as principais causas da informalidade para adoção de políticas públicas factíveis. Assim, a fim de contribuir com a literatura, este artigo pretende analisar o comportamento da informalidade em uma amostra de países da América Latina entre 2002 e 2015. A estratégia empírica usará o método de Vetores Autorregressivos (VAR) em Painel para contornar problemas de endogeneidade entre o nível de informalidade e seus principais determinantes. Os resultados da estimação do Generalized method of moments (GMM) e as análises das Funções de Resposta ao Impulso (FRIs) ressaltam o efeito negativo do Produto Interno Bruto (PIB) per capita sobre a informalidade e os efeitos positivos da taxa de desemprego e dos impostos sobre o tamanho da economia informal em relação ao PIB oficial.

APA, Harvard, Vancouver, ISO, and other styles

43

Ramos de Andrade, Eliane. "UMA ANÁLISE DO IMPACTO DO PROGRAMA SAÚDE DA FAMÍLIA SOBRE A TAXA DE MORTALIDADE INFANTIL NOS MUNICÍPIOS DO ESTADO DE ALAGOAS." A Economia em Revista - AERE 21, no. 2 (April 29, 2016): 18. http://dx.doi.org/10.4025/aere.v21i2.21346.

Full text

Abstract:

O objetivo deste estudo é avaliar o impacto do Programa Saúde da Família (PSF) sobre a taxa de mortalidade infantil (tmi) nos municípios alagoanos no período de 2005-2008, ou seja, em que momento o PSF tem cumprido seu papel para reduzir a taxa de mortalidade infantil dos menores de 1 ano. A partir dos dados em painel (Estático e Dinâmico) dos municípios alagoanos, estimamos o efeito do do PSF sobre as taxas de mortalidade infantil através dos modelos de efeitos fixos, Mínimos Quadrados Generalizados (MQG) e Métodos de Momentos Generalizados (GMM). O resultado que se pôde constatar é que o programa saúde família, e outro fator como coeficiente médico por mil habitantes diminua taxa de mortalidade infantil (tmi) no período em análise.

APA, Harvard, Vancouver, ISO, and other styles

44

Lisowski, Karol, and Andrzej Czyżewski. "Adaptive Method for Modeling of Temporal Dependencies between Fields of Vision in Multi-Camera Surveillance Systems." Electronics 10, no. 11 (May 30, 2021): 1303. http://dx.doi.org/10.3390/electronics10111303.

Full text

Abstract:

A method of modeling the time of object transition between given pairs of cameras based on the Gaussian Mixture Model (GMM) is proposed in this article. Temporal dependencies modeling is a part of object re-identification based on the multi-camera experimental framework. The previously utilized Expectation-Maximization (EM) approach, requiring setting the number of mixtures arbitrarily as an input parameter, was extended with the algorithm that automatically adapts the model to statistical data. The probabilistic model was obtained by matching to the histogram of transition times between a particular pair of cameras. The proposed matching procedure uses a modified particle swarm optimization (mPSO). A way of using models of transition time in object re-identification is also presented. Experiments with the proposed method of modeling the transition time were carried out, and a comparison between previous and novel approach results are also presented, revealing that added swarms approximate normalized histograms very effectively. Moreover, the proposed swarm-based algorithm allows for modelling the same statistical data with a lower number of summands in GMM.

APA, Harvard, Vancouver, ISO, and other styles

45

Becker, Kalinca Léia, and Ana Lúcia Kassouf. "Uma análise do efeito dos gastos públicos em educação sobre a criminalidade no Brasil." Economia e Sociedade 26, no. 1 (April 2017): 215–42. http://dx.doi.org/10.1590/1982-3533.2017v26n1art8.

Full text

Abstract:

Resumo O objetivo do estudo é analisar se o gasto público em educação pode contribuir para reduzir a taxa de homicídios e se é necessário um período para que esse resultado seja observado. Para isso, foram utilizados dados socioeconômicos dos estados brasileiros e um modelo de painel dinâmico (GMM-SYS) com uma defasagem para os gastos com educação por habitante, além da relação contemporânea. Os resultados indicaram uma elasticidade negativa de aproximadamente 0,1 na primeira defasagem, ou seja, se os gastos com educação aumentarem 10%, a taxa de homicídios diminuiria 1% no período seguinte, evidenciando que investir em educação pode ser uma forma de política pública de longo prazo para reduzir a criminalidade.

APA, Harvard, Vancouver, ISO, and other styles

46

Cristina Miranda Rodrigues, Ana. "Proteção ao Credor em Países de Origem Civil e Política Corporativa Dividendos: Uma Análise dos Modelos de Resultado e de Substituição." RGC - Revista de Governança Corporativa 8, no. 1 (June 15, 2021): e085. http://dx.doi.org/10.21434/iberoamericanjcg.v8i.85.

Full text

Abstract:

Este artigo investiga os efeitos dos mecanismos de proteção ao credor sobre as políticas corporativas de dividendos, à luz dos modelos de agência de resultado e de substituição. Os resultados empíricos estão baseados em dados de 6.191 empresas, em 27 países de direito civil, durante o período de 2008 a 2017. Para dar suporte às hipóteses formuladas, são apresentadas estatísticas resumidas, regressões Tobit e o Método Generalizado de Momentos (GMM). Os resultados sugerem que, em países de origem civil, a alta proteção ao credor reduz os dividendos de empresas com maiores oportunidades de investimento. Inversamente, quando da baixa proteção à dívida, as empresas pagam mais dividendos. Deste modo, é possível concluir que, em países de origem civil, sob a perspectiva do credor, as políticas de dividendos não são consistentes com os modelos de resultado e de substituição.

APA, Harvard, Vancouver, ISO, and other styles

47

ARRUDA, ELANO FERREIRA, MARIA THALITA ARRUDA OLIVEIRA, and IVAN CASTELAR. "Dinâmica recente da inflação brasileira em ambientes distintos de expectativas forward-looking." Brazilian Journal of Political Economy 37, no. 4 (December 2017): 808–31. http://dx.doi.org/10.1590/0101-31572017v37n04a09.

Full text

Abstract:

RESUMO Este estudo analisa como a inflação brasileira recente responde aos ciclos econômicos e ao seu componente inercial considerando ambientes distintos de expectativas forward-looking no arcabouço da Curva de Phillips Novo-Keynesiana Híbrida (CPNKH). Para tal, faz-se uso de informações mensais entre janeiro de 2002 e agosto de 2015 e estimações de GMM-HAC da CPNKH. Os resultados sugerem que a inflação brasileira ainda possui um forte componente inercial e que, em um ambiente de menor previsibilidade dos agentes, a inflação se mostra mais sensível às oscilações cíclicas da atividade econômica. Por fim, observou-se um repasse cambial positivo e significante para a inflação brasileira.

APA, Harvard, Vancouver, ISO, and other styles

48

Ferreira, Salime Nadur Duarte, Evandro Camargos Teixeira, and Gercione Dionizio Silva. "INFRAESTRUTURA DE TRANSPORTE RODOVIÁRIO E CRESCIMENTO ECONÔMICO NO BRASIL." Revista Baru - Revista Brasileira de Assuntos Regionais e Urbanos 5, no. 2 (December 20, 2019): 251. http://dx.doi.org/10.18224/baru.v5i2.7570.

Full text

Abstract:

O objetivo do presente estudo é analisar o impacto da infraestrutura de transporte rodoviário sobre o crescimento econômico brasileiro no período de 2011 a 2015. Para tal, optou-se pelo modelo econométrico dinâmico para dados em painel, estimado pelo método de Momentos Generalizados Sistêmico (GMM-Sys). Para caracterizar a infraestrutura de transporte rodoviário do país, foram criadas variáveis que mensuram a quantidade e principalmente a qualidade da pavimentação das rodovias brasileiras, com base nas informações da Confederação Nacional de Transporte - CNT. Os resultados demonstram que a qualidade da malha rodoviária impacta positivamente no crescimento econômico brasileiro, reforçando a hipótese de que maiores investimentos em infraestrutura de transporte geram retornos positivos para a economia.

APA, Harvard, Vancouver, ISO, and other styles

49

Rosa, Arthur Antonio Silva, Kárem Cristina de Sousa Ribeiro, and Luciano Ferreira Carvalho. "Volatilidade e Alavancagem: uma Análise das Empresas da América Latina." Contabilidade Gestão e Governança 26, no. 1 (July 31, 2023): 32–62. http://dx.doi.org/10.51341/cgg.v26i1.2992.

Full text

Abstract:

Objetivo: Analisar a relação entre o nível de alavancagem e a volatilidade das ações da América Latina, no período de janeiro de 2005 a junho 2020. Método: Utilizou-se uma regressão linear múltipla, sendo os coeficientes estimados pelo GMM e com os dados dispostos em painel. A volatilidade foi estimada pelo modelo EGARCH e utilizou-se seis medidas de alavancagem. Originalidade/Relevância: O estudo analisa a relação entre volatilidade e alavancagem no contexto da América Latina e mostra que os períodos de crise podem afetar essa relação. Os resultados são relevantes para gestores, que podem ajustar estrategicamente o grau de alavancagem a fim de maximizar o valor da empresa para os acionistas, e também para os investidores, pois permite um melhor alinhamento entre o seu perfil de risco e o retorno almejado. Resultados: Os resultados apontam que há uma relação positiva entre o grau de alavancagem da firma e a volatilidade dos ativos. Também se constatou que, em períodos de crise, mesmo que as empresas reduzam seus níveis alavancagem, a volatilidade tenderá a aumentar devido às incertezas relacionadas a esses períodos. Contribuições Teóricas/Metodológicas: Na análise da relação entre alavancagem e volatilidade, também se verificou o efeito moderador dos períodos de crise e considerou-se a endogeneidade entre as variáveis por meio do GMM. Além disso, a volatilidade foi estimada por meio do modelo EGARCH que considera as assimetrias da volatilidade, sendo os resultados controlados por variáveis corporativas e macroeconômicas.

APA, Harvard, Vancouver, ISO, and other styles

50

Brunozi Júnior, Antonio Carlos, Clóvis Antônio Kronbauer, Antônio Lopo Martinez, and Tiago Wickstrom Alves. "BTD anormais, accruals discricionários e qualidade dos accruals em empresas de capital aberto listadas no Brasil." Revista Contemporânea de Contabilidade 15, no. 35 (June 30, 2018): 108–41. http://dx.doi.org/10.5007/2175-8069.2018v15n35p108.

Full text

Abstract:

Este estudo teve como objetivo analisar as implicações das BTD, decorrentes das práticas de gerenciamentos dos resultados contábeis e tributários, nos accruals discricionários e na qualidade dos accruals em empresas de capital aberto listadas no Brasil. Metodologicamente, considerou-se uma amostra de 290 empresas e o período de 2002 a 2015, com a apuração de uma medida de BTD Anormais para o contexto brasileiro. Em seguida, associou-se as BTD Anormais com proxies de gerenciamento de resultados, que foram obtidas de Dechow, Sloan e Sweeny (1995) e Dechow e Dichev (2002). Houve a utilização da técnica de dados em painel dinâmico com momentos generalizados (GMM). Os resultados indicaram que as BTD Anormais são decorrentes do gerenciamento de resultados por accruals discricionários e pela diminuição na qualidade dos accruals. Com isso, concluiu-se e contribuiu-se com a literatura que há tendências de assimetria informacional nas BTD, principalmente em seus componentes discricionários, diminuindo a qualidade dos lucros.

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'GMM-EM'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles