Face Recognition Method Based on Fuzzy 2DPCA

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Xiaodong Li

2014-01-01

Full Text Available 2DPCA, which is one of the most important face recognition methods, is relatively sensitive to substantial variations in light direction, face pose, and facial expression. In order to improve the recognition performance of the traditional 2DPCA, a new 2DPCA algorithm based on the fuzzy theory is proposed in this paper, namely, the fuzzy 2DPCA (F2DPCA. In this method, applying fuzzy K-nearest neighbor (FKNN, the membership degree matrix of the training samples is calculated, which is used to get the fuzzy means of each class. The average of fuzzy means is then incorporated into the definition of the general scatter matrix with anticipation that it can improve classification result. The comprehensive experiments on the ORL, the YALE, and the FERET face database show that the proposed method can improve the classification rates and reduce the sensitivity to variations between face images caused by changes in illumination, face expression, and face pose.

SAR Ground Moving Target Indication Based on Relative Residue of DPCA Processing

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Jia Xu

2016-10-01

Full Text Available For modern synthetic aperture radar (SAR, it has much more urgent demands on ground moving target indication (GMTI, which includes not only the point moving targets like cars, truck or tanks but also the distributed moving targets like river or ocean surfaces. Among the existing GMTI methods, displaced phase center antenna (DPCA can effectively cancel the strong ground clutter and has been widely used. However, its detection performance is closely related to the target’s signal-to-clutter ratio (SCR as well as radial velocity, and it cannot effectively detect the weak large-sized river surfaces in strong ground clutter due to their low SCR caused by specular scattering. This paper proposes a novel method called relative residue of DPCA (RR-DPCA, which jointly utilizes the DPCA cancellation outputs and the multi-look images to improve the detection performance of weak river surfaces. Furthermore, based on the statistics analysis of the RR-DPCA outputs on the homogenous background, the cell average (CA method can be well applied for subsequent constant false alarm rate (CFAR detection. The proposed RR-DPCA method can well detect the point moving targets and distributed moving targets simultaneously. Finally, the results of both simulated and real data are provided to demonstrate the effectiveness of the proposed SAR/GMTI method.

Object Tracking via 2DPCA and l2-Regularization

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Haijun Wang

2016-01-01

Full Text Available We present a fast and robust object tracking algorithm by using 2DPCA and l2-regularization in a Bayesian inference framework. Firstly, we model the challenging appearance of the tracked object using 2DPCA bases, which exploit the strength of subspace representation. Secondly, we adopt the l2-regularization to solve the proposed presentation model and remove the trivial templates from the sparse tracking method which can provide a more fast tracking performance. Finally, we present a novel likelihood function that considers the reconstruction error, which is concluded from the orthogonal left-projection matrix and the orthogonal right-projection matrix. Experimental results on several challenging image sequences demonstrate that the proposed method can achieve more favorable performance against state-of-the-art tracking algorithms.

Existing data sources for clinical epidemiology: the Danish Patient Compensation Association database.

Science.gov (United States)

Tilma, Jens; Nørgaard, Mette; Mikkelsen, Kim Lyngby; Johnsen, Søren Paaske

2015-01-01

Any patient in the Danish health care system who experiences a treatment injury can make a compensation claim to the Danish Patient Compensation Association (DPCA) free of charge. The aim of this paper is to describe the DPCA database as a source of data for epidemiological research. Data to DPCA are collected prospectively on all claims and include information on patient factors and health records, system factors, and administrative data. Approval of claims is based on injury due to the principle of treatment below experienced specialist standard or intolerable, unexpected extensiveness of injury. Average processing time of a compensation claim is 6-8 months. Data collection is nationwide and started in 1992. The patient's central registration system number, a unique personal identifier, allows for data linkage to other registries such as the Danish National Patient Registry. The DPCA data are accessible for research following data usage permission and make it possible to analyze all claims or specific subgroups to identify predictors, outcomes, etc. DPCA data have until now been used only in few studies but could be a useful data source in future studies of health care-related injuries.

Enhanced dynamic data-driven fault detection approach: Application to a two-tank heater system

KAUST Repository

Harrou, Fouzi

2018-02-12

Principal components analysis (PCA) has been intensively studied and used in monitoring industrial systems. However, data generated from chemical processes are usually correlated in time due to process dynamics, which makes the fault detection based on PCA approach a challenging task. Accounting for the dynamic nature of data can also reflect the performance of the designed fault detection approaches. In PCA-based methods, this dynamic characteristic of the data can be accounted for by using dynamic PCA (DPCA), in which lagged variables are used in the PCA model to capture the time evolution of the process. This paper presents a new approach that combines the DPCA to account for autocorrelation in data and generalized likelihood ratio (GLR) test to detect faults. A DPCA model is applied to perform dimension reduction while appropriately considering the temporal relationships in the data. Specifically, the proposed approach uses the DPCA to generate residuals, and then apply GLR test to reveal any abnormality. The performances of the proposed method are evaluated through a continuous stirred tank heater system.

Existing data sources for clinical epidemiology: the Danish Patient Compensation Association database

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Tilma J

2015-07-01

Full Text Available Jens Tilma,1 Mette Nørgaard,1 Kim Lyngby Mikkelsen,2 Søren Paaske Johnsen1 1Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, 2Danish Patient Compensation Association, Copenhagen, Denmark Abstract: Any patient in the Danish health care system who experiences a treatment injury can make a compensation claim to the Danish Patient Compensation Association (DPCA free of charge. The aim of this paper is to describe the DPCA database as a source of data for epidemiological research. Data to DPCA are collected prospectively on all claims and include information on patient factors and health records, system factors, and administrative data. Approval of claims is based on injury due to the principle of treatment below experienced specialist standard or intolerable, unexpected extensiveness of injury. Average processing time of a compensation claim is 6–8 months. Data collection is nationwide and started in 1992. The patient's central registration system number, a unique personal identifier, allows for data linkage to other registries such as the Danish National Patient Registry. The DPCA data are accessible for research following data usage permission and make it possible to analyze all claims or specific subgroups to identify predictors, outcomes, etc. DPCA data have until now been used only in few studies but could be a useful data source in future studies of health care-related injuries. Keywords: public health care, treatment injuries, no-fault compensation, registries, research, Denmark

Systolically gated 3D phase contrast MRA of mesenteric arteries in suspected mesenteric ischemia

Energy Technology Data Exchange (ETDEWEB)

Wasser, M.N.; Schultze Kool, L.J.; Roos, A. de [Leiden Univ. Hospital (Netherlands)] [and others

1996-03-01

Our goal was to assess the value of MRA for detecting stenoses in the celiac (CA) and superior mesenteric (SMA) arteries in patients suspected of having chronic mesenteric ischemia, using an optimized systolically gated 3D phase contrast technique. In an initial study in 24 patients who underwent conventional angiography of the abdominal vessels for different clinical indications, a 3D phase contrast MRA technique (3D-PCA) was evaluated and optimized to image the CAs and SMAs. Subsequently, a prospective study was performed to assess the value of systolically gated 3D-PCA in evaluation of the mesenteric arteries in 10 patients with signs and symptoms of chronic mesenteric ischemia. Intraarterial digital subtraction angiography and surgical findings were used as the reference standard. In the initial study, systolic gating appeared to be essential in imaging the SMA on 3D-PCA. In 10 patients suspected of mesenteric ischemia, systolically gated 3D-PCA identified significant proximal disease in the two mesenteric vessels in 4 patients. These patients underwent successful reconstruction of their stenotic vessels. Cardiac-gated MRA may become a useful tool in selection of patients suspected of having mesenteric ischemia who may benefit from surgery. 16 refs., 6 figs., 4 tabs.

Demixed principal component analysis of neural population data.

Science.gov (United States)

Kobak, Dmitry; Brendel, Wieland; Constantinidis, Christos; Feierstein, Claudia E; Kepecs, Adam; Mainen, Zachary F; Qi, Xue-Lian; Romo, Ranulfo; Uchida, Naoshige; Machens, Christian K

2016-04-12

Neurons in higher cortical areas, such as the prefrontal cortex, are often tuned to a variety of sensory and motor variables, and are therefore said to display mixed selectivity. This complexity of single neuron responses can obscure what information these areas represent and how it is represented. Here we demonstrate the advantages of a new dimensionality reduction technique, demixed principal component analysis (dPCA), that decomposes population activity into a few components. In addition to systematically capturing the majority of the variance of the data, dPCA also exposes the dependence of the neural representation on task parameters such as stimuli, decisions, or rewards. To illustrate our method we reanalyze population data from four datasets comprising different species, different cortical areas and different experimental tasks. In each case, dPCA provides a concise way of visualizing the data that summarizes the task-dependent features of the population response in a single figure.

Peritonitis fúngica en diálisis peritoneal continua ambulatoria: descripción de 10 casos

OpenAIRE

García Martos, P.; Gil de Sola, F.; Marín, P.; García-Agudo, L.; García-Agudo, R.; Tejuca, F.; Calle, L.

2009-01-01

Antecedentes: La peritonitis fúngica es una complicación infrecuente pero grave en pacientes en diálisis peritoneal continua ambulatoria (DPCA). Métodos: Durante un período de 10 años (1999-2008), de un total de 175 pacientes con insuficiencia renal crónica en tratamiento con DPCA, estudiamos retrospectivamente 10 casos de peritonitis fúngica, analizando los factores predisponentes, aspectos clínicos, agentes etiológicos y tratamiento. El diagnóstico se estableció por la presencia de efluente...

Desajuste psicológico, calidad de vida y afrontamiento en pacientes diabéticos con insuficiencia renal crónica en diálisis peritoneal

OpenAIRE

Rivera-Ledesma, Armando; Montero-López Lena, María; Sandoval-Ávila, Rosalba

2012-01-01

Se ha reportado que el impacto del procedimiento de diálisis peritoneal continua ambulatoria (DPCA) en la calidad de vida del paciente suele presentar profundas consecuencias psicosociales para él y su familia; dicha sustitución de la función renal promueve la supervivencia pero no un completo bienestar físico, emocional y social. Estos últimos aspectos pueden ser determinantes para el éxito del tratamiento con DPCA por su influencia positiva o negativa en la adherencia del paciente al mismo....

Power Allocation in Multiple Access Networks: Implementation Aspects via Verhulst and Perron-Frobenius Models

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Fábio Engel de Camargo

2012-11-01

Full Text Available In this work, the Verhulst model and the Perron-Frobenius theorem are applied on the power control problem which is a concern in multiple access communication networks due to the multiple access interference. This paper deals with the performance versus complexity tradeoff of both power control algorithm (PCA, as well as highlights the computational cost aspects regarding the implementability of distributed PCA (DPCA version for both algorithms. As a proof-of-concept the DPCA implementation is carried out deploying a commercial point-floating DSP platform. Numerical results in terms of DSP cycles and computational time as well indicate a feasibility of implementing the PCA-Verhulst model in 2G and 3G cellular systems; b high computational cost for the PCA-Perron-Frobenius model.

Costo-efectividad de intervenciones para insuficiencia renal crónica terminal

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Armando Arredondo

1998-12-01

Full Text Available OBJETIVO: Analisó el costo-efectividad en intervenciones para pacientes con insuficiencia renal crónica terminal (IRCT en términos de los costos económicos de cada intervención, los años de vida ganados y la calidad de vida que generan tres alternativas comparables y mutuamente excluyentes: diálisis peritoneal contínua ambulatoria (DPCA, la hemodiálisis (HD y el trasplante renal (TR. MÉTODO: El diseño del estudio fue de tipo longitudinal. Los costos de cada intervención se determinaron mediante la técnica de manejo de caso promedio. Las medidas para evaluar los criterios de efectividad elegidos fueron la probabilidad de sobrevida y el Año de Vida Ajustado por Calidad (QALY, Quality Adjusted Life Year medido por el Indice de Rosser. RSULTADOS: Los costos de manejo anual de caso fueron: diálisis peritoneal $5,643.07, hemodiálisis $9,631.60 y trasplante $3,021.63. En cuanto a la efectividad, la sobrevida del injerto de trasplante renal resultó de 89,9% y 79,6% a uno y tres años respectivamente, mientras que los pacientes sometidos a DPCA tienen una sobrevida de 86,2% y 66,9% a un año y a tres años respectivamente. En cuanto a los QALY's, los resultados para cada intervención fueron: DPCA 0,879; HD 0,864; y para el TR 0,978. CONCLUSIÓN: La intervención más costo-efectiva resultó el trasplante renal con un coeficiente de 3,088.69, seguido de la DPCA y la hemodiálisis, cuyos coeficientes fueron de 6,416.95 y 11,147.68 respectivamente. Por lo tanto se recomienda promover y utilizar el trasplante renal como la intervención más costo-efectiva para pacientes con IRCT.

On the structure of dynamic principal component analysis used in statistical process monitoring

DEFF Research Database (Denmark)

Vanhatalo, Erik; Kulahci, Murat; Bergquist, Bjarne

2017-01-01

When principal component analysis (PCA) is used for statistical process monitoring it relies on the assumption that data are time independent. However, industrial data will often exhibit serial correlation. Dynamic PCA (DPCA) has been suggested as a remedy for high-dimensional and time...... for determining the number of principal components to retain. The number of retained principal components is determined by visual inspection of the serial correlation in the squared prediction error statistic, Q (SPE), together with the cumulative explained variance of the model. The methods are illustrated using...... driven method to determine the maximum number of lags in DPCA with a foundation in multivariate time series analysis. The method is based on the behavior of the eigenvalues of the lagged autocorrelation and partial autocorrelation matrices. Given a specific lag structure we also propose a method...

Average Gait Differential Image Based Human Recognition

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Jinyan Chen

2014-01-01

Full Text Available The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI, AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition.

Power Grid Modelling From Wind Turbine Perspective Using Principal Componenet Analysis

DEFF Research Database (Denmark)

Farajzadehbibalan, Saber; Ramezani, Mohammad Hossein; Nielsen, Peter

2015-01-01

In this study, we derive an eigenvector-based multivariate model of a power grid from the wind farm's standpoint using dynamic principal component analysis (DPCA). The main advantages of our model over previously developed models are being more realistic and having low complexity. We show that th...

Transient inhibition of connective tissue infiltration and collagen deposition into porous poly(lactic-co-glycolic acid) discs.

Science.gov (United States)

Love, Ryan J; Jones, Kim S

2013-12-01

Connective tissue rapidly proliferates on and around biomaterials implanted in vivo, which impairs the function of the engineered tissues, biosensors, and devices. Glucocorticoids can be utilized to suppress tissue ingrowth, but can only be used for a limited time because they nonselectively arrest cell proliferation in the local environment. The present study examined use of a prolyl-4-hydroxylase inhibitor, 1,4-dihydrophenonthrolin-4-one-3-carboxylic acid (1,4-DPCA), to suppress connective tissue ingrowth in porous PLGA discs implanted in the peritoneal cavity for 28 days. The prolyl-4-hydroxylase inhibitor was found to be effective at inhibiting collagen deposition within and on the outer surface of the disc, and also limited connective tissue ingrowth, but not to the extent of glucocorticoid inhibition. Finally, it was discovered that 1,4-DPCA suppressed Scavenger Receptor A expression on a macrophage-like cell culture, which may account for the drug's ability to limit connective tissue ingrowth in vivo. Copyright © 2013 Wiley Periodicals, Inc., a Wiley Company.

Verhulst populational model applied to distributed power control in DS/CDMA

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Paul Jean Etienne Jeszensky

2005-02-01

Full Text Available In this paper the continuous dynamic model of Verhulst is used. It had been initially elaborated to describe the population growth of biological species with food restriction and physical space, in order to synthesize a new distributed power control algorithm (DPCA, applicable in direct sequence code division multiple access (DS-CDMA systems. The discretization of the corresponding differential equation is accomplished via numeric integration Euler method (NIE. The properties of the proposed recursive algorithm, as Euclidian distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE, average power consumption per user and implementation complexity, are investigated through simulations. The simulation results are confronted with the other DPCAs: the classic algorithm derived by Foschini and Miljanic and the sigmoidal by Uykan and Koivo. With estimate errors, the proposed DPCA showed smaller discrepancy from the optimum power vector allocation after convergence and better convergence. Additionally, the Gerchgorin Circles theory (GC is applied for the feasibility of the power allocation problem.

Personal authentication through dorsal hand vein patterns

Science.gov (United States)

Hsu, Chih-Bin; Hao, Shu-Sheng; Lee, Jen-Chun

2011-08-01

Biometric identification is an emerging technology that can solve security problems in our networked society. A reliable and robust personal verification approach using dorsal hand vein patterns is proposed in this paper. The characteristic of the approach needs less computational and memory requirements and has a higher recognition accuracy. In our work, the near-infrared charge-coupled device (CCD) camera is adopted as an input device for capturing dorsal hand vein images, it has the advantages of the low-cost and noncontact imaging. In the proposed approach, two finger-peaks are automatically selected as the datum points to define the region of interest (ROI) in the dorsal hand vein images. The modified two-directional two-dimensional principal component analysis, which performs an alternate two-dimensional PCA (2DPCA) in the column direction of images in the 2DPCA subspace, is proposed to exploit the correlation of vein features inside the ROI between images. The major advantage of the proposed method is that it requires fewer coefficients for efficient dorsal hand vein image representation and recognition. The experimental results on our large dorsal hand vein database show that the presented schema achieves promising performance (false reject rate: 0.97% and false acceptance rate: 0.05%) and is feasible for dorsal hand vein recognition.

Decision time horizon for music genre classification using short time features

DEFF Research Database (Denmark)

Ahrendt, Peter; Meng, Anders; Larsen, Jan

2004-01-01

In this paper music genre classification has been explored with special emphasis on the decision time horizon and ranking of tapped-delay-line short-time features. Late information fusion as e.g. majority voting is compared with techniques of early information fusion such as dynamic PCA (DPCA......). The most frequently suggested features in the literature were employed including mel-frequency cepstral coefficients (MFCC), linear prediction coefficients (LPC), zero-crossing rate (ZCR), and MPEG-7 features. To rank the importance of the short time features consensus sensitivity analysis is applied...

Detecting Ionospheric Precursors of a Deep Earthquake (378.8 km on 7 July 2013, M w=7.2, in Papua New Guinea under a Geomagnetic Storm: Two-Dimensional Principal Component Analysis

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Jyh-Woei Lin

2013-07-01

Full Text Available Two-dimensional ionospheric total electron content (TEC data were collected during the time period from 00:00 on 2 July to 12:00 UT on 08 July 2013. This period spanned 5 days before to 1 day after a deep earthquake (378.8 km in Papua New Guinea at 18:35:30 on 7 July 2013 UT (Mw=7.2. Data were examined by two-dimensional principal component analysis (2DPCA to detect TEC precursors related to the earthquake because TEC precursors have usually appeared in earlier time periods (Liu et al. 2006. A TEC precursor was highly localized around the epicenter on 6 July for 5 minutes, from 06:00 to 06:05. Ionizing radiation from radon gas release could possibly have caused the anomalous TEC fluctuation through, for example, a density variance. The plasma might have experienced large damping to cause short-term TEC fluctuations, and the gas released in a small amount in a short time period. 2DPCA can also identify short-term TEC fluctuations, but this fluctuation lasted for a considerable length of time. Other background TEC anomalies caused by the geomagnetic storm, small earthquakes and non-earthquake activities, e.g., equatorial ionization anomaly (EIA, resulted in small principal eigenvalues. Therefore, the detection of TEC precursors through large eigenvalues was not due to these background TEC anomalies.  Resumen Datos del contenido total de electrones ionosféricos en dos dimensiones (TEC fueron medidos durante el período del 2 de julio de 2013, a las 0:00:00 horas GMT., hasta las 12:00 GMT. del 8 de julio. En este lapso se abarcan cinco días antes y un día después de un terremoto profundo (378,8 kilómetros en Papúa Nueva Guinea, que se presentó a las 18:35:30 del 7 de julio (M w =7.2. Los datos fueron examina- dos a través de los componentes principales en dos dimensiones (2DPCA para detectar los precursores TEC relacionados al terremoto (Liu et al. 2006. Un precursor de los TEC fue localizado alrededor del epicentro el 6 de julio durante 5