Objective-Pulmonary embolism (PE) is a life-threatening manifestation of venous thromboembolism with a high recurrence rate after anticoagulation cessation. Recently, we have reported that prothrombotic clot phenotype in venous thromboembolism patients is associated with an increased risk of recurrent deep-vein thrombosis. Approach and Results-We tested whether abnormal clot properties are predictive of recurrent PE. We investigated 156 consecutive white patients aged 18 to 65 years after the first-ever provoked or unprovoked PE (n=89), with or without deep-vein thrombosis. Plasma fibrin clot permeability (K s ), turbidity measurements, calibrated automated thrombography, and efficiency of fibrinolysis using clot lysis time, maximum D-dimer levels, and rate of increase in D-dimer levels were evaluated at ≥3 months of anticoagulant therapy, at least 4 weeks since the anticoagulation withdrawal. The primary end point was recurrent PE during a median follow-up of 50 months. Recurrent PE was diagnosed in 23 (14.7%; 5%/ yr) patients. Recurrent PE was associated with formation of denser fibrin networks reflected by lower K s (P=0.007) and impaired fibrinolysis, as evidenced by prolonged clot lysis time (P=0.012) and reduced maximum rate of increase in D-dimer levels in the lysis assay (P=0.004). Patients with recurrent PE had higher plasma D-dimer (P<0.001) and thrombin peak (P=0.007) compared with the remainder, whereas turbidity measurements and maximum D-dimer levels did not differ in the recurrence. Multivariate model showed that independent predictors of recurrent PE were female sex, unprovoked venous thromboembolism, higher plasma D-dimer, reduced K s , and reduced maximum rate of increase in D-dimer levels in the lysis assay (all P<0.05).
Conclusions-Altered
Methods for estimating parameters of periodic autoregressive moving average PARMA systems when the periodic coefficients are represented by Fourier series remain to be employed in practice and still offer problem areas for future research. As pointed out by early writers on the subject, such as Hannan (1955) and Jones and Brelsford (1967), if the periodic variations are smooth within the fundamental period, as might be expected in many physical time series, a substantial reduction in the number of estimated parameters may be realized by setting many of the Fourier coefficients to be zero; this restricts the estimated solutions to a subspace. The identification problem becomes the determination of lags and frequencies with significant amplitudes. While progress has been made in this area, improvements and new methods are needed. In reviewing the development of Fourier-PARMA methods, we naturally view many of the main advances in PARMA time series analysis under the usual parameterization. Two simulations are presented that demonstrate further potential and open problems associated with the Fourier methods.
Because making digital images secure runs into the substantial challenge of owner authentication, many security schemes based on cryptography, steganography and watermarking technology include biometric recognition methods. To follow on these studies, this paper describes a combination of facial images with watermarking technology to automatically authenticate digital images owners/users. In the proposed methodology, biometric face recognition methods such as principal component analysis and eigenfeature regularization and extraction produce vectorial representations of facial images. These vectors are used as copyright watermarks, in a few common watermarking schemes, and are tested for identification purposes after they are extracted. Initially, watermarking algorithms are studied with some arbitrary cover image, and also the most robust algorithm is tested for different cover images of particular subjects. The strength of this paper is finding relationships between the original and extracted biometric data using neural networks instead of the most common, simple measures such as correlation coefficients or distance metrics. The NN subject identification is performed directly, as there is no need to reconstruct facial images after the watermarks are extracted, compute templates for particular subjects, or seek a suitable distance metric. What is more, the presented study includes a performance comparison of two machine learning methods, frequently used for face recognition, and of a few popular watermarking algorithms. Very promising identification results were obtained in many considered experiments, even those involving attacks on watermarked images. and watermarking [7,[15][16][17][18] are provided, because they now represent mainstream security technologies. This paper proposes a security model enabling the authentication of digital image owners using the watermarking
This paper provides a preliminary investigation on digital watermarking as an effective technology to protect property rights and limit distribution of multimedia data. First, crucial properties and design requirements of watermarking schemes are discussed. Then, as watermarking techniques finds many applications in healthcare industry, aspects of medical image watermarking are raised. Nowadays, the transmission of digitized medical information has become very easy due to the generality of Internet. However, the digital form of these images can easily be manipulated and degraded. This causes problems of medical security and copyright protection and poses a great challenge to privacy protection using watermarking techniques.
This paper gives a general introduction to the digital watermarking procedures and their security aspects. The first issue is to clarify unifying and differentiating properties of steganography and watermarking. Then the most important aspects of digital watermarking are reviewed by studying application, requirement and design problems. We put emphasis on the importance of digital watermark as an effective technology to protect intellectual property rights and legitimate use of digital images. In the paper we provide an overview of the most popular digital watermarking methods for still images available today. The watermarking algorithms are divided into two major categories of spatial and transform domains. Because of outstanding robustness and imperceptibility the transform domain algorithms are the mainstream of research. Popular transforms of images include the DFT
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