Data-based Scheme Research Articles

A secure and robust digital signature scheme for JPEG2000 image authentication

In this paper, we present a secure and robust content-based digital signature scheme for verifying the authenticity of JPEG2000 images quantitatively, in terms of a unique concept named lowest authenticable bit rates (LABR). Given a LABR, the authenticity of the watermarked JPEG2000 image will be protected as long as its final transcoded bit rate is not less than the LABR. The whole scheme, which is extended from the crypto data-based digital signature scheme, mainly comprises signature generation/verification, error correction coding (ECC) and watermark embedding/extracting. The invariant features, which are generated from fractionalized bit planes during the procedure of embedded block coding with optimized truncation in JPEG2000, are coded and signed by the sender's private key to generate one crypto signature (hundreds of bits only) per image, regardless of the image size. ECC is employed to tame the perturbations of extracted features caused by processes such as transcoding. Watermarking only serves to store the check information of ECC. The proposed solution can be efficiently incorporated into the JPEG2000 codec (Part 1) and is also compatible with Public Key Infrastructure. After detailing the proposed solution, system performance on security as well as robustness will be evaluated.

Oxford Textbook of Psychopathology

Back to table of contents Previous article Next article Book Forum: TextbooksFull AccessOxford Textbook of PsychopathologyRICHARD LEWINE, PH.D., RICHARD LEWINESearch for more papers by this author, PH.D., Atlanta, Ga.Published Online:1 Feb 2002https://doi.org/10.1176/appi.ajp.159.2.329-aAboutSectionsView EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail I read this textbook cover to cover with the same reaction I had to my first exposure to Aaron Copland and to Snoop Dogg: cacophonous confusion and mild mental pain. As is true for Copland and Snoop Dogg, however, a willingness to work at finding their structure and meaning, and even their “music,” is well worth the effort. At first blush, this comprehensive textbook, which covers both axis I and axis II disorders, is typical of edited books in its collection of seemingly self-contained reviews. The chapters are of uneven quality, there is considerable redundancy from chapter to chapter, and by the conclusion the reader is left wondering what exactly is known about psychopathology. Despite these shortcomings, the three chapters by Raulin and Lilienfeld, Pihl, and Lenzenweger, respectively, are in themselves worth the price of the book. These scholars elegantly and comprehensively manage to highlight significant conceptual issues that should help even the seasoned researcher think more clearly about psychopathology. At worst, therefore, the Oxford Textbook of Psychopathology brings together an impressive summary of psychopathology research data and sophisticated discussions of methodological and conceptual issues.What is lacking, and in this the Oxford Textbook of Psychopathology is not unique, is the “big picture.” What is the theme, the tune if you will? In self-consciously denouncing (analytic) theory and shifting to a data-based diagnostic scheme (the various DSMs), psychiatry lost its theoretical nerve. In its place is a fragmented collection of disorders that appears to be categorical in nature on superficial reading. The authors of the Oxford Textbook of Psychopathology, the vast majority of whom are psychologists, follow the structure of DSM-IV nomenclature. Having gone through its own antitheoretical period (“dustbowl empiricism,” “black box” behaviorism), however, psychology is more at ease with complex models and theories, a smattering of which can be found throughout this volume. At the very least, the Oxford Textbook of Psychopathology suggests that we have sufficient data to begin the arduous task of making sense of them.The real value in this book will yield only to multiple readings to ferret out the cross-chapter commonalities that point to unifying themes and perhaps theory. This will be the first assignment I give my next psychopathology student. Consider, for example, that childhood trauma has been associated with eating disorders, depression, substance abuse, and dissociative disorders, among others. Or that “co-morbidity” (or, more correctly, “co-occurrence,” as pointed out by Lenzenweger in the text and by Lilienfeld in an earlier article) links mood disturbance and substance abuse with numerous other disorders, indeed almost everything else. Or that the “biopsychosocial” model (the diathesis-stress variant being the most common) is invoked in virtually all disorders. Or that perinatal brain injury has been associated with disorders as disparate as schizophrenia and eating disorders. Or that “hypofrontality” has been invoked as a possible explanatory construct for both schizophrenia and depressive personality disorder. The diligent and persistent scholar will find in this one volume the raw material for an exercise that could stimulate a return to unifying theoretical speculation.We should confuse neither data with information nor information with understanding. Perhaps most importantly, we should confuse volume with neither productivity nor quality. There is much in the Oxford Textbook of Psychopathology that is of enviable quality. However, the voluminous text is also a reflection of a broader cultural struggle: trying to do too much too quickly. I was so struck by what I assume are typographical errors that, beginning on page 291, I kept track of them. In the 305 pages of text (excluding references) that followed, there was at least one typo on 47 pages (15.4%). Why make a point of this? Because the same environment that allows such an error rate will be the primary obstacle to the understanding needed in the field of psychopathology. We need to slow down, attend, reread, and think. Only then will we generate the quality of scholarship necessary to meet the challenges of modern psychopathology. Buy the book, read it, then read it again and let me know what you discover.Edited by Theodore Millon, Paul H. Blaney, and Roger D. Davis. New York, Oxford University Press, 1999, 732 pp., $85.00. FiguresReferencesCited byDetailsCited ByNone Volume 159Issue 2 February 2002Pages 329-a-330 Metrics History Published online 1 February 2002 Published in print 1 February 2002

Optimal sampling interval for system identification based on decimation and interpolation

To improve the mean square error (MSE) of the least squares (LS) estimate of an impulse response, a new approach to signal sampling and measurement is proposed, based on decimation and interpolation. It is analytically shown that there exists an optimal sampling interval which can minimise the MSE, and this optimal sampling interval depends on the impulse response, the input power spectrum or the eigenvalues' distribution of the correlation matrix of the input signal, the noise variance and the total number of data. Furthermore, an effective data-based scheme to determine the optimal sampling interval is given by using the only accessible input-output data. The effectiveness of the presented algorithm is demonstrated through numerical examples.

Optimal Sampling Rate for System Identification Based on Decimation and Interpolation

This paper clarifies that adequate decimation of high-rate sampled input-output data can give much improvement on the MSE of the least squares estimate of an impulse response. In order to reconstruct the impulse response estimate with the original sampling rate, we employ an interpolation scheme with the same factor of the decimation. We will show that there exists an optimal sampling rate for the least squares estimation, which minimizes the MSE that depends on the impulse response itself, the input power spectrum or the distribution of the eigenvalues of input correlation matrix, the noise variance and the total number of data. Furthermore, we give an effective data-based scheme for deciding the decimation and interpolation rate using the accessible input-output data.

A data-based scheme for evaluating faculty performance

Both sound management practice and the law require that administrative decisions affecting faculty members reflect systematic, uniformly applied, fair, and valid evaluations of performance. To meet these requirements a performance evaluation scheme must involve two decision elements, both of which are addressed and illustrated in this paper:what will be evaluated, andhow the evaluation will be made. A data-based faculty performance evaluation program specifically oriented toward such administrative actions as tenure, promotion, and salary adjustment is described. This program rests upon task analysis to clarify the nature of the desired evaluative content and peer review as the primary evaluative mechanism. The scheme is illustrated using the experience of a department of psychology training to the doctorate. However, the approach to faculty performance evaluation herein described and illustrated is generalizable, with modification, to other departments and institutions. Several considerations pertinent to such modification are discussed.