There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

The 11th edition of Harrison's Principles of Internal Medicine welcomes Anthony Fauci to its editorial staff, in addition to more than 85 new contributors. While the organization of the book is similar to previous editions, major emphasis has been placed on disorders that affect multiple organ systems. Important advances in genetics, immunology, and oncology are emphasized. Many chapters of the book have been rewritten and describe major advances in internal medicine. Subjects that received only a paragraph or two of attention in previous editions are now covered in entire chapters. Among the chapters that have been extensively revised are the chapters on infections in the compromised host, on skin rashes in infections, on many of the viral infections, including cytomegalovirus and Epstein-Barr virus, on sexually transmitted diseases, on diabetes mellitus, on disorders of bone and mineral metabolism, and on lymphadenopathy and splenomegaly. The major revisions in these chapters and many

Harrison's Principles of Internal Medicine

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

We explore the effect of dimensionality on the nearest neighbor problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never meaningful; we illustrate this point by identifying some high-dimensional workloads for which this effect does not occur. However, our results do emphasize that the methodology used almost universally in the database literature to evaluate high-dimensional indexing techniques is flawed, and should be modified. In particular, most such techniques proposed in the literature are not evaluated versus simple linear scan, and are evaluated over workloads for which nearest neighbor is not meaningful. Often, even the reported experiments, when analyzed carefully, show that linear scan would outperform the techniques being proposed on the workloads studied in high (10-15) dimensionality!.

When is nearest neighbor meaningful

Image enhancement performance is currently judged subjectively, with no reliable manner of quantifying the results of an enhancement. Current quantitative measures rely on linear algorithms to determine contrast, leaving room for improvement. With the introduction of more complex enhancement algorithms, there is a need for an effective method of quantifying performance to select optimal parameters. In this paper, we present a logarithmic based image enhancement measure. We demonstrate its performance on real world images. The results will show the effectiveness of our measures to select optimal enhancement parameters for the enhancement algorithms.

A logarithmic measure of image enhancement

Decompositional methods for stack filtering using Fibonacci p -codes

Because of high sensitivity for initial values and random-like behaviors, chaotic systems are widely used in image encryption. Conventionally, encryption keys for these image encryption methods based chaotic systems are limited to manipulate the initial values or parameters of the chaotic system. However, effective attacks are found to crack encryption systems by using prior information about the system chaotic map. In this paper, we introduce a wheel-switch chaotic system for image encryption. The used chaotic map is not fixed but changeable via the wheel-switch structure according to the controlling sequence. Further, a substitution and permutation network based image encryption algorithm using the wheel-switch chaotic system is also provided. Experimental results showed that the proposed system with the key schedule inherits the random-like property of single chaotic system with additional security level from the wheel-switch structure. The same idea is also applicable to secure communication, and data encryption for other multimedia.

A wheel-switch chaotic system for image encryption

Performance measures of image enhancement are traditionally subjective and have difficulty quantifying the improvement made by the algorithm. In this paper, we present the image enhancement measures and show how utilizing logarithmic arithmetic based addition, subtraction, and multiplication provides better results than previously used measures. In addition, for illustration of the performance of developed measures, we present a comprehensive study of several image enhancement algorithms from all three domains, including spatial, transform, and logarithmic algorithms.

Comparative study of logarithmic enhancement algorithms with performance measure

The detection of threat objects using X-ray luggage scan images has become an important means of aviation security. Most airport screening is still based on the manual detection of potential threat objects by human experts. This paper presents a system for the automatic detection of potential threat objects in X-ray luggage scan images. Segmentation and edge-based feature vectors form the basis of the automatic detection system. The system is illustrated using handguns as the threat objects in question. The experimental results show that the system can effectively detect the handguns in X-ray luggage scan images with minimal amounts of false positives. Also, apart from the initial setup of the classification database, the algorithm is suitable for real-time applications.

Sos S. Agaian

Papers

A logarithmic measure of image enhancement

Decompositional methods for stack filtering using Fibonacci p -codes

A wheel-switch chaotic system for image encryption

Comparative study of logarithmic enhancement algorithms with performance measure

Automatic Detection of Potential Threat Objects in X-ray Luggage Scan Images