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

Baggage scanning systems are used for detecting the presence of explosives and other prohibited items in baggage at
security checkpoints in airports. However, the CT baggage images contain projection noise and are of low resolution.
This paper introduces a new enhancement algorithm combining alpha-weighted mean separation and histogram
equalization to enhance the CT baggage images while removing the background projection noise. A new enhancement
measure is introduced for quantitative assessment of image enhancement. Simulations and a comparative analysis are
given to demonstrate the new algorithm's performance.

CT baggage image enhancement using a combination of alpha-weighted mean separation and histogram equalization

Median filters excel at removing impulse noise from digital signals, with high accuracy and quick running-times. However, they have limitations if the resulting signals are to be used for feature recognition purposes, as they often remove crucial details and add unwanted noise. In this paper, an algorithm for digital filtering using the logical transform is proposed. This method is able to achieve mean-squared-error results similar to median type filters while maintaining image details. Variations of the algorithm allow for grea ter noise reduction, but at the cost of increased computation. Keywords: impulse noise, digital filtering, Histogram of Primar y Implicants, Boolean Minimization, logical transform 1. INTRODUCTIONDigital signals can be corrupted by impulse noise (i.e. salt and pepper noise) in a variety of ways, from errors in collection sensors to noisy transmission channels to faulty storage devices. The industry standard for eliminating impulse noise is median type filters

Filtering of impulse noise in digital signals using logical transform

This paper presents a fast matched filter algorithm in time domain. Matched filters compute correlation of signals for optimal detection of signals in noise, for extracting ranging measurements, synchronisation, etc. We consider matched filters in the context of Global Positioning System (GPS) receivers, but the algorithms presented here can be used for other applications as no constraining assumptions are made in derivations. Our method outperforms conventional time domain method several times in arithmetic complexity. It is also competitive with transform domain techniques based on Fast Fourier Transform (FFT). Unlike FFT based methods our approach is accurate and is not using rounding and scaling operations.

A fast matched filter in time domain

The quantum Fourier transform (QFT) is perhaps the furthermost central building block in creation quantum algorithms. In this work, we present a new approach to compute the standard quantum Fourier transform of the length $$ N = 2^{r} , \;r > 1 $$
 , which also is called the r-qubit discrete Fourier transform. The presented algorithm is based on the paired transform developed by authors. It is shown that the signal-flow graphs of the paired algorithms could be used for calculating the quantum Fourier and Hadamard transform with the minimum number of stages. The calculation of all components of the transforms is performed by the Hadamard gates and matrices of rotations and all simple NOT gates. The new presentation allows for implementing the QFT (a) by using only the r Hadamard gates and (b) organizing parallel computation in r stages. Also, the circuits for the length-2r fast Hadamard transform are described. Several mathematical illustrative examples of the order the $$ N = 4,\;8 $$
 , and 16 cases are illustrated. Finally, the QFT for inputs being two, three and four qubits is described in detail.

Paired quantum Fourier transform with log 2 N Hadamard gates

Security images transmitted over network or wireless mediums are subjected to a variety of transmission errors and non-eccentricity pattern noise Some of these errors are due to hardware limitations that can result in lower quality images caused by quantization noise Currently, there are no quantitative metrics to evaluate the visual quality of images containing transmission errors based on human perception Traditional methods rely on human evaluators, which is not always feasible in live field security applications Image quality measures are desired to evaluate these images and to help with parameter selection in their enhancement process The performances of existing spatial domain image quality measures are sensitive to the image contents and attributes The image quality measures that operate in the transform domain such as the DCT, DFT, or DWT, are independent of image attributes such as periodicity, texture, and randomness; however, these measures are mostly contrast measures and designed to handle gray scale images Currently, there are no transform domain measures for color images that are suitable for these classes of noise and distortions In this article, we introduce a no-parameter, no-reference transform domain measure of enhancement for color images The test images are distorted with JPEG/JPEG2000 transmission errors, quantization noise, and non-eccentricity pattern noise Our measure utilizes the spectrum of the color content of images in the transform domain This measure can help optimize parameter selection during the enhancement process or to autonomously evaluate images in accordance with human visual perception

Sos S. Agaian

Papers

CT baggage image enhancement using a combination of alpha-weighted mean separation and histogram equalization

Filtering of impulse noise in digital signals using logical transform

A fast matched filter in time domain

Paired quantum Fourier transform with log 2 N Hadamard gates

Quality assessment of color images affected by transmission error, quantization noise, and noneccentricity pattern noise