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

Over the past several years there has been an apparent shift in research focus in the area of digital steganography and
steganalysis - a shift from primarily image based methods to a new focus on broader multimedia techniques. More
specifically the area of digital audio steganography is of prime interest. We introduce a new high capacity, covert
channel data embedding and recovery system for digital audio carrier files using a key based encoding and decoding
method. It will be shown that the added information file is interleaved within the carrier file and is fully indexed
allowing for segmented extraction and recovery of data at chosen start and stop points in the sampled stream. The
original audio quality is not affected by the addition of this covert data. The embedded information can also be secured
by a binary key string or cryptographic algorithm and resists statistical analytic detection attempts. We will also
describe how this new method can be used for data compression and expansion applications in the transfer and storage of
digital multimedia to increase the overall data capacity and security.

System for non-disruptive high-capacity indexed data embedding and recovery using multimedia signal covers

In this paper, we propose a new algorithm based on Fourier spectral characteristics. This technique improves the coding prediction accuracy, boosting the protein coding region and suppressing the non-coding region within the DNA sequences. We also compare this algorithm using computer simulation with commonly used techniques showing that our technique for exon region prediction provides superior properties for the separation of exon and intron regions.

Prediction of coding region in the DNA sequences

The objects in the medical images are not visible due to low contrast and the noise. In general, X-ray, computed tomography (CT), and magnetic resonance imaging (MRI) images are often affected by blurriness, lack of contrast, which are very important for the accuracy of medical diagnosis. It is difficult to segmentation in such case without losing the details of the objects. The goal of image enhancement is to improve certain details of an image and to improve its visual quality. So, image enhancement technology is one of the key procedures in image segmentation for medical imaging. This article presents a two-stage approach, combining novel and traditional algorithms, for the enhancement and segmentation of images of bones obtained from CT. The first stage is a new combined local and global transform domain-based image enhancement algorithm. The basic idea of using local alfa-rooting method is to apply it to different disjoint blocks of different sizes. We used image enhancement non-reference quality measure for optimization alfa-rooting parameters. The second stage applies the modified active contour method based on an anisotropic gradient. The simulation results of the proposed algorithm are compared with other state-of-the-art segmentation methods, and its superiority in the presence of noise and blurred edges on the database of CT images is illustrated.

Medical image segmentation by combing the local, global enhancement, and active contour model

Thermography is an imaging technique which is based on the idea that the temperature rises in regions with increased blood flow and metabolism, which could be a sign of a tumor. Recently, it has found promising applications in cancer diagnosis, particularly, in breast cancer exposure. Even though many thermo-medical applications need a good image assessment tool, there were no reports in literature on using a thermal image as a thermal conditioning of breast cancer progress/treatment. In this paper, a novel thermal images assessment tool for detecting the conditions of breast cancer exposure based on thermography is proposed. The presented innovative measure is based on integration of human visual system, intensity and density attributes of observed images. The proposed scheme as thermal conditions of breast cancer has the advantages of: (i) determining cancer risks for prevention by introducing a measuring system for estrogen imbalance, (ii) detecting the progress and treatment by monitoring the conditions as a new measurements and (iii) breast skin temperature measurement. The experiments show the effectiveness of the proposed measuring system on thermal conditions of breast cancer.

Thermal conditions of breast cancer progress-treatment

In the modern world, the use of visual information is ubiquitous. Small-sized data analysis devices have found application in almost all areas, including security systems, industrial production, gaming, car control, etc. To increase the accuracy, fault tolerance, and decision-making speed, combined information data fields are used as input data. The article developed an approach to combining data obtained in different ranges into a single image. To improve the alignment accuracy, the paper proposes using a group of methods for the primary processing of image enhancement. The article proposes finding anchor points for a series of images used for their subsequent merging. An algorithm for calibrating a system of several cameras is presented, a description of the influence of parameters on the result of combining is given. To increase the processing speed and the selection of the processing methods' primary parameters, it is proposed to change the bitness of the image by simplifying them. The operation includes absorbing small objects and averaging the ranges of histograms of color gradients. As test data, a series of images of one object obtained in: visible (camera with a resolution of 1920 x 1080 pixels, color depth of 8 bits); far-infrared (thermal imaging images with a resolution of 320x240 pixels, grayscale); 3D model (construction is carried out based on a stereo pair with a resolution of 1024x768 pixels).

Sos S. Agaian

Papers

System for non-disruptive high-capacity indexed data embedding and recovery using multimedia signal covers

Prediction of coding region in the DNA sequences

Medical image segmentation by combing the local, global enhancement, and active contour model

Thermal conditions of breast cancer progress-treatment

Algorithm for fusing data obtained by thermal, 3D, and the visible range cameras