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

Machine vision systems used in modern industrial complexes, based on the analysis of multi and hyperspectral imaging. The transition to implementing the "Industry 4.0" program is not possible when using one type of data. The first control system used only the visible range image. They made it possible to analyze the trajectories of movement of objects, control product quality, carry out security functions (control of perimeter crossing), etc. The development of new industrial robotic cells and processing complexes using cognitive functions implying the receipt, analysis, and processing of heterogeneous data. The construction of a unified information field, which allows performing multidimensional operations with data, allows increasing the speed of decision-making and the implementation of automated robot-human systems at the level of an assistant working in a unified workspace. The use of machine vision systems analyzing information received in: visible (shape, the trajectory of movement, position of objects, etc.); near-infrared range (data is similar to visible, allows operation in dusty, foggy, low light conditions); far-infrared range - thermal (plotting temperature gradients, identifying areas of overheating); ultraviolet range (analysis of ionization sources, corona discharges, static charges, tags); X-ray and microwave ranges (analysis of the surface and internal structure of objects, allow the identification of defects); range and 3D sensors (construction of volumetric figures, analysis of the relative position of objects and their interaction), etc. Data analysis is often performed not by a single camera but by a group of sensors located not in a single housing. Primary data integration reduces the number of information channels while maintaining the functionality and accuracy of the analysis. The article discusses creating fusion images obtained by industrial sensors into a combined image containing joint data. Combining multi and hyperspectral imaging makes it possible to increase existing systems' efficiency and implement automated decision-making through their small reconfiguration. The article deals with searching for transformation matrices to create single combined images. A method for forming areas of significance obtained based on the analysis of various channels is proposed As methods of primary data processing, a multicriteria filtering method with an automated selection of processing parameters was used, based on the simultaneous minimization of the L2 norm and the first-order finite differences between the input implementation and the obtained values. The proposed method allows preserving the boundaries of objects and minimizing the noise component both on smooth local sections and near transitions. The transformations of color ranges are carried out using a modified multirange alfa-routing algorithm. The paper proposes an algorithm for fusion images with different coefficients and a criterion for their change in given local areas. On a set of test data obtained by cameras in visible (1024x1024 pixels, 8 bits), nearinfrared (800x600 pixels, 8 bits), thermal imaging (320x240, 8 bits), and depth maps (1024x1024, 8 bits in grayscale), presented examples of the formation of object masks and creating combined images.

Development of methods for parallel processing of series of images obtained by a machine vision system in various electromagnetic ranges

When analyzing images in the far-infrared spectrum, the problem of separation of objects arises on the given temperature ranges. The simple threshold separation is hindered by the presence of a noise component. This task is most relevant when used to on weak computing systems and organizing data processing onboard the device (or mobile device). This problem may arise during data analysis: during processing onboard aircraft (UAV), automated control systems for robotic systems, security and access control systems, etc. In article proposes an approach that allows solving the problem of separating a thermal imaging image to objects within specified ranges. The approach is step-by-step image processing using the filtering and blurring method based on multicriteria image preprocessing. A method for changing the bitrate and a method for detecting objects based on the density of similar pixels in a given analysis sliding window. The filtering and blurring method is adapted and accelerated for implementation on low-performance computing modules. As a result of developing the method, we managed to lower the computational requirements. However, this slightly increases the time of preprocessing. The article describes in detail the algorithm for changing the multicriterial method, shows of changes in characteristics and their influence on the result. A method is proposed for changing the gradation of IR image ranges, based on multiple changes on the section gradient. The on a step-by-step merging algorithm for adjacent ranges is based on the use of adaptive weighting factors. The coefficients are determined automatically and depend on the frame. The method of final separation into objects is based on an analysis in the sliding window, we analysis of the number of different elements and the allocation of close objects in groups. The methods and algorithms proposed in the work are adapted for calculations on devices with reduced requirements for computational costs. On the set of test images obtained by portable thermal imaging cameras (SEEK with a resolution of 320 by 240 pixels) from the UAV, car, and street, we present the effectiveness of the application of the approach introduced in the article.

Solving the problem of quickly separating objects into thermal structures in IR images based on analyzing temperature gradients

In hazy weather, images and videos captured outdoor scenes often suffer from inadequate visibility, low contrast, and color shift due to the atmospheric light scattering from the atmosphere particles. In general, the haze is not uniformly distributed. It is a high challenge in computer vision-based applications to visualize matters behind hazy scenes like haze-free images. This paper aims to: i) develop a new optimal-based transmission map for removing haze or fog from a single image and a video; and ii) demonstrate the utility and effectiveness of the developed technique. The proposed method offers a single image de-hazing algorithm based on transmission map optimization and novel enhancement techniques. Intensive computer simulation results of natural Live-Haze dataset and synthetic image datasets such as O-HAZY, dataset show that: 1. The presented approach effectively removes haze and prevents color distortion from undesirable de-hazing. 2. The resulting dehazed images illustrate realistic colors and remarkable details. 3. The proposed method achieves to restore the visibility of hazy scenes and illustrates colorful and natural appearances.

Transmission map optimization for single image dehazing

In many assistive robotic systems, the interface to the user is simply a tablet computer or a monitor attached to a single robot. Missing from approaches are the system extensibility made possible with a tablet computer and a division of work between multiple agents. In this paper we present the design for a software interface to connect users to an assistive robot system for the disabled and elderly. The system is comprised of heterogeneous low-cost assistive robots, a home management portal and a cloud computing backend. The system is designed with the premise that all components do not need to be present for the system to function, but it will be improved when expanded by addition of robots and expanded computing capabilities. This paper focuses on developing the interfaces necessary to connect the user to these systems in a simple and easy to comprehend manner for the target user population.

http://techlav.ncat.edu/publications/Software%20Interface%20Design%20for%20Home-Based%20Assistive.pdf

Sos S. Agaian

Papers

Development of methods for parallel processing of series of images obtained by a machine vision system in various electromagnetic ranges

Solving the problem of quickly separating objects into thermal structures in IR images based on analyzing temperature gradients

Transmission map optimization for single image dehazing

Software interface design for home-based assistive multi-robot system

Front Matter: Volume 6982