An adaptive method based on the improved LPA-ICI algorithm for MRI enhancement

Various diseases are diagnosed using medical imaging used for analysing internal anatomical structures. However, medical images are susceptible to noise introduced in both acquisition and transmission processes. We propose an adaptive data-driven image denoising algorithm based on an improvement of the intersection of confidence intervals (ICI), called relative ICI (RICI) algorithm. The 2D mask of the adaptive size and shape is calculated for each image pixel independently, and utilized in the design of the 2D local polynomial approximation (LPA) filters. Denoising performances, in terms of the PSNR, are compared to the original ICI-based method, as well as to the fixed sized filtering. The proposed adaptive RICI-based denoising outperformed the original ICI-based method by up to 1.32 dB, and the fixed size filtering by up to 6.48 dB. Furthermore, since the denoising of each image pixel is done locally and independently, the method is easy to parallelize.     

A SLIT THROUGH PHOTOGRAPHY

Post-war experimental and conceptual photography in former Yugoslavia has only rarely been the subject of detailed study and interpretation. In considering this period, it is necessary to take into account several factors, including the absence of permanent exhibition spaces for photography, the lack of magazines in which photographic themes were presented and discussed, the impossibility of studying the field of photography and, finally, the inadequate knowledge and application of contemporary criticism and theories of photography. Nevertheless, from the mid-1950s onwards it is possible to note a variety of innovations in the field, in terms of both form and subject-matter. This article considers rare instances of institutional support for progressive photography-related events and unique, intellectual-poetic works. After the break-up of Yugoslavia, there is a dominant tendency to nationalize art created in the former state, thus ignoring the specific Yugoslav cultural field as well as the European context. Based on a methodology which surpasses the national (but still acknowledges it) and searches for meaning within the broader socio-political space to which art is referring, the research aims to change the paradigm of the peripheral position and general ignorance of the circumstances under which this innovative practice emerges.     

Improvements in data reduction in direct pulse heating calorimetry

This paper describes improvements introduced in data reduction in direct heating pulse specific heat experiments. In calculations of specific heat, it is necessary to calculate the first derivative of the recorded temperature data as a function of time. The error induced by different numerical differentiation techniques can represent a significant part of the overall measurement error. Thus, different digital filtering techniques, differentiation, and smoothing algorithms were applied and tested to examine their influence on the minimization of errors induced by noise, which is unavoidable in measured signals. A minimum square error criterion was applied in designing digital filters, with arbitrary prescribed magnitude characteristics. Attention was paid to applications when one or more structural phase transitions in the specimen material occur within the temperature range covered by the experiment. The cases where the frequency spectrum of induced noise overlaps with the spectrum of temperature transient signals originating from phase transitions were analyzed in detail. The effectiveness of the methods of extracting the final specific heat data from a noisy signal using different digital filtering techniques is demonstrated.Paper presented at the Fourth International Workshop on Subsecond Thermophysics, June 27–29, 1995, Köln, Germany.     

Augmented AVI video file for road surveying

This paper presents a novel video augmentation approach: a video recording of a real entity augmented by structured data. This augmented video is a self-contained entity integrating values of perceptible and non-perceptible attributes of the same real entity. It simplifies data search, storage and management. Streaming, sharing, collaboration and synchronization are also simplified by the fact that the structured data (so-called augmented data) are integrated in the video file and therefore only one file needs to be manipulated. Our approach was applied to address the issues which road engineers experience while using the ROad Measurement and Data Acquisition System (ROMDAS). The ROMDAS system collects and analyses the road-condition state through video recordings and the data corresponding acquired by specific measuring devices. Currently, however, road engineers have to search the videos manually in order to find details of interest provided by the analysis of the data measured due to the separation of the video from the data. The ROMDAS system manages a large collection of road-condition data. It does not offer history management of video recordings of the same road captured at different time. We present this hybrid video augmentation system: the Augmented Video stream Framework (AVF). It allows creation, search, history management and playback of such augmented video files for effective road surveying based on the discrete data recorded in parallel to the video recordings. The AVF provides road engineers with effective and more comfortable perceptible and non-perceptible data search, storage and history management to be used for (collaborative) road inspection and maintenance.     

Extending applications using an advanced approach to DLL injection and API hooking

When programmers need to modify third‐party applications, they frequently do not have access to their source code. In such cases, DLL injection and API hooking are techniques that can be used to modify applications without intervening into their source code. The commonly used varieties of injection and hooking approaches have many practical limitations: they are inconvenient for a programmer to implement, do not work reliably in conjunction with all applications and with certain low‐level machine instructions. In this paper we present two novel approaches to DLL injection and API hooking, which we call Debugger‐aided DLL injection and Single Instruction Hooking. Our approaches overcome the limitations of the state‐of‐the art approaches. Despite incurring greater execution times, our approach allows extending of the applications in situations where the comparable approaches fail. As such, it has a notable practical value for beneficial practical applications of injection and hooking approaches, which are present in malware detection programs and computer security tools. Copyright © 2010 John Wiley & Sons, Ltd.     

An intelligent hybrid system for surface coal mine safety analysis

Analysis of safety in surface coal mines represents a very complex process. Published studies on mine safety analysis are usually based on research related to accidents statistics and hazard identification with risk assessment within the mining industry. Discussion in this paper is focused on the application of AI methods in the analysis of safety in mining environment. Complexity of the subject matter requires a high level of expert knowledge and great experience. The solution was found in the creation of a hybrid system PROTECTOR, whose knowledge base represents a formalization of the expert knowledge in the mine safety field. The main goal of the system is the estimation of mining environment as one of the significant components of general safety state in a mine. This global goal is subdivided into a hierarchical structure of subgoals where each subgoal can be viewed as the estimation of a set of parameters (gas, dust, climate, noise, vibration, illumination, geotechnical hazard) which determine the general mine safety state and category of hazard in mining environment. Both the hybrid nature of the system and the possibilities it offers are illustrated through a case study using field data related to an existing Serbian surface coal mine.     

World lines

In this paper we present World Lines as a novel interactive visualization that provides complete control over multiple heterogeneous simulation runs. In many application areas, decisions can only be made by exploring alternative scenarios. The goal of the suggested approach is to support users in this decision making process. In this setting, the data domain is extended to a set of alternative worlds where only one outcome will actually happen. World Lines integrate simulation, visualization and computational steering into a single unified system that is capable of dealing with the extended solution space. World Lines represent simulation runs as causally connected tracks that share a common time axis. This setup enables users to interfere and add new information quickly. A World Line is introduced as a visual combination of user events and their effects in order to present a possible future. To quickly find the most attractive outcome, we suggest World Lines as the governing component in a system of multiple linked views and a simulation component. World Lines employ linking and brushing to enable comparative visual analysis of multiple simulations in linked views. Analysis results can be mapped to various visual variables that World Lines provide in order to highlight the most compelling solutions. To demonstrate this technique we present a flooding scenario and show the usefulness of the integrated approach to support informed decision making.     

Adaptive content-based music retrieval system

This paper presents a tunable content-based music retrieval (CBMR) system suitable the for retrieval of music audio clips. The audio clips are represented as extracted feature vectors. The CBMR system is expert-tunable by altering the feature space. The feature space is tuned according to the expert-specified similarity criteria expressed in terms of clusters of similar audio clips. The main goal of tuning the feature space is to improve retrieval performance, since some features may have more impact on perceived similarity than others. The tuning process utilizes our genetic algorithm. The R-tree index for efficient retrieval of audio clips is based on the clustering of feature vectors. For each cluster a minimal bounding rectangle (MBR) is formed, thus providing objects for indexing. Inserting new nodes into the R-tree is efficiently performed because of the chosen Quadratic Split algorithm. Our CBMR system implements the point query and the n-nearest neighbors query with the O(logn) time complexity. Different objective functions based on cluster similarity and dissimilarity measures are used for the genetic algorithm. We have found that all of them have similar impact on the retrieval performance in terms of precision and recall. The paper includes experimental results in measuring retrieval performance, reporting significant improvement over the untuned feature space.