Digital Image Watermarking for Arbitrarily Shaped Objects Based On SA-DWT

Many image watermarking schemes have been proposed in recent years, but they usually involve embedding a watermark to the entire image without considering only a particular object in the image, which the image owner may be interested in. This paper proposes a watermarking scheme that can embed a watermark to an arbitrarily shaped object in an image. Before embedding, the image owner specifies an object of arbitrary shape that is of a concern to him. Then the object is transformed into the wavelet domain using in place lifting shape adaptive DWT(SADWT) and a watermark is embedded by modifying the wavelet coefficients. In order to make the watermark robust and transparent, the watermark is embedded in the average of wavelet blocks using the visual model based on the human visual system. Wavelet coefficients n least significant bits (LSBs) are adjusted in concert with the average. Simulation results shows that the proposed watermarking scheme is perceptually invisible and robust against many attacks such as lossy compression (e.g.JPEG, JPEG2000), scaling, adding noise, filtering, etc.Comment: International Journal of Computer Science Issues, Volume 5, pp1-8, October 200

Seismic data clustering management system

This is the abstract of the paper given at the conference. Copyright @ 2011 The Authors.Over the last years, seismic images have increasingly played a vital role to the study of earthquakes. The large volume of seismic data that has been accumulated has created the need to develop sophisticated systems to manage this kind of data. Seismic interpretation can play a much more active role in the evaluation of large volumes of data by providing at an early stage vital information relating to the framework of potential producing levels. [1] This work presents a novel method to manage and analyse seismic data. The data is initially turned into clustering maps using clustering techniques [2] [3] [4] [5] [6], in order to be analysed on the platform. These clustering maps can then be analysed with the friendly-user interface of Seismic 1 which is based on .Net framework architecture [7]. This feature permits the porting of the application in any Windows – based computer as also to many other Linux based environments, using the Mono project functionality [8], so it can run an application using the No-Touch Deployment [7]. The platform supports two ways of processing seismic data. Firstly, a fast multifunctional version of the classical region-growing segmentation algorithm [9], [10] is applied to various areas of interest permitting their precise definition and labelling. Moreover, this algorithm is assigned to automatically allocate new earthquakes to a particular cluster based upon the magnitude of the centre of gravity of the existing clusters; or create a new cluster if all centers of gravity are above a predefined by the user upper threshold point. Secondly, a visual technique is used to record the behaviour of a cluster of earthquakes in a designated area. In this way, the system functions as a dynamic temporal simulator which depicts sequences of earthquakes on a map [11]

On the Relative Contribution of Deep Convolutional Neural Networks for SSVEP-based Bio-Signal Decoding in BCI Speller Applications

Brain-computer interfaces (BCI) harnessing Steady State Visual Evoked Potentials (SSVEP) manipulate the frequency and phase of visual stimuli to generate predictable oscillations in neural activity. For BCI spellers, oscillations are matched with alphanumeric characters allowing users to select target numbers and letters. Advances in BCI spellers can, in part, be accredited to subject-speci?c optimization, including; 1) custom electrode arrangements, 2) ?lter sub-band assessments and 3) stimulus parameter tuning. Here we apply deep convolutional neural networks (DCNN) demonstrating cross-subject functionality for the classi?cation of frequency and phase encoded SSVEP. Electroencephalogram (EEG) data are collected and classi?ed using the same parameters across subjects. Subjects ?xate forty randomly cued ?ickering characters (5 ×8 keyboard array) during concurrent wet-EEG acquisition. These data are provided by an open source SSVEP dataset. Our proposed DCNN, PodNet, achieves 86% and 77% of?ine Accuracy of Classi?cation across-subjects for two data capture periods, respectively, 6-seconds (information transfer rate= 40bpm) and 2-seconds (information transfer rate= 101bpm). Subjects demonstrating sub-optimal (< 70%) performance are classi?ed to similar levels after a short subject-speci?c training period. PodNet outperforms ?lter-bank canonical correlation analysis (FBCCA) for a low volume (3channel) clinically feasible occipital electrode con?guration. The networks de?ned in this study achieve functional performance for the largest number of SSVEP classes decoded via DCNN to date. Our results demonstrate PodNet achieves cross-subject, calibrationless classi?cation and adaptability to sub-optimal subject data and low-volume EEG electrode arrangements

Audio Universe: Tour of the Solar System

We have created a show about the Solar System, freely available for both planetariums and home viewing, where objects in space are represented with sound as well as with visuals. For example, the audience listens to the stars appear above the European Southern Observatory's Very Large Telescope and they hear the planets orbit around their heads. The aim of this show is that it can be enjoyed and understood, irrespective of level of vision. Here we describe how we used our new computer code, STRAUSS, to convert data into sound for the show. We also discuss the lessons learnt during the design of the show, including how it was imperative to obtain a range of diverse perspectives from scientists, a composer and representatives of the blind and vision impaired community.Comment: Published in Astronomy and Geophysics, Volume 63, Issue 2, Pages 2.38-2.40. This is the authors' accepted version of the manuscript. Visit https://www.audiouniverse.org for audio-visual resources. Our new sonification code, STRAUSS, is available at: https://github.com/james-trayford/strauss. Article is 5 pages with 3 figure

Pleurisy Management in Breast Cancer

DergiPark: 379039tmsjAims: According to the data of the Russian Ministry of Public Health, in 2014, 46% cases of breast cancer were complicated by exudative pleurisy. In management of the complication, there are two treatment modalities: Pleurodesis induced by sclerosing drugs and immunomodulators, repetitive pleural aspiration or a combination of those. However, there is still inadequate information about the optimal treatment modality. Therefore we aimed to analyze cases with exudative paracancrosis pleurisy and compare treatment results in order to determine the most effective treatment mode applied.Methods: Three patients with exudative paracancrosis pleurisy were treated. One patient underwent repetitive pleural aspiration and pleurodesis was performed on two patients. Exudate volume and drainage were determined, in addition, pain assessment by the visual analog scale, general exudate analysis, X-ray, Computer Tomography and Ultrasonography were performed.Results: The first patient diagnosed with exudative paracancrosis pleurisy on the right side and treated by thoracentesis. As response to treatment, exudate volume increased from 300 ml up to 800 ml and the patient rated the pain intensity as 5. The second patient was diagnosed with exudative paracancrosis pleurisy on the left side and treated by a combination of thoracentesis and pleurodesis. Pleurodesis is included when the condition worsened after thoracentesis. The treatment concluded with the reduction of exudate volume to the level considered insignificant. The third patient diagnosed with exudative paracancrosis pleurisy on the right side treated by a combination of thoracentesis and pleurodesis. Pleurodesis is included when the condition became worse after thoracentesis. Unlike the second patient, including pleurodesis to treatment caused the symptoms to become heavier.Conclusion: After repetitive pleural aspirations, the patient visited the hospital more frequently and exudate volume increased. Pleurodesis excluded the necessity of punctures and, therefore, the visits. Thus, the treatment with pleurodesis is found to be better than repetitive pleural aspirations, as it decreased the volume of exudate and the number of hospital admission

Inviwo -- A Visualization System with Usage Abstraction Levels

The complexity of today's visualization applications demands specific visualization systems tailored for the development of these applications. Frequently, such systems utilize levels of abstraction to improve the application development process, for instance by providing a data flow network editor. Unfortunately, these abstractions result in several issues, which need to be circumvented through an abstraction-centered system design. Often, a high level of abstraction hides low level details, which makes it difficult to directly access the underlying computing platform, which would be important to achieve an optimal performance. Therefore, we propose a layer structure developed for modern and sustainable visualization systems allowing developers to interact with all contained abstraction levels. We refer to this interaction capabilities as usage abstraction levels, since we target application developers with various levels of experience. We formulate the requirements for such a system, derive the desired architecture, and present how the concepts have been exemplary realized within the Inviwo visualization system. Furthermore, we address several specific challenges that arise during the realization of such a layered architecture, such as communication between different computing platforms, performance centered encapsulation, as well as layer-independent development by supporting cross layer documentation and debugging capabilities