Organization and Security of the Audio and Video Archive for Unique Bulgarian Bells

AMS Subj. Classification: H.3.7 Digital Libraries, K.6.5 Security and Protection

Análise de desempenho de algoritmos de compressão de dados com perda para aplicações industriais

The great amount of data generated as the result of the automation and process supervision in industry implies in two problems: a big demand of storage in discs and the difficulty in streaming this data through a telecommunications link. The lossy data compression algorithms were born in the 90’s with the goal of solving these problems and, by consequence, industries started to use those algorithms in industrial supervision systems to compress data in real time. These algorithms were projected to eliminate redundant and undesired information in a efficient and simple way. However, those algorithms parameters must be set for each process variable, becoming impracticable to configure this parameters for each variable in case of systems that monitor thousands of them. In that context, this paper propose the algorithm Adaptive Swinging Door Trending that consists in a adaptation of the Swinging Door Trending, as this main parameters are adjusted dynamically by the analysis of the signal tendencies in real time. It’s also proposed a comparative analysis of performance in lossy data compression algorithms applied on time series process variables and dynamometer cards. The algorithms used to compare were the piecewise linear and the transforms.

Improving Smartphones Battery Life by Reducing Energy Waste of Background Applications

Smartphones have undergone a remarkable evolution over the last few years, from simple calling devices to full fledged computing devices where multiple services and applications run concurrently. Unfortunately, battery capacity increases at much slower pace, resulting as a main bottleneck for Internet connected smartphones. Several software-based techniques have been proposed in the literature for improving the battery life. Most common techniques include data compression, packet aggregation or batch scheduling, offloading partial computations to cloud, switching OFF interfaces (e.g., WiFi or 3G/4G) periodically for short intervals etc. However, there has been no focus on eliminating the energy waste of background applications that extensively utilize smartphone resources such as CPU, memory, GPS, WiFi, 3G/4G data connection etc. In this paper, we propose an Application State Proxy (ASP) that suppresses/stops the applications on smartphones and maintains their presence on any other network device. The applications are resumed/restarted on smartphones only in case of any event, such as a new message arrival. In this paper, we present the key requirements for the ASP service and different possible architectural designs. In short, the ASP concept can significantly improve the battery life of smartphones, by reducing to maximum extent the usage of its resources due to background applications.

Analysis of Molecular Dynamics Simulations of Protein Folding

Microsecond long Molecular Dynamics (MD) trajectories of biomolecular processes are now possible due to advances in computer technology. Soon, trajectories long enough to probe dynamics over many milliseconds will become available. Since these timescales match the physiological timescales over which many small proteins fold, all atom MD simulations of protein folding are now becoming popular. To distill features of such large folding trajectories, we must develop methods that can both compress trajectory data to enable visualization, and that can yield themselves to further analysis, such as the finding of collective coordinates and reduction of the dynamics. Conventionally, clustering has been the most popular MD trajectory analysis technique, followed by principal component analysis (PCA). Simple clustering used in MD trajectory analysis suffers from various serious drawbacks, namely, (i) it is not data driven, (ii) it is unstable to noise and change in cutoff parameters, and (iii) since it does not take into account interrelationships amongst data points, the separation of data into clusters can often be artificial. Usually, partitions generated by clustering techniques are validated visually, but such validation is not possible for MD trajectories of protein folding, as the underlying structural transitions are not well understood. Rigorous cluster validation techniques may be adapted, but it is more crucial to reduce the dimensions in which MD trajectories reside, while still preserving their salient features. PCA has often been used for dimension reduction and while it is computationally inexpensive, being a linear method, it does not achieve good data compression. In this thesis, I propose a different method, a nonmetric multidimensional scaling (nMDS) technique, which achieves superior data compression by virtue of being nonlinear, and also provides a clear insight into the structural processes underlying MD trajectories. I illustrate the capabilities of nMDS by analyzing three complete villin headpiece folding and six norleucine mutant (NLE) folding trajectories simulated by Freddolino and Schulten [1]. Using these trajectories, I make comparisons between nMDS, PCA and clustering to demonstrate the superiority of nMDS. The three villin headpiece trajectories showed great structural heterogeneity. Apart from a few trivial features like early formation of secondary structure, no commonalities between trajectories were found. There were no units of residues or atoms found moving in concert across the trajectories. A flipping transition, corresponding to the flipping of helix 1 relative to the plane formed by helices 2 and 3 was observed towards the end of the folding process in all trajectories, when nearly all native contacts had been formed. However, the transition occurred through a different series of steps in all trajectories, indicating that it may not be a common transition in villin folding. The trajectories showed competition between local structure formation/hydrophobic collapse and global structure formation in all trajectories. Our analysis on the NLE trajectories confirms the notion that a tight hydrophobic core inhibits correct 3-D rearrangement. Only one of the six NLE trajectories folded, and it showed no flipping transition. All the other trajectories get trapped in hydrophobically collapsed states. The NLE residues were found to be buried deeply into the core, compared to the corresponding lysines in the villin headpiece, thereby making the core tighter and harder to undo for 3-D rearrangement. Our results suggest that the NLE may not be a fast folder as experiments suggest. The tightness of the hydrophobic core may be a very important factor in the folding of larger proteins. It is likely that chaperones like GroEL act to undo the tight hydrophobic core of proteins, after most secondary structure elements have been formed, so that global rearrangement is easier. I conclude by presenting facts about chaperone-protein complexes and propose further directions for the study of protein folding.

ViDRILO: The Visual and Depth Robot Indoor Localization with Objects information dataset

In this article we describe a semantic localization dataset for indoor environments named ViDRILO. The dataset provides five sequences of frames acquired with a mobile robot in two similar office buildings under different lighting conditions. Each frame consists of a point cloud representation of the scene and a perspective image. The frames in the dataset are annotated with the semantic category of the scene, but also with the presence or absence of a list of predefined objects appearing in the scene. In addition to the frames and annotations, the dataset is distributed with a set of tools for its use in both place classification and object recognition tasks. The large number of labeled frames in conjunction with the annotation scheme make this dataset different from existing ones. The ViDRILO dataset is released for use as a benchmark for different problems such as multimodal place classification and object recognition, 3D reconstruction or point cloud data compression.

Integer Linear Programming for Sequence Problems: A general approach to reduce the problem size

Sequence problems belong to the most challenging interdisciplinary topics of the actuality. They are ubiquitous in science and daily life and occur, for example, in form of DNA sequences encoding all information of an organism, as a text (natural or formal) or in form of a computer program. Therefore, sequence problems occur in many variations in computational biology (drug development), coding theory, data compression, quantitative and computational linguistics (e.g. machine translation). In recent years appeared some proposals to formulate sequence problems like the closest string problem (CSP) and the farthest string problem (FSP) as an Integer Linear Programming Problem (ILPP). In the present talk we present a general novel approach to reduce the size of the ILPP by grouping isomorphous columns of the string matrix together. The approach is of practical use, since the solution of sequence problems is very time consuming, in particular when the sequences are long.

Poster Abstract : A sensor network for compression and streaming of GPS trajectory data

We present the design and deployment results for PosNet - a large-scale, long-duration sensor network that gathers summary position and status information from mobile nodes. The mobile nodes have a fixed-sized memory buffer to which position data is added at a constant rate, and from which data is downloaded at a non-constant rate. We have developed a novel algorithm that performs online summarization of position data within the buffer, where the algorithm naturally accommodates data input and output rate mismatch, and also provides a delay-tolerant approach to data transport. The algorithm has been extensively tested in a large-scale long-duration cattle monitoring and control application.

Wavelet based compression and denoising of optical tomography data

Two methods based on wavelet/wavelet packet expansion to denoise and compress optical tomography data containing scattered noise are presented, In the first, the wavelet expansion coefficients of noisy data are shrunk using a soft threshold. In the second, the data are expanded into a wavelet packet tree upon which a best basis search is done. The resulting coefficients are truncated on the basis of energy content. It can be seen that the first method results in efficient denoising of experimental data when scattering particle density in the medium surrounding the object was up to 12.0 x 10(6) per cm(3). This method achieves a compression ratio of approximate to 8:1. The wavelet packet based method resulted in a compression of up to 11:1 and also exhibited reasonable noise reduction capability. Tomographic reconstructions obtained from denoised data are presented. (C) 1999 Published by Elsevier Science B.V. All rights reserved,

Data transmission by pulse compression

Pulse compression techniques originated in radar.The present work is concerned with the utilization of these techniques in general, and the linear FM (LFM) technique in particular, for comnunications. It introduces these techniques from an optimum communications viewpoint and outlines their capabilities.It also considers the candidacy of the class of LFM signals for digital data transmission and the LFM spectrum. Work related to the utilization of LFM signals for digital data transmission has been mostly experimental and mainly concerned with employing two rectangular LFM pulses (or chirps) with reversed slopes to convey the bits 1 and 0 in an incoherent node.No systematic theory for LFM signal design and system performance has been available. Accordingly, the present work establishes such a theory taking into account coherent and noncoherent single-link and multiplex signalling modes. Some new results concerning the slope-reversal chirp pair are obtained. The LFM technique combines the typical capabilities of pulse compression with a relative ease of implementation. However, these merits are often hampered by the difficulty of handling the LFM spectrum which cannot generally be expressed closed-form. The common practice is to obtain a plot of this spectrum with a digital computer for every single set of LFM pulse parameters.Moreover, reported work has been Justly confined to the spectrum of an ideally rectangular chirp pulse with no rise or fall times.Accordingly, the present work comprises a systerratic study of the LFM spectrum which takes the rise and fall time of the chirp pulse into account and can accommodate any LFM pulse with any parameters.It· formulates rather simple and accurate prediction criteria concerning the behaviour of this spectrum in the different frequency regions. These criteria would facilitate the handling of the LFM technique in theory and practice.

Content-aware compression for big textual data analysis

A substantial amount of information on the Internet is present in the form of text. The value of this semi-structured and unstructured data has been widely acknowledged, with consequent scientific and commercial exploitation. The ever-increasing data production, however, pushes data analytic platforms to their limit. This thesis proposes techniques for more efficient textual big data analysis suitable for the Hadoop analytic platform. This research explores the direct processing of compressed textual data. The focus is on developing novel compression methods with a number of desirable properties to support text-based big data analysis in distributed environments. The novel contributions of this work include the following. Firstly, a Content-aware Partial Compression (CaPC) scheme is developed. CaPC makes a distinction between informational and functional content in which only the informational content is compressed. Thus, the compressed data is made transparent to existing software libraries which often rely on functional content to work. Secondly, a context-free bit-oriented compression scheme (Approximated Huffman Compression) based on the Huffman algorithm is developed. This uses a hybrid data structure that allows pattern searching in compressed data in linear time. Thirdly, several modern compression schemes have been extended so that the compressed data can be safely split with respect to logical data records in distributed file systems. Furthermore, an innovative two layer compression architecture is used, in which each compression layer is appropriate for the corresponding stage of data processing. Peripheral libraries are developed that seamlessly link the proposed compression schemes to existing analytic platforms and computational frameworks, and also make the use of the compressed data transparent to developers. The compression schemes have been evaluated for a number of standard MapReduce analysis tasks using a collection of real-world datasets. In comparison with existing solutions, they have shown substantial improvement in performance and significant reduction in system resource requirements.

Compression stockings and the prevention of symptomatic venous thromboembolism: data from the Tinzaparin in Acute Ischaemic Stroke Trial

Background: Venous thromboembolism (VTE) is a well recognised and preventable complication of acute stroke. While graduated compression stockings reduce the risk of VTE in surgical patients their benefit in acute stroke remains uncertain. Methods: The relationship between symptomatic VTE and use of stockings using observational data from the ‘Tinzaparin in Acute Ischaemic Stroke Trial’, which compared 10 days of treatment with tinzaparin (175 IU.kg-1 or 100 IU.kg-1) with, aspirin (300 mg od), was assessed using logistic regression adjusted for known VTE risk factors and treatment. Results: Symptomatic VTE occurred in 28 patients (1.9%, DVT 18, PE 13) within 15 days of enrolment in 1,479 patients. Patients wearing one or two stockings for any period of time during the first 10 days (n=803) had a non-significant increase (odds ratio, OR 2.45, 95% confidence interval, CI 0.95 - 6.32) in the risk of symptomatic VTE. In contrast, those wearing bilateral stockings for 10 days (n=374) had a non-significant reduction in the odds of symptomatic VTE as compared to those who wore no stockings or wore them for less than 10 days (OR 0.65, 95% CI 0.26-1.65). Mild stroke and treatment with tinzaparin were associated with a reduced risk of VTE. Conclusions: Bilateral graduated compression stockings may reduce the incidence of VTE by one-third in patients with acute ischaemic stroke. However, the uncertainty in this finding, low frequency of symptomatic VTE, potential for stockings to cause harm, and cost of stockings highlight the need for a large randomised-controlled trial to examine the safety and efficacy of stockings in acute stroke.

Development of a biaxial compression device for biological samples : preliminary experimental results for a closed cell foam

Biological tissues are subjected to complex loading states in vivo and in order to define constitutive equations that effectively simulate their mechanical behaviour under these loads, it is necessary to obtain data on the tissue's response to multiaxial loading. Single axis and shear testing of biological tissues is often carried out, but biaxial testing is less common. We sought to design and commission a biaxial compression testing device, capable of obtaining repeatable data for biological samples. The apparatus comprised a sealed stainless steel pressure vessel specifically designed such that a state of hydrostatic compression could be created on the test specimen while simultaneously unloading the sample along one axis with an equilibrating tensile pressure. Thus a state of equibiaxial compression was created perpendicular to the long axis of a rectangular sample. For the purpose of calibration and commissioning of the vessel, rectangular samples of closed cell ethylene vinyl acetate (EVA) foam were tested. Each sample was subjected to repeated loading, and nine separate biaxial experiments were carried out to a maximum pressure of 204 kPa (30 psi), with a relaxation time of two hours between them. Calibration testing demonstrated the force applied to the samples had a maximum error of 0.026 N (0.423% of maximum applied force). Under repeated loading, the foam sample demonstrated lower stiffness during the first load cycle. Following this cycle, an increased stiffness, repeatable response was observed with successive loading. While the experimental protocol was developed for EVA foam, preliminary results on this material suggest that this device may be capable of providing test data for biological tissue samples. The load response of the foam was characteristic of closed cell foams, with consolidation during the early loading cycles, then a repeatable load-displacement response upon repeated loading. The repeatability of the test results demonstrated the ability of the test device to provide reproducible test data and the low experimental error in the force demonstrated the reliability of the test data.

An experimental and finite element investigation of the biomechanics of vertebral compression fractures

Osteoporosis is a disease characterized by low bone mass and micro-architectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fracture. Osteoporosis affects over 200 million people worldwide, with an estimated 1.5 million fractures annually in the United States alone, and with attendant costs exceeding $10 billion dollars per annum. Osteoporosis reduces bone density through a series of structural changes to the honeycomb-like trabecular bone structure (micro-structure). The reduced bone density, coupled with the microstructural changes, results in significant loss of bone strength and increased fracture risk. Vertebral compression fractures are the most common type of osteoporotic fracture and are associated with pain, increased thoracic curvature, reduced mobility, and difficulty with self care. Surgical interventions, such as kyphoplasty or vertebroplasty, are used to treat osteoporotic vertebral fractures by restoring vertebral stability and alleviating pain. These minimally invasive procedures involve injecting bone cement into the fractured vertebrae. The techniques are still relatively new and while initial results are promising, with the procedures relieving pain in 70-95% of cases, medium-term investigations are now indicating an increased risk of adjacent level fracture following the procedure. With the aging population, understanding and treatment of osteoporosis is an increasingly important public health issue in developed Western countries. The aim of this study was to investigate the biomechanics of spinal osteoporosis and osteoporotic vertebral compression fractures by developing multi-scale computational, Finite Element (FE) models of both healthy and osteoporotic vertebral bodies. The multi-scale approach included the overall vertebral body anatomy, as well as a detailed representation of the internal trabecular microstructure. This novel, multi-scale approach overcame limitations of previous investigations by allowing simultaneous investigation of the mechanics of the trabecular micro-structure as well as overall vertebral body mechanics. The models were used to simulate the progression of osteoporosis, the effect of different loading conditions on vertebral strength and stiffness, and the effects of vertebroplasty on vertebral and trabecular mechanics. The model development process began with the development of an individual trabecular strut model using 3D beam elements, which was used as the building block for lattice-type, structural trabecular bone models, which were in turn incorporated into the vertebral body models. At each stage of model development, model predictions were compared to analytical solutions and in-vitro data from existing literature. The incremental process provided confidence in the predictions of each model before incorporation into the overall vertebral body model. The trabecular bone model, vertebral body model and vertebroplasty models were validated against in-vitro data from a series of compression tests performed using human cadaveric vertebral bodies. Firstly, trabecular bone samples were acquired and morphological parameters for each sample were measured using high resolution micro-computed tomography (CT). Apparent mechanical properties for each sample were then determined using uni-axial compression tests. Bone tissue properties were inversely determined using voxel-based FE models based on the micro-CT data. Specimen specific trabecular bone models were developed and the predicted apparent stiffness and strength were compared to the experimentally measured apparent stiffness and strength of the corresponding specimen. Following the trabecular specimen tests, a series of 12 whole cadaveric vertebrae were then divided into treated and non-treated groups and vertebroplasty performed on the specimens of the treated group. The vertebrae in both groups underwent clinical-CT scanning and destructive uniaxial compression testing. Specimen specific FE vertebral body models were developed and the predicted mechanical response compared to the experimentally measured responses. The validation process demonstrated that the multi-scale FE models comprising a lattice network of beam elements were able to accurately capture the failure mechanics of trabecular bone; and a trabecular core represented with beam elements enclosed in a layer of shell elements to represent the cortical shell was able to adequately represent the failure mechanics of intact vertebral bodies with varying degrees of osteoporosis. Following model development and validation, the models were used to investigate the effects of progressive osteoporosis on vertebral body mechanics and trabecular bone mechanics. These simulations showed that overall failure of the osteoporotic vertebral body is initiated by failure of the trabecular core, and the failure mechanism of the trabeculae varies with the progression of osteoporosis; from tissue yield in healthy trabecular bone, to failure due to instability (buckling) in osteoporotic bone with its thinner trabecular struts. The mechanical response of the vertebral body under load is highly dependent on the ability of the endplates to deform to transmit the load to the underlying trabecular bone. The ability of the endplate to evenly transfer the load through the core diminishes with osteoporosis. Investigation into the effect of different loading conditions on the vertebral body found that, because the trabecular bone structural changes which occur in osteoporosis result in a structure that is highly aligned with the loading direction, the vertebral body is consequently less able to withstand non-uniform loading states such as occurs in forward flexion. Changes in vertebral body loading due to disc degeneration were simulated, but proved to have little effect on osteoporotic vertebra mechanics. Conversely, differences in vertebral body loading between simulated invivo (uniform endplate pressure) and in-vitro conditions (where the vertebral endplates are rigidly cemented) had a dramatic effect on the predicted vertebral mechanics. This investigation suggested that in-vitro loading using bone cement potting of both endplates has major limitations in its ability to represent vertebral body mechanics in-vivo. And lastly, FE investigation into the biomechanical effect of vertebroplasty was performed. The results of this investigation demonstrated that the effect of vertebroplasty on overall vertebra mechanics is strongly governed by the cement distribution achieved within the trabecular core. In agreement with a recent study, the models predicted that vertebroplasty cement distributions which do not form one continuous mass which contacts both endplates have little effect on vertebral body stiffness or strength. In summary, this work presents the development of a novel, multi-scale Finite Element model of the osteoporotic vertebral body, which provides a powerful new tool for investigating the mechanics of osteoporotic vertebral compression fractures at the trabecular bone micro-structural level, and at the vertebral body level.