SOPS: A System for Efficient Processing of Spatial-Keyword Publish/Subscribe

Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. These geo-textual data cover a wide range of topics. Users are interested in receiving up-to-date geo-textual objects (e.g., geo-tagged Tweets) such that their locations meet users’ need and their texts are interesting to users. For example, a user may want to be updated with tweets near her home on the topic “dengue fever headache.” In this demonstration, we present SOPS, the Spatial-Keyword Publish/Subscribe System, that is capable of efficiently processing spatial keyword continuous queries. SOPS supports two types of queries: (1) Boolean Range Continuous (BRC) query that can be used to subscribe the geo-textual objects satisfying a boolean keyword expression and falling in a specified spatial region; (2) Temporal Spatial-Keyword Top-k Continuous (TaSK) query that continuously maintains up-to-date top-k most relevant results over a stream of geo-textual objects. SOPS enables users to formulate their queries and view the real-time results over a stream of geotextual objects by browser-based user interfaces. On the server side, we propose solutions to efficiently processing a large number of BRC queries (tens of millions) and TaSK queries over a stream of geo-textual objects.

Data Processing at the Flaw Detector with Combined Multisector Eddy-Current Transducer

There is described data processing at the flaw detector with combined multisectional eddy-current transducer and heterofrequency magnetic field. The application of this method for detecting flaws in rods and pipes under the conditions of significant transverse displacements is described.

Juvenile Justice System Planning Data Iowa’s Juvenile Justice Advisory Council Three Year Comprehensive Plan with Additional Juvenile Justice System Information, November 2015

This report provides key juvenile justice system planning data, most of which are taken from Iowa’s 2015 Juvenile Justice and Delinquency Prevention Act Three Year Plan. The data and related descriptions serve as an overview of decision making for major juvenile justice system processing points, and also assist state and local officials with policy and practice. Included in the report are school discipline data and data related to juvenile in the adult criminal justice system.

Online data processing consent under EU law: a theoretical framework and empirical evidence from the UK

This article analyses the results of an empirical study on the 200 most popular UK-based websites in various sectors of e-commerce services. The study provides empirical evidence on unlawful processing of personal data. It comprises a survey on the methods used to seek and obtain consent to process personal data for direct marketing and advertisement, and a test on the frequency of unsolicited commercial emails (UCE) received by customers as a consequence of their registration and submission of personal information to a website. Part One of the article presents a conceptual and normative account of data protection, with a discussion of the ethical values on which EU data protection law is grounded and an outline of the elements that must be in place to seek and obtain valid consent to process personal data. Part Two discusses the outcomes of the empirical study, which unveils a significant departure between EU legal theory and practice in data protection. Although a wide majority of the websites in the sample (69%) has in place a system to ask separate consent for engaging in marketing activities, it is only 16.2% of them that obtain a consent which is valid under the standards set by EU law. The test with UCE shows that only one out of three websites (30.5%) respects the will of the data subject not to receive commercial communications. It also shows that, when submitting personal data in online transactions, there is a high probability (50%) of incurring in a website that will ignore the refusal of consent and will send UCE. The article concludes that there is severe lack of compliance of UK online service providers with essential requirements of data protection law. In this respect, it suggests that there is inappropriate standard of implementation, information and supervision by the UK authorities, especially in light of the clarifications provided at EU level.

Error, reproducibility and sensitivity: a pipeline for data processing of Agilent oligonucleotide expression arrays

Background: Expression microarrays are increasingly used to obtain large scale transcriptomic information on a wide range of biological samples. Nevertheless, there is still much debate on the best ways to process data, to design experiments and analyse the output. Furthermore, many of the more sophisticated mathematical approaches to data analysis in the literature remain inaccessible to much of the biological research community. In this study we examine ways of extracting and analysing a large data set obtained using the Agilent long oligonucleotide transcriptomics platform, applied to a set of human macrophage and dendritic cell samples. Results: We describe and validate a series of data extraction, transformation and normalisation steps which are implemented via a new R function. Analysis of replicate normalised reference data demonstrate that intrarray variability is small (only around 2 of the mean log signal), while interarray variability from replicate array measurements has a standard deviation (SD) of around 0.5 log(2) units (6 of mean). The common practise of working with ratios of Cy5/Cy3 signal offers little further improvement in terms of reducing error. Comparison to expression data obtained using Arabidopsis samples demonstrates that the large number of genes in each sample showing a low level of transcription reflect the real complexity of the cellular transcriptome. Multidimensional scaling is used to show that the processed data identifies an underlying structure which reflect some of the key biological variables which define the data set. This structure is robust, allowing reliable comparison of samples collected over a number of years and collected by a variety of operators. Conclusions: This study outlines a robust and easily implemented pipeline for extracting, transforming normalising and visualising transcriptomic array data from Agilent expression platform. The analysis is used to obtain quantitative estimates of the SD arising from experimental (non biological) intra- and interarray variability, and for a lower threshold for determining whether an individual gene is expressed. The study provides a reliable basis for further more extensive studies of the systems biology of eukaryotic cells.

CMS data processing workflows during an extended cosmic ray run

The CMS Collaboration conducted a month-long data taking exercise, the Cosmic Run At Four Tesla, during October-November 2008, with the goal of commissioning the experiment for extended operation. With all installed detector systems participating, CMS recorded 270 million cosmic ray events with the solenoid at a magnetic field strength of 3.8 T. This paper describes the data flow from the detector through the various online and offline computing systems, as well as the workflows used for recording the data, for aligning and calibrating the detector, and for analysis of the data. © 2010 IOP Publishing Ltd and SISSA.

Statistical methods for analysis and processing of medical ultrasound: applications to segmentation and restoration

In this thesis two major topics inherent with medical ultrasound images are addressed: deconvolution and segmentation. In the first case a deconvolution algorithm is described allowing statistically consistent maximum a posteriori estimates of the tissue reflectivity to be restored. These estimates are proven to provide a reliable source of information for achieving an accurate characterization of biological tissues through the ultrasound echo. The second topic involves the definition of a semi automatic algorithm for myocardium segmentation in 2D echocardiographic images. The results show that the proposed method can reduce inter- and intra observer variability in myocardial contours delineation and is feasible and accurate even on clinical data.

A set of canonical problems in sloshing. Part 0: Experimental setup and data processing

In a series of attempts to research and document relevant sloshing type phenomena, a series of experiments have been conducted. The aim of this paper is to describe the setup and data processing of such experiments. A sloshing tank is subjected to angular motion. As a result pressure registers are obtained at several locations, together with the motion data, torque and a collection of image and video information. The experimental rig and the data acquisition systems are described. Useful information for experimental sloshing research practitioners is provided. This information is related to the liquids used in the experiments, the dying techniques, tank building processes, synchronization of acquisition systems, etc. A new procedure for reconstructing experimental data, that takes into account experimental uncertainties, is presented. This procedure is based on a least squares spline approximation of the data. Based on a deterministic approach to the first sloshing wave impact event in a sloshing experiment, an uncertainty analysis procedure of the associated first pressure peak value is described.

Data Processing Modeling in Decision Support Systems.

Due to the advancement of both, information technology in general, and databases in particular; data storage devices are becoming cheaper and data processing speed is increasing. As result of this, organizations tend to store large volumes of data holding great potential information. Decision Support Systems, DSS try to use the stored data to obtain valuable information for organizations. In this paper, we use both data models and use cases to represent the functionality of data processing in DSS following Software Engineering processes. We propose a methodology to develop DSS in the Analysis phase, respective of data processing modeling. We have used, as a starting point, a data model adapted to the semantics involved in multidimensional databases or data warehouses, DW. Also, we have taken an algorithm that provides us with all the possible ways to automatically cross check multidimensional model data. Using the aforementioned, we propose diagrams and descriptions of use cases, which can be considered as patterns representing the DSS functionality, in regard to DW data processing, DW on which DSS are based. We highlight the reusability and automation benefits that this can be achieved, and we think this study can serve as a guide in the development of DSS.

Integration of embedded data processing algorithms inside PAMELA devices

PAMELA (Phased Array Monitoring for Enhanced Life Assessment) SHMTM System is an integrated embedded ultrasonic guided waves based system consisting of several electronic devices and one system manager controller. The data collected by all PAMELA devices in the system must be transmitted to the controller, who will be responsible for carrying out the advanced signal processing to obtain SHM maps. PAMELA devices consist of hardware based on a Virtex 5 FPGA with a PowerPC 440 running an embedded Linux distribution. Therefore, PAMELA devices, in addition to the capability of performing tests and transmitting the collected data to the controller, have the capability of perform local data processing or pre-processing (reduction, normalization, pattern recognition, feature extraction, etc.). Local data processing decreases the data traffic over the network and allows CPU load of the external computer to be reduced. Even it is possible that PAMELA devices are running autonomously performing scheduled tests, and only communicates with the controller in case of detection of structural damages or when programmed. Each PAMELA device integrates a software management application (SMA) that allows to the developer downloading his own algorithm code and adding the new data processing algorithm to the device. The development of the SMA is done in a virtual machine with an Ubuntu Linux distribution including all necessary software tools to perform the entire cycle of development. Eclipse IDE (Integrated Development Environment) is used to develop the SMA project and to write the code of each data processing algorithm. This paper presents the developed software architecture and describes the necessary steps to add new data processing algorithms to SMA in order to increase the processing capabilities of PAMELA devices.An example of basic damage index estimation using delay and sum algorithm is provided.

Online Personal Data Processing and EU Data Protection Reform. CEPS Task Force Report, April 2013

This report sheds light on the fundamental questions and underlying tensions between current policy objectives, compliance strategies and global trends in online personal data processing, assessing the existing and future framework in terms of effective regulation and public policy. Based on the discussions among the members of the CEPS Digital Forum and independent research carried out by the rapporteurs, policy conclusions are derived with the aim of making EU data protection policy more fit for purpose in today’s online technological context. This report constructively engages with the EU data protection framework, but does not provide a textual analysis of the EU data protection reform proposal as such.

Diabetic retinopathy and blockade of the renin–angiotensin system:new data from the DIRECT study programme

The pathogenesis and medical management of diabetic retinopathy is reviewed. The importance of good control of blood glucose and blood pressure remain key elements in the prevention and treatment of diabetic retinopathy, and a number of specific metabolic pathways have been identified that may be useful additional targets for therapeutic intervention. Trial data, however, aimed specifically to answer the questions of optimum medical management are limited, so the DIRECT study of renin-angiotensin blockade using oral candesartan 32 mg daily is a welcome addition to our knowledge. This arose from the promising improvement of retinopathy outcomes in the EUCLID study of lisinopril in type I diabetes. In DIRECT, 5 years of candesartan treatment in type I diabetes reduced the incidence of retinopathy by two or more steps (EDTRS) in severity by 18% (P = 0.0508) and, in a post hoc analysis, reduced the incidence of retinopathy by three-step progression by 35% (P = 0.034). In type I diabetes patients there was no effect on progression of established retinopathy. In contrast, in type II diabetes, 5 years of candesartan treatment resulted in 34% regression of retinopathy (P ≤0.009). Importantly, an overall significant change towards less-severe retinopathy was noted in both type I and II diabetes (P0.03). Although there is still no absolute proof that these effects were specific to RAS blockade, or just an effect of lower blood pressure, it is reasonable to conclude that candesartan has earned a place in the medical management of diabetic retinopathy, to prevent the problem in type I diabetes and to treat the early stages in type II diabetes. © 2010 Macmillan Publishers Limited All rights reserved.

Distributed Visualization Systems in Remote Sensing Data Processing Grid

Implementation of GEOSS/GMES initiative requires creation and integration of service providers, most of which provide geospatial data output from Grid system to interactive user. In this paper approaches of DOS- centers (service providers) integration used in Ukrainian segment of GEOSS/GMES will be considered and template solutions for geospatial data visualization subsystems will be suggested. Developed patterns are implemented in DOS center of Space Research Institute of National Academy of Science of Ukraine and National Space Agency of Ukraine (NASU-NSAU).

Advances in characterisation, calibration and data processing speed of optical coherence tomography systems

This thesis describes advances in the characterisation, calibration and data processing of optical coherence tomography (OCT) systems. Femtosecond (fs) laser inscription was used for producing OCT-phantoms. Transparent materials are generally inert to infra-red radiations, but with fs lasers material modification occurs via non-linear processes when the highly focused light source interacts with the materials. This modification is confined to the focal volume and is highly reproducible. In order to select the best inscription parameters, combination of different inscription parameters were tested, using three fs laser systems, with different operating properties, on a variety of materials. This facilitated the understanding of the key characteristics of the produced structures with the aim of producing viable OCT-phantoms. Finally, OCT-phantoms were successfully designed and fabricated in fused silica. The use of these phantoms to characterise many properties (resolution, distortion, sensitivity decay, scan linearity) of an OCT system was demonstrated. Quantitative methods were developed to support the characterisation of an OCT system collecting images from phantoms and also to improve the quality of the OCT images. Characterisation methods include the measurement of the spatially variant resolution (point spread function (PSF) and modulation transfer function (MTF)), sensitivity and distortion. Processing of OCT data is a computer intensive process. Standard central processing unit (CPU) based processing might take several minutes to a few hours to process acquired data, thus data processing is a significant bottleneck. An alternative choice is to use expensive hardware-based processing such as field programmable gate arrays (FPGAs). However, recently graphics processing unit (GPU) based data processing methods have been developed to minimize this data processing and rendering time. These processing techniques include standard-processing methods which includes a set of algorithms to process the raw data (interference) obtained by the detector and generate A-scans. The work presented here describes accelerated data processing and post processing techniques for OCT systems. The GPU based processing developed, during the PhD, was later implemented into a custom built Fourier domain optical coherence tomography (FD-OCT) system. This system currently processes and renders data in real time. Processing throughput of this system is currently limited by the camera capture rate. OCTphantoms have been heavily used for the qualitative characterization and adjustment/ fine tuning of the operating conditions of OCT system. Currently, investigations are under way to characterize OCT systems using our phantoms. The work presented in this thesis demonstrate several novel techniques of fabricating OCT-phantoms and accelerating OCT data processing using GPUs. In the process of developing phantoms and quantitative methods, a thorough understanding and practical knowledge of OCT and fs laser processing systems was developed. This understanding leads to several novel pieces of research that are not only relevant to OCT but have broader importance. For example, extensive understanding of the properties of fs inscribed structures will be useful in other photonic application such as making of phase mask, wave guides and microfluidic channels. Acceleration of data processing with GPUs is also useful in other fields.

Nonlinear dynamics and chaos simulation system analysis for improved design

Small errors proved catastrophic. Our purpose to remark that a very small cause which escapes our notice determined a considerable effect that we cannot fail to see, and then we say that the effect is due to chance. Small differences in the initial conditions produce very great ones in the final phenomena. A small error in the former will produce an enormous error in the latter. When dealing with any kind of electrical device specification, it is important to note that there exists a pair of test conditions that define a test: the forcing function and the limit. Forcing functions define the external operating constraints placed upon the device tested. The actual test defines how well the device responds to these constraints. Forcing inputs to threshold for example, represents the most difficult testing because this put those inputs as close as possible to the actual switching critical points and guarantees that the device will meet the Input-Output specifications. ^ Prediction becomes impossible by classical analytical analysis bounded by Newton and Euclides. We have found that non linear dynamics characteristics is the natural state of being in all circuits and devices. Opportunities exist for effective error detection in a nonlinear dynamics and chaos environment. ^ Nowadays there are a set of linear limits established around every aspect of a digital or analog circuits out of which devices are consider bad after failing the test. Deterministic chaos circuit is a fact not a possibility as it has been revived by our Ph.D. research. In practice for linear standard informational methodologies, this chaotic data product is usually undesirable and we are educated to be interested in obtaining a more regular stream of output data. ^ This Ph.D. research explored the possibilities of taking the foundation of a very well known simulation and modeling methodology, introducing nonlinear dynamics and chaos precepts, to produce a new error detector instrument able to put together streams of data scattered in space and time. Therefore, mastering deterministic chaos and changing the bad reputation of chaotic data as a potential risk for practical system status determination. ^