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.

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.

Evaluating interval forecasts of high-frequency financial data

A number of methods of evaluating the validity of interval forecasts of financial data are analysed, and illustrated using intraday FTSE100 index futures returns. Some existing interval forecast evaluation techniques, such as the Markov chain approach of Christoffersen (1998), are shown to be inappropriate in the presence of periodic heteroscedasticity. Instead, we consider a regression-based test, and a modified version of Christoffersen's Markov chain test for independence, and analyse their properties when the financial time series exhibit periodic volatility. These approaches lead to different conclusions when interval forecasts of FTSE100 index futures returns generated by various GARCH(1,1) and periodic GARCH(1,1) models are evaluated.

Data Processing Student Working

A student from the Data Processing program at the New York Trade School is shown working. Black and white photograph with some edge damage due to writing in black along the top.

Felice Gigante, Data Processing Customer Engineer

Felice Gigante a graduate from the New York Trade School Electronics program works on a machine in his job as Data Processing Customer Engineer for the International Business Machines Corp. Original caption reads, "Felice Gigante - Electronices, International Business Machines Corp." Black and white photograph with caption glued to reverse.

Road network and GPS tracking with data processing and quality assessment

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

An architecture of internet based data processing based on multicast and anycast protocols

Most of the current web-based application systems suffer from poor performance and costly heterogeneous accessing. Distributed or replicated strategies can alleviate the problem in some degree, but there are still some problems of the distributed or replicated model, such as data synchronization, load balance, and so on.  In this paper, we propose a novel architecture for Internet-based data processing system based on multicast and anycast protocols. The proposed architecture breaks the functionalities of existing data processing system, in particular, the database functionality, into several agents. These agents communicate with each other using multicast and anycast mechanisms. We show that the proposed architecture provides better scalability, robustness, automatic load balance, and performance than the current distributed architecture of Internet-based data
processing.

A conceptual matrix model for biological data processing

This paper proposes a conceptual matrix model with algorithms for biological data processing. The required elements for constructing a matrix model are discussed. The representative matrix-based methods and algorithms which have potentials in biological data processing are presented / proposed. Some application cases of the model in biological data processing are studied, which show the applicability of this model in various kinds of biological data processing. This conceptual model established a framework within which biological data processing and mining could be conducted. The model is also heuristic to other applications.

Modeling data processing activity to assess the internal control function

This thesis describes research that was conducted into the potential of modeling the activities of the Data Processing Department as an aid to the computer auditor. A methodology is composed to aid in the evaluation of the Internal Controls, particularly the General Controls relative to computer processing. Consisting of three major components, the methodology enables the auditor to model the presumed activities of the Data Processing Department against the actual activities, as recorded on the Operating System Log. The first component of the methodology is the construction and loading of a model of the presumed activities of the Data Processing Department from its verbal, scheduled, and reported activities. The second component is the generation of a description of the actual activities of the Data Processing Department from the information recorded on the Operating System Log. This is effected by reducing the Operating System Log to the format described by the Standard Audit File concept. Finally, the third component in the methodology is the modeling process itself. This is in fact a new analysis technique proposed for use by the EDP auditor. The modeling process is composed of software that compares the model developed and loaded in the first component, with the description of actual activity as collated by the second component. Results from this comparison are then reviewed by the auditor, who determines if they adequately depict the situation, or whether the models description as specified in the first component requires to be altered, and the modeling process re-initiated. In conducting the research, information and data from a production installation was used. Use of the ‘real-world’ input proved both the feasibility of developing a model of the reported activities of the Data Processing Department, and the adequacy of the operating system log as a source of information to report the departments actual activities. Additionally, it enabled the involvement and comment of practicing auditors. The research involved analysis of the effect of EDP on the audit process, structure of the EDP audit process, data reduction, data structures, model formalization, and model processing software. Additionally, the Standard Audit File concept was verified through its use by practising auditors, and expanded by the development of an indexed data structure, which enabled its analysis to be conducted interactively. Results from the trial implementation of the research software and methodology at a production installation confirmed the research hypothesis that the activities of the Data Processing Department could be modelled, and that there are substantial benefits from the EDP auditor in analysing this process. The research in fact provides a new source of information, and develops a new analysis technique for the EDP auditor. It demonstrates the utilization of computer technology to monitor itself for the audit function, and reasserts auditor independence by providing access to technical detail describing the processing activities of the computer.

Performance evaluation of open source seismic data processing packages

In many businesses, including hydrocarbon industries, reducing cost is of high priority. Although hydrocarbon industries appear able to afford the expensive computing infrastructure and software packages used to process seismic data in the search for hydrocarbon traps, it is always imperative to find ways to minimize cost. Seismic processing costs can be significantly reduced by using inexpensive, open source seismic data processing packages. However, hydrocarbon industries question the processing performance capability of open source packages, claiming that their seismic functions are less integrated and provide almost no technical guarantees for one to use. The objective of this paper is to demonstrate, through a comparative analysis, that open source seismic data processing packages are capable of executing the required seismic functions on an actual industrial workload. To achieve this objective we investigate whether or not open source seismic data processing packages can be executed using the same set of seismic data through data format conversions, and whether or not they can achieve reasonable performance and speedup when executing parallel seismic functions on a HPC cluster. Among the few open source packages available on the Internet, the subjects of our study are two popular packages: Seismic UNIX (SU) and Madagascar.

Recommendations for improved data processing from expired gas analysis indirect calorimetry

There is currently no universally recommended and accepted method of data processing within the science of indirect calorimetry for either mixing chamber or breath-by-breath systems of expired gas analysis. Exercise physiologists were first surveyed to determine methods used to process oxygen consumption ([OV0312]O 2) data, and current attitudes to data processing within the science of indirect calorimetry. Breath-by-breath datasets obtained from indirect calorimetry during incremental exercise were then used to demonstrate the consequences of commonly used time, breath and digital filter post-acquisition data processing strategies. Assessment of the variability in breath-by-breath data was determined using multiple regression based on the independent variables ventilation (VE), and the expired gas fractions for oxygen and carbon dioxide, FEO 2 and FECO2, respectively. Based on the results of explanation of variance of the breath-by-breath [OV0312]O2 data, methods of processing to remove variability were proposed for time-averaged, breath-averaged and digital filter applications. Among exercise physiologists, the strategy used to remove the variability in sequential [OV0312]O2 measurements varied widely, and consisted of time averages (30 sec [38%], 60 sec [18%], 20 sec [11%], 15 sec [8%]), a moving average of five to 11 breaths (10%), and the middle five of seven breaths (7%). Most respondents indicated that they used multiple criteria to establish maximum [OV0312]O 2 ([OV0312]O2max) including: the attainment of age-predicted maximum heart rate (HRmax) [53%], respiratory exchange ratio (RER) >1.10 (49%) or RER >1.15 (27%) and a rating of perceived exertion (RPE) of >17, 18 or 19 (20%). The reasons stated for these strategies included their own beliefs (32%), what they were taught (26%), what they read in research articles (22%), tradition (13%) and the influence of their colleagues (7%). The combination of VE, FEO 2 and FECO2 removed 96-98% of [OV0312]O2 breath-by-breath variability in incremental and steady-state exercise [OV0312]O2 data sets, respectively. Correction of residual error in [OV0312]O2 datasets to 10% of the raw variability results from application of a 30-second time average, 15-breath running average, or a 0.04 Hz low cut-off digital filter. Thus, we recommend that once these data processing strategies are used, the peak or maximal value becomes the highest processed datapoint. Exercise physiologists need to agree on, and continually refine through empirical research, a consistent process for analysing data from indirect calorimetry.