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Quality assessment enables organisations to identify the strengths and weaknesses of their services, which is essential for continuous improvement and adaptation to customer needs. IBM SPSS Statistics is one of the most widely used statistical analysis tools that enables efficient processing and evaluation of survey data. With its wide range of features and intuitive interface, SPSS is the ideal tool for data analysis in a variety of fields, including transportation. The aim of this paper is to present methods for data analysis in transport services, focusing on the use of IBM SPSS Statistics. Using chi-square test, the relationships between different quality criteria will be investigated, which will provide valuable information for improving the services provided and increasing customer satisfaction. The results of this analysis will highlight the importance of a systematic approach to quality management and the benefits it brings to organisations operating in a dynamic and competitive environment. [ABSTRACT FROM AUTHOR]

Digital Twin (DT) aims to provide industrial companies with an interface to visualize, analyze, and simulate the production process, improving overall performance. This paper proposes to extend existing DT by adding a complementary methodology to make it suitable for process supervision. To implement our methodology, we introduce a novel framework that identifies, collects, and analyses data from the production system, enhancing DT functionalities. In our case study, we implemented Key Performance Indicators (KPIs) in the immersive environment to monitor physical processes through cyber representation. First, a review of the Digital Twin (DT) allows us to understand the status of the existing methodologies as well as the problem of data contextualization in recent years. Based on this review, performance data in Cyber–Physical Systems (CPS) are identified, localized, and processed to generate indicators for monitoring machine and production line performance through DT. Finally, a discussion reveals the difficulties of integration and the possibilities to respond to other major industrial challenges, like predictive maintenance. [ABSTRACT FROM AUTHOR]

Primarily methodological in its orientation, this paper offers a presentation of 'research outcomes' in ways that challenge and disrupt commonplace notions of data and analysis. In an attempt to write against the grain of conventional qualitative research practice and to experiment with alternative encounters with data and analysis, I present 'data/analysis' in the form of a play (or imagined performance) that writes into being two Deleuzo-Guattarian principles – the critique of the self-conscious 'I' and desire. The play draws on a wider study that examined the potential of writing as a tool for learning for undergraduate student teachers in England. As such, the paper also contributes to debates on the practice and purpose of writing as a method of (professional) inquiry. [ABSTRACT FROM AUTHOR]

Geo-environmental information is an important basis for geohazard analysis and the integration of geo-environmental data is crucial in the construction of urban emergency management systems. In existing urban spatial information systems, the integration of geo-environmental data is neither intuitive nor efficient enough to support the analysis of geohazards well. On the basis of Web virtual globe, this paper proposes a comprehensive framework for the integration and analysis of geo-environmental data. This framework can effectively integrate geological data with a 3D geological model as a carrier, seamlessly connect geographic data, dynamically load real-time monitoring data, and build 3D visualisation and analysis scenes of urban full-space temporal information in the browser. The application example shows that the proposed framework can provide good geo-environmental data and practical data analysis functions for geohazard early warning and decision making, and improve the efficiency of government departments' response to geohazards. [ABSTRACT FROM AUTHOR]

Big data is one of the most rising tools trends that have the ability for considerably changing the way production organizations use user behaviour to analyse and transform it into valuable insights. In this decision trees can be used efficiently for analysing data. In this paper we proposed C4.5 algorithm uses information gain as splitting criteria. In this you are using un-structured data; it can understand data with categorical or numerical values. To handle non-stop values it generates threshold and then divides attributes with values above the threshold and values equal to or below the threshold. C4.5algorithm can easily handle missing values. C4.5 is one of the most classic classification algorithms, but when it is used in mass calculations, the efficiency is very low. C4.5 is one of the most effective classification methods. This paper also gives insights into the rate of accuracy it provides when an XsA dataset contains noisy data, missing data and large amount of data. [ABSTRACT FROM AUTHOR]

The paper focuses on the possibilities of quantitative linguistic method application in the context of psychological disciplines, especially psychodiagnostics. It presents the theoretical basis for this approach, as well as documentation and selected results of the Quantitative Psycholinguistic Analysis of the Formal Parameters of the Text (QPA-FPT) research. The research sample consisted of 76 undergraduates who wrote two types of texts according to in advance given criteria, a stylistically formal text (apology letter) and a stylistically informal text (letter from holiday). Besides, results of psychodiagnostic tests (STAI-X, KṢAT, SSI and PSSI) were collected. During data analysis, all the texts were computationally processed and described by the means of 48 linguistic characteristics (parameters of text). The outcomes of the analysis were then compared with the test results, and significant correlations were identified. The research results include a number of key findings, pointing out the influence of a given text type on its morphological structure, but also the potential links among linguistic features (i.e. text parameters) and specific personality characteristics of the writer, e.g. between the quantity of verbs, emotional skills and the overall score in the SSI test, and between incidence of punctuation and the PSSI test scale distrustful—paranoid. [ABSTRACT FROM AUTHOR]

Piecewise linear fitting, the technique proposed in this paper, performs data reduction on a large dynamic CT dataset and it already takes a step in the direction of the data analysis and characterization that needs to be performed afterwards. In addition, it drastically improves the signal-to-noise ratio. This is demonstrated on two complementary samples: a Bentheimer sandstone and a pharmaceutical tablet. This technique is developed for dynamic high-resolution CT scanning or 4D-μCT, a tool to study dynamic processes in situ on the micro-scale. We propose to start from the low quality reconstruction and perform a piecewise linear fit in the time direction for each voxel. This effectively uses the nearby temporal information, regardless of the nature of the dynamic process, without introducing spatial correlation. [ABSTRACT FROM AUTHOR]

Considering all human activities, one can say information is powerful, but information overload is a problem with meaning and consequences very well known for all of us. Fortunately, performing sophisticated data analysis no longer requires complex research laboratories; big data sets can be accessed, explored, and analyzed in a way that simply was not possible in the past. In this respect, dataoriented parsing is a probabilistic model in computational linguistics conceived with the aim of developing a performance-oriented grammar framework. The paper presents a parsing application for the data related to a cyber attack, all the information being stored in a data base, with an attached graphical interface that displays processed information. [ABSTRACT FROM AUTHOR]

The nominal group technique (NGT) is a method to elicit healthcare priorities. Yet, there is variability on how to conduct the NGT, and limited guidance on how to analyse a diverse sample of multiple groups. This paper addresses some of this ambiguity, and explores whether different approaches to analysis provide the same outcome/s. Conceptual papers and empirical studies were identified via PubMed and informed an adapted version of the NGT. Twenty-six nominal groups were conducted, which provided in-depth knowledge on how to best conduct this method. Pilot group data were used to compare different analysis methods and to explore how this impacted on reported outcomes. Data analyses for large data-sets are complex; thematic analysis is needed to be able to conduct across group comparisons of participant priorities. Consideration should be given not just to the strength, i.e. sum of votes, or relative importance of the priority, but to the voting frequency, i.e. the popularity of the idea amongst participants; our case study demonstrated that this can affect priority rankings for those ideas with the same score. As a case study, this paper provides practical information on analysis for complex data sets. Researchers need to consider more than one analysis process to ensure that the results truly reflect participant priorities. A priority that has a high score may not necessarily reflect its popularity within the group; the voting frequency may also need to be considered. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to introduce Digital Methods Initiative Twitter Capture and Analysis Toolset, a toolset for capturing and analyzing Twitter data. Instead of just presenting a technical paper detailing the system, however, the authors argue that the type of data used for, as well as the methods encoded in, computational systems have epistemological repercussions for research. The authors thus aim at situating the development of the toolset in relation to methodological debates in the social sciences and humanities. Design/methodology/approach – The authors review the possibilities and limitations of existing approaches to capture and analyze Twitter data in order to address the various ways in which computational systems frame research. The authors then introduce the open-source toolset and put forward an approach that embraces methodological diversity and epistemological plurality. Findings – The authors find that design decisions and more general methodological reasoning can and should go hand in hand when building tools for computational social science or digital humanities. Practical implications – Besides methodological transparency, the software provides robust and reproducible data capture and analysis, and interlinks with existing analytical software. Epistemic plurality is emphasized by taking into account how Twitter structures information, by allowing for a number of different sampling techniques, by enabling a variety of analytical approaches or paradigms, and by facilitating work at the micro, meso, and macro levels. Originality/value – The paper opens up critical debate by connecting tool design to fundamental interrogations of methodology and its repercussions for the production of knowledge. The design of the software is inspired by exchanges and debates with scholars from a variety of disciplines and the attempt to propose a flexible and extensible tool that accommodates a wide array of methodological approaches is directly motivated by the desire to keep computational work open for various epistemic sensibilities. [ABSTRACT FROM AUTHOR]

This paper focuses on the application of principal component analysis (PCA) to thoroughly analyse and interpret multidimensional data from a cold rolling process. The analysis includes the effects of variables on the final properties of strips in a cold rolling mill. Unscrambler software was used to analyse and identify hidden variables. Variable correlations were also used to derive correlations between the control parameters. The results of this research will be used to improve the selection of material in order to reduce the occurrence of defects in the cold rolling process and to improve the adjustment of the set points that are performed in every pass or section of the cold rolling process. The hot rolled strips that enter the cold rolling mill are made of different materials and are produced by different strip manufacturers. Some strips break during the thickness reduction process in the cold rolling mill. This paper focuses on two possible causes of breakage: non-uniform strip material properties and failures in the rolling mill process. Two types of rolled strips (those that break and those that do not break) were compared to identify causes of breakage. The results indicate that breakages are caused by material or process failures. PCA was applied to the dataset in order to identify and analyse the relationships between the variables in the process. This information was used to interpret and diagnose the process behaviour. Swarm analysis and relating observations to process behaviour were able to distinguish between different start-up conditions, and between desirable and undesirable process conditions. [ABSTRACT FROM AUTHOR]

Social networks have gained a lot attention. They are perceived as a vast source of information about their users. Variety of different methods and techniques has been proposed to analyze these networks in order to extract valuable information about the users - things they do and like/dislike. A lot of effort is put into improvement of analytical methods in order to grasp a more accurate and detailed image of users. Such information would have an impact on many aspects of everyday life of people - from politics, via professional life, to shopping and entertainment. The theory of fuzzy sets and systems, introduced in 1965, has the ability to handle imprecise and ambiguous information, and to cope with linguistic terms. The theory has evolved into such areas like possibility theory and computing with words. It is very suitable for processing data in a human-like way, and providing the results in a human-oriented manner. The paper presents a short survey of works that use fuzzy-based technologies for analysis of social networks. We pose an idea that fuzzy-based techniques allow for introduction of humancentric and human-like data analysis processes. We include here detailed descriptions of a few target areas of social network analysis that could benefit from applications of fuzzy sets and systems methods. [ABSTRACT FROM AUTHOR]

Discourse analysis is a modern discipline that has inherited lots of attributes from text analysis. So broad is the range of texts and so different the perspectives under which these texts can be analyzed that we can easily understand the different fields that discourse analysis as a whole can cover. The aim of this paper is twofold: firstly, to clarify the different terms included in the discourse in order to separate the features of this discipline from others, and, secondly, to offer a general vision of all the methods that can be carried out under this umbrella to take the most of the data to be analyzed. [ABSTRACT FROM AUTHOR]

In this editorial discussion we reflect on the issues addressed by, and arising from, the papers in this special issue on Single-Case Experimental Design (SCED) study methodology. We identify areas of consensus and disagreement regarding the conduct and analysis of SCED studies. Despite the long history of application of SCEDs in studies of interventions in clinical and educational settings, the field is still developing. There is an emerging consensus on methodological quality criteria for many aspects of SCEDs, but disagreement on what are the most appropriate methods of SCED data analysis. Our aim is to stimulate this ongoing debate and highlight issues requiring further attention from applied researchers and methodologists. In addition we offer tentative criteria to support decision-making in relation to the selection of analytical techniques in SCED studies. Finally, we stress that large-scale interdisciplinary collaborations, such as the current Special Issue, are necessary if SCEDs are going to play a significant role in the development of the evidence base for clinical practice. [ABSTRACT FROM AUTHOR]

Abstract: Disaster relief shelters must be transitional, meaning capable of serving an affected community from emergency, to rehabilitation, to reconstruction. Deployable scissor structures are well-suited for this application since they are lightweight, can be compactly packaged, and have a high volume expansion ratio. Their constitutive parts can be reused and reconfigured to facilitate rehabilitation and reconstruction. This paper presents a preliminary concept for a deployable scissor shelter, including its design, analysis, and experimental validation on a full-scale prototype. First, the conceptual design and analysis using a parametric finite element method are presented. Testing of the prototype is then employed to evaluate the deployment process, support conditions and stiffening elements. Experimental data from these studies validates results from the finite element model, suggesting that the modeling tool is effective for the design of transitional shelters. A final design is presented which meets the requirements of the European Standards. [Copyright &y& Elsevier]

Abstract: The distribution of forces, acting on components of the electromagnetic (EM) system considered herein has been analyzed with the use of simplified models and equivalent dynamic simulators for a variety of plasma event scenarios. The work was aimed at the formulation of the problem of the global force balance and the approach to its resolution, identification of the main factors of the force interaction between components, development of the numerical models for qualitative and quantitative assessment of the problem and relevant parameters and the computations and assessment of the results. The use of equivalent simulators with elimination of redundant details and degrees of freedom (DOFs) principally reduces computational complexity of the problem. The selection (identification) of the equivalent system on the basis of the evaluation of the significance of impacts on the parameter of interest provides the effective and natural filtering of secondary or irrelevant information. The finding of equivalent minimum dynamic systems (EMDS) opens, at a certain rate of computations, a way to develop real-time simulators. The paper describes simplified models, the principles of definition (synthesis) and use of EMDS, the structure of the database (magnitude and time evolution of distributed and integral basic parameters) required for the evaluation of the EM loads and examples of the data. [Copyright &y& Elsevier]

Clinicians during their training period and practice are often called upon to conduct studies to explore the association between certain exposures and disease states or interventions and outcomes. More often they need to interpret the results of research data published in the medical literature. Case-control studies are one of the most frequently used study designs for these purposes. This paper explains basic features of case control studies, rationality behind applying case control design with appropriate examples and limitations of this design. Analysis of sensitivity and specificity along with template to calculate various ratios are explained with user friendly tables and calculations in this article. The interpretation of some of the laboratory results requires sound knowledge of the various risk ratios and positive or negative predictive values for correct identification for unbiased analysis. A major advantage of case-control study is that they are small and retrospective and so they are economical than cohort studies and randomized controlled trials. [ABSTRACT FROM AUTHOR]

The karst groundwater system is extremely vulnerable and easily contaminated by human activities. To understand the spatial distribution of contaminants in the groundwater of karst urban areas and contributors to the contamination, this paper employs the spatial information statistics analysis theory and method to analyze the karst groundwater environment in Guiyang City. Based on the karst groundwater quality data detected in 61 detection points of the research area in the last three years, we made Kriging evaluation isoline map with some ions in the karst groundwater, such as SO, Fe, Mn and F, analyzed and evaluated the spatial distribution, extension and variation of four types of ions on the basis of this isoline map. The results of the analysis show that the anomaly areas of SO, Fe, Mn, F and other ions are mainly located in Baba'ao, Mawangmiao and Sanqiao in northwestern Guiyang City as well as in its downtown area by reasons of the original non-point source pollution and the contamination caused by human activities (industrial and domestic pollution). [ABSTRACT FROM AUTHOR]

Healthcare laboratories are increasingly joining into larger laboratory organizations encompassing several physical laboratories. This caters for important new opportunities for re-defining the concept of a 'laboratory' to encompass all laboratories and measurement methods measuring the same measurand for a population of patients. In order to make measurement results, comparable bias should be minimized or eliminated and measurement uncertainty properly evaluated for all methods used for a particular patient population. The measurement as well as diagnostic uncertainty can be evaluated from internal and external quality control results using GUM principles. In this paper the uncertainty evaluations are described in detail using only two main components, within-laboratory reproducibility and uncertainty of the bias component according to a Nordtest guideline. The evaluation is exemplified for the determination of creatinine in serum for a conglomerate of laboratories both expressed in absolute units (μmol/L) and relative (%). An expanded measurement uncertainty of 12 μmol/L associated with concentrations of creatinine below 120 μmol/L and of 10% associated with concentrations above 120 μmol/L was estimated. The diagnostic uncertainty encompasses both measurement uncertainty and biological variation, and can be estimated for a single value and for a difference. This diagnostic uncertainty for the difference for two samples from the same patient was determined to be 14 μmol/L associated with concentrations of creatinine below 100 μmol/L and 14 % associated with concentrations above 100 μmol/L. [ABSTRACT FROM AUTHOR]

Abstract: Background: Data analysis is a complex and contested part of the qualitative research process, which has received limited theoretical attention. Researchers are often in need of useful instructions or guidelines on how to analyze the mass of qualitative data, but face the lack of clear guidance for using particular analytic methods. Objectives: The aim of this paper is to propose and discuss the Qualitative Analysis Guide of Leuven (QUAGOL), a guide that was developed in order to be able to truly capture the rich insights of qualitative interview data. Method: The article describes six major problems researchers are often struggling with during the process of qualitative data analysis. Consequently, the QUAGOL is proposed as a guide to facilitate the process of analysis. Challenges emerged and lessons learned from own extensive experiences with qualitative data analysis within the Grounded Theory Approach, as well as from those of other researchers (as described in the literature), were discussed and recommendations were presented. Strengths and pitfalls of the proposed method were discussed in detail. Results: The Qualitative Analysis Guide of Leuven (QUAGOL) offers a comprehensive method to guide the process of qualitative data analysis. The process consists of two parts, each consisting of five stages. The method is systematic but not rigid. It is characterized by iterative processes of digging deeper, constantly moving between the various stages of the process. As such, it aims to stimulate the researcher''s intuition and creativity as optimal as possible. Conclusion: The QUAGOL guide is a theory and practice-based guide that supports and facilitates the process of analysis of qualitative interview data. Although the method can facilitate the process of analysis, it cannot guarantee automatic quality. The skills of the researcher and the quality of the research team remain the most crucial components of a successful process of analysis. Additionally, the importance of constantly moving between the various stages throughout the research process cannot be overstated. [Copyright &y& Elsevier]

Abstract: Exact timing is essential for functional MRI data analysis. Datasets are commonly measured using repeated 2D imaging methods, resulting in a temporal offset between slices. To compensate for this timing difference, slice-timing correction (i.e. temporal data interpolation) has been used as an fMRI pre-processing step for more than fifteen years. However, there has been an ongoing debate about the effectiveness and applicability of this method. This paper presents the first elaborated analysis of the impact of the slice-timing effect on simulated data for different fMRI paradigms and measurement parameters, taking into account data noise and smoothing effects. Here we show, depending on repetition time and paradigm design, slice-timing effects can significantly impair fMRI results and slice-timing correction methods can successfully compensate for these effects and therefore increase the robustness of the data analysis. In addition, our results from simulated data were supported by empirical in vivo datasets. Our findings suggest that slice-timing correction should be included in the fMRI pre-processing pipeline. [Copyright &y& Elsevier]

In this paper, the authors compare subgroup analyses as outlined in grant applications and their related publications. Grants awarded by the Netherlands Organization for Health Research and Development (ZonMw) from 2001 onward that were finalized before March 1, 2010, were studied. Of the 79 grant proposals, 50 (63%) were intervention studies, 18 (23%) were diagnostic studies, and 6 (8%) were prognostic studies. Subgroups were mentioned in 49 (62%) grant applications and in 53 (67%) publications. In 20 of the 79 projects (25%), the publications were completely in agreement with the grant proposal; that is, subgroups that were prespecified in the grant proposal were reported and no new subgroup analyses were introduced in the publications. Of the 149 prespecified subgroups, 46 (31%) were reported in the final report or scientific publications, and 143 of the 189 (76%) reported subgroups were based on post-hoc findings. For 77% of the subgroup analyses in the publications, there was no mention of whether these were prespecified or post hoc. Justification for subgroup analysis and methods to study subgroups were rarely reported. The authors conclude that there is a large discrepancy between grant applications and final publications regarding subgroup analyses. Both nonreporting prespecified subgroup analyses and reporting post-hoc subgroup analyses are common. More guidance is clearly needed. [ABSTRACT FROM PUBLISHER]

Abstract: In the past, the availability and/or the acquisition of spatial data were often the main problems of the realization of spatial applications. Meanwhile this situation has changed: on one hand, comprehensive spatial datasets already exist and on the other hand, new sensor technologies have the ability to capture fast and with high quality large amounts of spatial data. More and more responsible for the increasing accessibility of spatial data are also collaborative mapping techniques which enable users to create maps by themselves and to make them available in the internet. However, the potential of this diversity of spatial data can only hardly be utilized. Especially maps in the internet are represented very often only with graphical elements and no explicit information about the map’s scale, extension and content is available. Nevertheless, humans are able to extract this information and to interpret maps. For example, it is possible for a human to distinguish between rural and industrial areas only by looking at the objects’ geometries. Furthermore, a human can easily identify and group map objects that belong together. Also the type, scale and extension of a map can be identified under certain conditions only by looking at the objects’ geometries. All these examples can be subsumed under the term “map interpretation”. In this paper it is discussed how map interpretation can be automated and how automatic map interpretation can be used in order to support other processes. The different kinds of automatic map interpretation are discussed and two approaches are shown in detail. [Copyright &y& Elsevier]

This paper proposes a method to analyze statistically maintenance data for complex medical devices with censoring and missing information. It presents a classification of the different types of failures and establishes policies for analyzing data at the system and component levels taking into account the failure types. The results of this analysis can be used as basic assumptions in the development of a maintenance/inspection optimization model. As a case study, we present the reliability analysis of a general infusion pump from a hospital. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Skype applies strong encryption to provide secure communication inside the whole Skype network. It also uses several techniques to conceal the traffic and the protocol. As a consequence, traditional port-based or payload-based identification of Skype traffic cannot be applied. In this paper, after an overview of the Skype P2P system, network entities and operation, we introduce novel algorithms to detect several types of communications (including voice calls primarily) that the Skype client initiates toward dedicated servers of the Skype network and other peers. The common point in these algorithms is that all of them are based on packet headers only and the extracted flow level information. We do not need information from packet payloads. The identification methods allow us to discover logged on Skype users and their voice calls. The whole identification process is scripted in Transact-SQL; it can thus be executed automatically on a prerecorded (offline) data set. We present identification results, analysis and comparison of data sets captured in mobile and fixed networks. We also present the validation of the algorithms in both network types. Copyright © 2010 John Wiley & Sons, Ltd. After investigating the operation of the Skype peer-to-peer overlay network and performing traffic measurements, we proposed heuristic methods based on flow-dynamics to identify Skype traffic. Besides packet headers and the extracted flow-level information, the identification algorithms rely on the observable behavior of the Skype protocol. We performed traffic analysis in fixed and mobile network environments, including ADSL and 3G/HSDPA mobile networks. The results involve daily profiles of Skype calls and user activity, characteristic properties of Skype voice calls, and findings about the Skype codec. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Background: In the setting of multiple remission and relapse periods of a chronic disease, simple endpoint analysis does not fully capture all relevant information, and we need methods to additionally describe both the duration of remission as well as the interruptions in this desired state. Probably the two-state continuous Markov process model comprises the best mathematical approach to data analysis. However, this approach is complex and not intuitive to clinicians. In this paper we propose a simple scoring system and a graph that can enhance the information about the remission experience in a trial or cohort study. Methods: The continuity rewarded (‘ConRew’) score sums up periods in remission, and rewards extended periods by placing more value on uninterrupted periods than on interrupted periods. The ‘patient vector graph’ attempts to plot each patient''s remission experience over time as a horizontal line (the ‘vector’) that is visible when the patient is in remission, but interrupted whenever relapse occurs. In this way a pattern is formed that conveys the number of patients experiencing remission, their individual total duration and interruptions, and time when these occur. Results: In a dataset of a randomized trial in early rheumatoid arthritis, the graph clearly showed both early and late benefit of one group over the other. The scoring system demonstrated the main benefit was in the number of remission periods, not in their ‘uninterruptedness’. Conclusion: Both approaches proved feasible and added extra information. [Copyright &y& Elsevier]

This paper discusses a pragmatic and innovative approach to the data analysis of oral testimonies when used within a methodological framework of Historiography. Oral testimony is increasingly perceived as an exciting research method within the nursing discipline. However, the availability of a clear method to guide the researcher in their analysis of oral testimonies as the primary data for a Historiography is limited. A practical approach to the interpretation of oral testimony is needed to ensure the continued and successful use of Historiography as a valued research methodology in nursing science. The primary discussion revolves around the explication of a four-stage method proposed as a pragmatic tool for the analysis of oral testimonies. Theoretical literature from the Historian, Paul Thompson and Pragmatist Philosopher, Richard Rorty is drawn upon to bring validity and reliability to the proposed method of analysis. This new technique can be easily used by nurses and many other disciplines in their efforts to efficiently analyse the qualitative data obtained from oral testimonies. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents APERTA, a Web-based tool for the diffusion and analysis of geoscientific data. The main feature differentiating APERTA from other Web-based data diffusion tools is that all output documents and graphics displayed are created each time a user makes a request. The databases queried by APERTA only have to store raw numerical data and the graphics are always generated from an up-to-date database. APERTA allows users to interactively analyze data on-line with standard statistical and geostatistical methods and produce various graphic documents commonly used in earth sciences such as semivariograms, contour maps and cross-sections. Another unique feature of APERTA, which is its most powerful, is that it lets the user decide how data are extracted and graphics are produced. According to their needs and to the type of data, users can thus select the data processing and the output documents required. Because they control processing, users are fully aware of the limits, accuracy and effects of processing on the graphical output. The purpose of APERTA is therefore not only to distribute data but to be a tool to quickly inspect data using an interactive document creation approach. The main features of APERTA are described here along with several examples of data analysis for hydrogeological, geochemical and geotechnical data. [Copyright &y& Elsevier]

Abstract: Unified Accelerator Libraries (UAL, http://www.ual.bnl.gov) software is an open accelerator simulation environment addressing a broad spectrum of accelerator tasks ranging from efficient online-oriented modeling to full-scale realistic beam dynamics studies. The paper introduces a new package integrating UAL simulation algorithms with the QT-based Graphical User Interface and the ROOT data analysis and visualization framework (http://root.cern.ch). The primary user application is implemented as an interactive and configurable Accelerator Physics Player. Its interface to visualization components is based on the QT layer (http://root.bnl.gov) supported by the STAR experiment. [Copyright &y& Elsevier]

In this work the spectrum of the water molecule has been the subject of extensive experimental and theoretical investigations. More than 1500 transitions have been assigned in a far infrared emission spectrum recorded in the 50–500 cm-1 region and experimental rotational energies have been obtained for the second triad of interacting states, (0 3 0), (1 1 0), and (0 1 1), up to J=10 using flame spectroscopy. These new data along with a large data set of already published experimental rotational energies, high-resolution infrared transitions, and microwave lines, involving the eight first vibrational states, have been analyzed using the theoretical formalism developed for water in a previous paper (J. Mol. Spectrosc. 206 (2001) 83), which accounts for the anomalous centrifugal distortion as well as for the Fermi- and Coriolis-type couplings. [Copyright &y& Elsevier]

The text deals with the data analysis from an area of the strategic planning. It focuses on a searching of association rules by the Apriori algorithm. The administrative district of municipalities with extended powers in the Czech Republic were chosen as objects and were described by indicators based on the strategic planning. In the data pre-processing, selected rates of dynamics of the monitored indicators were calculated. Values of the average absolute increase of indicators were converted and were used to the searching of the association rules. Achieved results of three models were compared (e.g. by the support, confidence, rule support, and lift) and described. These models were differed in the way of the association rules searching (i.e. measure of the rule confidence; measure of the confidence difference; and measure of the confidence ratio). The association rules can serve as a support for a preparation of new strategic plans for e.g. municipality, region. Problem areas of the mentioned units could be selected on the basis of the achieved association rules. [ABSTRACT FROM AUTHOR]