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Ever since DIALOG services were first offered, it has held a dominant position in the online industry because of its outstanding software, however STN, which is devoted to the distribution of scientific and technical information, ...
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Ever since DIALOG services were first offered, it has held a dominant position in the online industry because of its outstanding software, however STN, which is devoted to the distribution of scientific and technical information, has recently developed a powerful softward family that corresponds closely to the needs of researchers. These new system features are causing shifts in usage in the online industry. STN's SmartSELECT, which simplifies the complicated steps in citation analysis, is helping to shift usage from DIALOG to STN.
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Background Cancer information services (CISs) are a valuable source of evidence-based information. Previous studies in the field of CISs often investigate only short periods of time. However, there is a need for long-term analyses...
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Background Cancer information services (CISs) are a valuable source of evidence-based information. Previous studies in the field of CISs often investigate only short periods of time. However, there is a need for long-term analyses to identify changes in the use of CISs. Objectives The purpose of this study was to analyze trends in the inquiries of patients and surrogate seekers to a CIS. Method We conducted a secondary data analysis of the inquiry records of the German CIS (Krebsinformationsdienst, KID) hosted by the German Cancer Research Center from 1992 until 2016 (N= 545,070). Trends in the number of inquiries were described using the whole sample, while the description of further characteristics is based on a sample (n= 55,046) of patients, their family members, and friends. Results The inquiries increased in the period examined (1992: 11,344 inquiries; 2016: 34,869 inquiries). Since 2005, a greater share of patients (between 52 and 60%) than surrogate seekers have been contacting the CIS. The mean age of both self-seeking and supported patients increased from under 55 years between 1992 and 2000 up to over 60 years in the year 2016. Breast cancer is at all times the most frequently inquired cancer type (patients: n= 11,319, 39%; surrogate seekers: n= 4173, 17%). Even after the implementation of e-mail as an additional communication channel, the majority of inquirers still prefer contact by phone (between 80 and 98%). Conclusions Changes in the utilization of a CIS over time are discussed against the background of structural changes, such as shifts in prevalence rates, family structures, or media environments.
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Social network concepts are invaluable for understanding the social network phenomena, but they are difficult to comprehend without computerized visualization. However, most existing network visualization techniques provide limite...
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Social network concepts are invaluable for understanding the social network phenomena, but they are difficult to comprehend without computerized visualization. However, most existing network visualization techniques provide limited support for the comprehension of network concepts. This research proposes an approach called concept visualization to facilitate the understanding of social network concepts. The paper describes an implementation of the approach. Results from a controlled laboratory experiment indicate that, compared with the benchmark system, the NetVizer system facilitated better understanding of the concepts of betweenness centrality, gatekeepers of subgroups, and structural similarity. It also supported a faster comprehension of subgroup identification.
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In Big Data: A Revolution That Will Transform How We Live, Work, and Think, Viktor Mayer-Sch?nberger and Kenneth Cukier present the emerging trend of big data and its various political, economic, social, and professional implicati...
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In Big Data: A Revolution That Will Transform How We Live, Work, and Think, Viktor Mayer-Sch?nberger and Kenneth Cukier present the emerging trend of big data and its various political, economic, social, and professional implications. This book is intended for a diverse academic and professional audience in various disciplines. It should be of particular interest to scholars and practitioners in the information sciences and professions because of its focus on the information concepts and practices inherent in, and influenced by, big data. The chapters are divided by big data's major components, thereby providing a clear framework in which to approach and understand this emerging trend. A detailed section for notes on each chapter is included, along with a bibliography and index.
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Watershed delineation is a process for defining a land area that contributes surface water flow to a single outlet point. It is a commonly used in water resources analysis to define the domain in which hydrologic process calculati...
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Watershed delineation is a process for defining a land area that contributes surface water flow to a single outlet point. It is a commonly used in water resources analysis to define the domain in which hydrologic process calculations are applied. There has been a growing effort over the past decade to improve surface elevation measurements in the U.S., which has had a significant impact on the accuracy of hydrologic calculations. Traditional watershed processing on these elevation rasters, however, becomes more burdensome as data resolution increases. As a result, processing of these datasets can be troublesome on standard desktop computers. This challenge has resulted in numerous works that aim to provide high performance computing solutions to large data, high resolution data, or both. This work proposes an efficient watershed delineation algorithm for use in desktop computing environments that leverages existing data, U.S. Geological Survey (USGS) National Hydrography Dataset Plus (NHD_+), and open source software tools to construct watershed boundaries. This approach makes use of U.S. national-level hydrography data that has been precomputed using raster processing algorithms coupled with quality control routines. Our approach uses carefully arranged data and mathematical graph theory to traverse river networks and identify catchment boundaries. We demonstrate this new watershed delineation technique, compare its accuracy with traditional algorithms that derive watershed solely from digital elevation models, and then extend our approach to address subwatershed delineation. Our findings suggest that the open-source hierarchical network-based delineation procedure presented in the work is a promising approach to watershed delineation that can be used summarize publicly available datasets for hydrologic model input pre-processing. Through our analysis, we explore the benefits of reusing the NHD_+ datasets for watershed delineation, and find that the our technique offers greater flexibility and extendability than traditional raster algorithms.
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In this paper, the author presents a novel information extraction system that analyses fire service reports. Although the reports contain valuable information concerning fire and rescue incidents, the narrative information in thes...
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In this paper, the author presents a novel information extraction system that analyses fire service reports. Although the reports contain valuable information concerning fire and rescue incidents, the narrative information in these reports has received little attention as a source of data. This is because of the challenges associated with processing these data and making sense of the contents through the use of machines. Therefore, a new issue has emerged: How can we bring to light valuable information from the narrative portions of reports that currently escape the attention of analysts? The idea of information extraction and the relevant system for analysing data that lies outside existing hierarchical coding schemes can be challenging for researchers and practitioners. Furthermore, comprehensive discussion and propositions of such systems in rescue service areas are insufficient. Therefore, the author comprehensively and systematically describes the ways in which information extraction systems transform unstructured text data from fire reports into structured forms. Each step of the process has been verified and evaluated on real cases, including data collected from the Polish Fire Service. The realisation of the system has illustrated that we must analyse not only text data from the reports but also consider the data acquisition process. Consequently, we can create suitable analytical requirements. Moreover, the quantitative analysis and experimental results verify that we can (1) obtain good results of the text segmentation (F-measure 95.5%) and classification processes (F-measure 90%) and (2) implement the information extraction process and perform useful analysis.
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A new image analysis method, called contiguous volume analysis, has been developed to automatically extract 3D information from emission images. The method considers volumes of activity and displays data about them in a format whi...
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A new image analysis method, called contiguous volume analysis, has been developed to automatically extract 3D information from emission images. The method considers volumes of activity and displays data about them in a format which allows quantitative image comparison. This method of numerical analysis enables the authors to show, for example, whether or not information has been gained, lost or changed through the use of different filters and different attenuation and scatter correction, and reconstruction algorithms. Since the analysis method is consistent with a visual inspection of the data, intuitive insights into the meaning of the data are possible, allowing a better understanding of the effects of the different image processing techniques on the images. The method can be used to find patterns of activity in sets of images, and may be used to quantify noise, allowing an objective determination of which volumes in an image are meaningful.
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Purpose - Information overload has led to a situation where users are swamped with too much information, resulting in difficulty sifting through material in search of relevant content. Aims to address this issue from the perspecti...
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Purpose - Information overload has led to a situation where users are swamped with too much information, resulting in difficulty sifting through material in search of relevant content. Aims to address this issue from the perspective of collaborative querying, an approach that helps users formulate queries by harnessing the collective knowledge of other searchers. Design/methodology/approach - The design and implementation of the Query Graph Visualizer (QGV), a collaborative querying system which harvests and clusters previously issued queries to form query networks that represent related information needs are described. A preliminary evaluation of the QGV is also described in which a group of participants evaluated the usability and usefulness of the system by completing a set of tasks and a questionnaire based on Nielsen's heuristic evaluation technique. Findings - In the QGV, a submitted query is matched to its closest cluster and a recursive algorithm is applied to find other related clusters, forming a query network. The queries in the network are explored in the QGV, helping users locate other queries that might meet their current information needs. The results of the evaluation suggest the usefulness and usability of the system. Participants could complete their assigned tasks using the QGV and positively rated the system in terms of usability. Originality/value - The techniques described can be used to design information retrieval systems that learn from the trials and tribulations of other searchers and help users in their quest for relevant and quality information.
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This paper extends possibilities for analyzing incomplete ordinal information about the parameters of an additive value function. Such information is modeled through preference statements which associate sets of alternatives or at...
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This paper extends possibilities for analyzing incomplete ordinal information about the parameters of an additive value function. Such information is modeled through preference statements which associate sets of alternatives or attributes with corresponding sets of rankings. These preference statements can be particularly helpful in developing a joint preference representation for a group of decision-makers who may find difficulties in agreeing on numerical parameter values. Because these statements can lead to a non-convex set of feasible parameters, a mixed integer linear formulation is developed to establish a linear model for the computation of decision recommendations. This makes it possible to complete incomplete ordinal information with other forms of incomplete information.
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Although the entropy of a given signal-type waveform is technically zero, it is nonetheless desirable to use entropic measures to quantify the associated information. Several such prescriptions have been advanced in the literature...
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Although the entropy of a given signal-type waveform is technically zero, it is nonetheless desirable to use entropic measures to quantify the associated information. Several such prescriptions have been advanced in the literature but none are generally successful. Here, we report that the Fourier-conjugated 'total entropy' associated with quantum-mechanical probabilistic amplitude functions (PAFs) is a meaningful measure of information in non-probabilistic real waveforms, with either the waveform itself or its (normalized) analytic representation acting in the role of the PAF. Detailed numerical calculations are presented for both adaptations, showing the expected informatic behaviours in a variety of rudimentary scenarios. Particularly noteworthy are the sensitivity to the degree of randomness in a sequence of pulses and potential for detection of weak signals.
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