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The purpose of this paper is to examine the influence of reference data, input address quality, and crime type on completeness and positional accuracy of street geocoded crime events.

Existing data were analyzed using ArcGIS, including crime incident information, street network reference data, and address point and/or parcel reference data. Geocoding completeness was determined by the overall match rate. Positional accuracy was determined by comparing the Euclidian distance between street geocoded locations of crime events to the corresponding address point/parcel geocoded location.

Results indicate that match rates vary by reference data, input address quality, and crime type. Local street centerline files consistently produced match rates that were as good as – and in many cases superior to – other types of reference data, including commercial data. Greater variability in positional accuracy was observed across reference data when crime type and input address quality was considered, but results were consistent with positional accuracy analysis conducted using data from other disciplines.

Results provide researchers and practitioners with valuable guidance and insight into one of the most basic – albeit fundamental – procedures related to the spatio‐temporal analysis of crime, suggesting that reference data required to produce geocoded crime incidents successfully and of high quality does not necessarily mean a large financial investment on the part of law enforcement agencies or researchers interested in the geospatial analysis of crime.

Prior to this investigation, a comprehensive examination of the impact of data quality on geocoded crime events was absent from the literature.

Reference data collection tools facilitate the collection of in‐depth data about reference interactions. Since this information may influence decisions, library managers should examine how these tools are used and assess how these data entry behaviors may impact the accuracy of the data. This paper aims to analyze reference staff perceptions and data entry behaviors using a reference data collection tool.

The two‐year mixed method study analyses reference staff perceptions and data entry behaviors related to the reference data collection tool used at the University of Colorado Boulder Libraries. The authors identified six distinct data entry behaviors for analysis in this study.

The survey results indicate that staff consider the tool to be both easy to use and useful. These findings, under the technology acceptance model, indicate technology acceptance, which influences adoption and use of the tool. Though rates of adoption and use of the tool are high, the authors' analysis of behaviors indicate that not all users record reference interactions in the same way, and this inconsistency may impact the accuracy of collected data.

Inconsistency in data entry behaviors should inform the design of staff training sessions, best practice guidelines, and the tool's interface.

If data are used to justify changes to services and collections, decision makers need to be confident that data accurately reflect activity at library service points.

Previous studies related to reference data collection mention the importance of consistent data entry practices, but no studies have explicitly evaluated how inconsistencies in use may impact the accuracy of data.

Cartosat‐1 is the first Indian Remote Sensing satellite, developed for topographic mapping, able to collect in‐track high‐resolution stereo images with a 2.5 m pixel size. In the framework of the Cartosat‐1 Scientific Assessment Programme (C‐SAP), the Politecnico di Milano University (Italy) evaluated the performances of the Cartosat‐1 satellite in the generation of digital terrain models (DTMs) from stereo‐couples. The purpose of this paper is to describe in detail the outcomes for the Salon de Provence (France) test site, with respect to existing standards and products actually used in France and also to provide a comparison with the global Shuttle Radar Topography Mission's DTM freely available from by NASA.

The Cartosat‐1 data processing was done using the commercial off‐the‐shelf software ENVI®, selected for investigating the capabilities and limits of the system using standard image processing tools, so from the point of view of a typical remote sensing user. The data processing involved the following aspects: data pre‐processing; optimization of the DTM's extraction procedure; analysis of the influence of ground control points' (GCPs) in the generated DTMs; analysis of the influence of the DTM's resolution in the elevation accuracy; and post‐processing refinement.

When generating relative DTMs an error was observed in elevation of some hundreds of meters. After georeferencing, the root mean square error (RMSE) was between 9.0 and 14.2 m and the LE90 between 16.1 and 19.0 m. When generating absolute DTMs, the optimum number of GCPs was found to be 9, with a regular geometric distribution (4.6 m RMSE and 6.5 m LE90 for 10 m grid cell size). Post‐processing may be applied to enhance results (1.6 m RMSE and 2.0 m LE90 for 10 m grid cell size). In this case, the absolute DTMs fulfilled and also overcame the standards required for the IGNs and Spot Image's Reference 3D®.

This paper describes the outcomes of the C‐SAP led by the International Society for Photogrammetry and Remote Sensing and the Indian Space Research Organisation for evaluating the capabilities of the last Cartosat‐1 satellite. The aim is to provide remote sensing users a comprehensive study about the potentialities and limits of the Cartosat‐1 images for multi‐resolution DTM generation (from 5 to 90 m grid cell size).

To gain an in-depth understanding and provide direction to governments on their quality measurement practices related to open government data (OGD), this paper aims to develop a common frame of reference for quality assessment of OGD.

Qualitative meta-synthesis was used to synthesize previous studies on the quality measurement of OGD. This paper applies a meta-synthesis approach to integrate 10 qualitative studies into a common frame of reference for quality assessment of OGD.

Based on a seven-step meta-synthesis, the paper proposes a common frame of reference for quality assessment of OGD, which includes six indicators, namely, accuracy, accessibility, completeness, timeliness, consistency and understandability.

A common frame of reference for quality assessment of OGD will help researchers better understand the quality assessment of OGD and government agencies to improve the quality of OGD that they publish.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

The purpose of this paper is to understand sustainability assurance (SA), and diversity in that practice, by examining assurance providers’ understandings of the practice and the influences that those understandings have on the actual assurance process. It focuses on the issues beyond the content of statements in SA reports.

This paper employs semi-structured interviews, supplemented by textual data sources. Research participants are assurance providers in the UK, including those within and outside the accounting profession. Drawing on the perspective of actor-network theory, the study focuses on the associations between different actors and how those shape the assurance practice.

The findings indicate that providers’ understandings of SA practice vary significantly. This variation has a major effect on how the assurance practice is conducted. The study identifies four types of SA engagements, which are designated as: social assurance, integrated assurance, formative assurance and compliance assurance. Such a categorization provides a broad-based understanding of the operationalization of SA and the degree of heterogeneity within it.

This paper extends the understanding of SA by focusing on the practice beyond the statements made by assurance providers, which have been the predominant focus of analysis in the existing literature, and by offering a categorization of the diversity in practice. The focus on the associations between assurance providers and other actors provides a new perspective for exploring the fundamentals of the practice.

The purpose of this study is three-dimensional flow and heat transfer investigation of water/Al₂O₃ nanofluid inside a microchannel with different cross-sections in two-phase mode.

The effect of microchannel walls geometry (trapezoidal, sinusoidal and stepped microchannels) on flow characteristics and also changing circular cross section to trapezoidal cross section in laminar flow at Reynolds numbers of 50, 100, 300 and 600 were investigated. In this study, two-phase water/Al₂O₃ nanofluid is simulated by the mixture model, and the effect of volume fraction of nanoparticles on performance evaluation criterion (PEC) is studied. The accuracy of obtained results was compared with the experimental and numerical results of other similar papers.

Results show that in flow at lower Reynolds numbers, sinusoidal walls create a pressure drop in pure water flow which improves heat transfer to obtain PEC < 1. However, in sinusoidal and stepped microchannel with higher Reynolds numbers, PEC > 1. Results showed that the stepped microchannel had higher pressure drop, better thermal performance and higher PEC than other microchannels.

Review of previous studies showed that existing papers have not compared and investigated nanofluid in a two-phase mode in inhomogeneous circular, stepped and sinusoidal cross and trapezoidal cross-sections by considering the effect of changing channel shape, which is the aim of the present paper.

The purpose of this chapter is to review the accumulated research on a strategically important intangible asset – organizational reputation – and articulate promising research pathways forward. To do so, I first provide definitional clarity by comparing reputation to the related constructs of status, celebrity, legitimacy, and social approval and highlight the codifiable, cumulative, and beneficial nature of reputation. I then discuss three developments in reputation literature: (1) conceptualizing reputation as a multidimensional, rather than generalized, construct; (2) theorizing about reputational malleability rather than its path dependence; and (3) focusing on the costs of a high reputation in addition to its benefits. Based on these developments and the increasing role of social media in affecting and reflecting stakeholder perceptions, I discuss three pathways for future reputation research. Specifically, I focus on the decrease in credibility of powerful intermediaries and increase in stakeholder empowerment, conceptualization of reputation as a flow rather than a stock, and the role of strategic reticence. My hope is that this chapter will stimulate conceptual and empirical work on the role of reputation in the complex and dynamic era of social media.

This study aims to fabricate and study the effect of five cumulative graphite (G) and graphite nanoplatelets (GNP) filler loading composites by polymerising PA6 precursor; monomer epsilon caprolactam with the two carbons in situ while taking cognisance of the mixing effects (simultaneous stirring and sonication at varying amplitudes and duration). Different aspect ratios will be used to model the two streams of polymerisations.

High viscosity extrusion grade PA6 and synthetic G of less than 2 µm particle size were used as fillers. GNP and G are dried for 6 h in vacuum oven at 90°C. Prior to in situ polymerisation, probe sonication was applied to disperse fillers in molten ɛ-caprolactam, the PA6 monomer. Five carbon loadings were made, that is 5–25 Wt.% for G and 0.5–2.5 Wt.% for GNP composites. Two different sonification regimes were applied 20% sonication amplitude for 20 min (20/20) and 40% sonication amplitude for 10 min (40/10).

Better tensile properties were achieved using the 20/20 processing streams for both G and GNP. The G- and the GNP-based composites systems of the 20/20 processing stream had tensile modulus and yield strength retained or improved above the unfilled PA6 value. The highest modulus obtained in the 20/20 streams are 1,878 and 1,201 MPa, respectively, for GNP and G at the highest loading levels, while the 40/10 processing streams had 963 and 1,247 MPa, respectively, for the GNP and G.

To the best of the authors’ knowledge, nobody has ever used sonification amplitude to compare mechanical properties.