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This paper sets out to discuss the use of information extraction (IE), a natural language‐processing (NLP) technique to assist “rich” semantic indexing of diverse archaeological text resources. The focus of the research is to direct a semantic‐aware “rich” indexing of diverse natural language resources with properties capable of satisfying information retrieval from online publications and datasets associated with the Semantic Technologies for Archaeological Resources (STAR) project.

The paper proposes use of the English Heritage extension (CRM‐EH) of the standard core ontology in cultural heritage, CIDOC CRM, and exploitation of domain thesauri resources for driving and enhancing an Ontology‐Oriented Information Extraction process. The process of semantic indexing is based on a rule‐based Information Extraction technique, which is facilitated by the General Architecture of Text Engineering (GATE) toolkit and expressed by Java Annotation Pattern Engine (JAPE) rules.

Initial results suggest that the combination of information extraction with knowledge resources and standard conceptual models is capable of supporting semantic‐aware term indexing. Additional efforts are required for further exploitation of the technique and adoption of formal evaluation methods for assessing the performance of the method in measurable terms.

The value of the paper lies in the semantic indexing of 535 unpublished online documents often referred to as “Grey Literature”, from the Archaeological Data Service OASIS corpus (Online AccesS to the Index of archaeological investigationS), with respect to the CRM ontological concepts E49.Time Appellation and P19.Physical Object.

This study aims to investigate the main drivers of private saving in Egypt (2005–2020).

It employs an autoregressive distributed lag (ARDL) approach for quarterly data on private saving, lagged private saving, real gross domestic product (GDP) growth, public saving, inflation, real interest rate, money supply, current account deficit and unemployment.

Private saving in Egypt displays persistency and public saving depresses private saving in the short run and long run. Real interest rate, inflation and unemployment have negative and statistically significant impacts on private saving in the short run and long run. The current account deficit displays a negative effect on private saving but is significant only in the short run. Other incorporated variables, like real GDP and money supply, are not statistically significant. This could be attributed to the high consumption rather than saving motive of the Egyptian population and their tendency to rely more on other informal saving channels.

Findings are of policy relevance as unleashing the determinants of private saving guides policymakers in formulating the appropriate sustainable development policies. It also assists in identifying the main obstacles hindering the promotion of private saving and hence major areas for policy intervention, like financial inclusion, poverty eradication, employment generation and structural reforms.

This study contributes to the literature: (1) it tackles private saving figure rather than aggregate saving figure that is covered by similar studies due to lack of consistent data, (2) given the relatively low quality, unavailability and inconsistency of data on private saving in developing countries, investigating the determinants of private saving should be carried out on an individual country basis which is done by this study, (3) this study fulfills the gap in literature related to the lack of up-to-date studies on private saving in Egypt and (4) it relies on quarterly data that could produce more reliable results.

Significant evidence in the literature points to money demand instability and therefore inaccurate forecasting. In view of this issue, this chapter seeks to use a method, innovative for money demand literature, that is, the machine learning model to predict money demand. Specifically, this chapter uses Random Forest Regression to predict money demand using monthly data in the Indian context over the period April-1996 to December-2018 using the variables usually used in literature. The chapter finds that in money demand prediction, the Random Forest Regression performs fairly well. The results are also compared to traditional models and it is found that the Random Forest Regression model has the potential to enhance the prediction of money demand over what traditional models predicts.

The emerging market economies, in particular, have become victim to the laundering activities which have damaged investment potentials, undermined governance, fostered crime and corruption, and decreased tax revenues. In this chapter, we construct a macrotheoretic framework to analyze money laundering in the form of tax evasion by individuals in an economy in the events of financial autarky and free trade. In other words, our theoretical model allows us to examine if movement from autarky to a state of financial integration whets the degree of financial malpractice like money laundering.

This study deals with waste in New Product Development (NPD) processes of SMEs. The purpose of this paper is to reveal opportunities for SMEs to overcome resource constraints in their NPD process.

The authors employed qualitative key informant interviews. This design was chosen because research in this field is still limited. The authors performed 49 interviews in engineering-oriented German SMEs to examine the dimension of waste in NPD processes. The data were collected by conducting semi-structured, face-to-face interviews.

The study highlights substantial waste types such as waiting times, rework and duplication of work. In contrast to contemporary literature, waste of material is considered to be relevant in particular for NPD processes of SMEs. In addition to that, the authors found that waste drivers differ to a great extent between the study and the hitherto literature on larger companies.

The overall outcome of this study can help organisations to address waste in NPD more thoroughly. The research presented was not specifically designed to draw statistical generalisations. For this reason, the results may not be applicable to all SMEs.

Based on waiting times as the major waste type in NPD processes of SMEs, the authors claim that firms should pay special attention to disruptions of these processes.

The paper gives insights into current waste types in the NPD processes of SMEs. Moreover, it uncovers the NPD activities which can lead to waste.

With the spread of the coronavirus disease across over 100 countries and its status upgraded to that of a pandemic on 11 March 2020 (World Health Organization), increased attention is being placed on the policy measures that may be required to effectively curb the rate of contagion within and across countries. Currently, several governments, such as China, Italy, Spain, Japan and the Republic of Korea, have implemented emergency measures informed by the principle of social distancing to limit the spread of coronavirus (World Health Organization). Ever since the virus was first identified in Wuhan City in December 2019, this succession of uncoordinated policy responses offers a set of natural experiments that should be analysed to understand the successes and failures of containment at the societal level. In this analysis, we focus on the case of Italy, the hardest hit country in Europe (Dong, Du, & Gardner, 2020; World Health Organization). The objective of this short note is to provide an even-handed analysis of the actions taken by the Italian government to cope with the transmission of the virus and to highlight lessons in emergency management that can be learnt for other countries currently facing the onset of the Covid-19 epidemic.

Highlights a number of developments in Europe that have been important in the evolution of the relationship between the rules for computing profits for tax and accounting purposes. This will assist users in their understanding of European financial reports and will highlight areas where particular caution is required when analysing financial statements over an extended period. Recent changes in the UK are put forward as an alternative to breaking the tax link, and a possible avenue for promoting the harmonization of taxation as well as financial reporting.

Predicting a patient's length of stay (LOS) in a hospital setting has been widely researched. Accurately predicting an individual's LOS can have a significant impact on a healthcare provider's ability to care for individuals by allowing them to properly prepare and manage resources. A hospital's productivity requires a delicate balance of maintaining enough staffing and resources without being overly equipped or wasteful. This has become even more important in light of the current COVID-19 pandemic, during which emergency departments around the globe have been inundated with patients and are struggling to manage their resources.

In this study, the authors focus on the prediction of LOS at the time of admission in emergency departments at Rhode Island hospitals through discharge data obtained from the Rhode Island Department of Health over the time period of 2012 and 2013. This work also explores the distribution of discharge dispositions in an effort to better characterize the resources patients require upon leaving the emergency department.

This chapter provides a comprehensive review of research and developments relating to the use of Web 2.0 technologies in education. As opposed to early educational uses of the Internet involving publication of static information on web pages, Web 2.0 tools offer a host of opportunities for educators to provide more interactive, collaborative, and creative online learning experiences for students. The chapter starts by defining Web 2.0 tools in terms of their ability to facilitate online creation, editing, and sharing of web content. A typology of Web 2.0 technologies is presented to illustrate the wide variety of tools at teachers’ disposal. Educational uses of Web 2.0 technologies such as wikis, blogs, and microblogging are explored, in order to showcase the variety of designs that can be utilized. Based on a review of the research literature the educational benefits of using Web 2.0 technologies are outlined, including their ability to facilitate communication, collaborative knowledge building, student-centered activity, and vicarious learning. Similarly, issues surrounding the use of Web 2.0 tools are distilled from the literature and discussed, such as the possibility of technical problems, collaboration difficulties, and plagiarism. Two case studies involving the use Web 2.0 tools to support personalized learning and small group collaboration are detailed to exemplify design possibilities in greater detail. Finally, design recommendations for learning and teaching using Web 2.0 are presented, again based on findings from the research literature.