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Article
Publication date: 1 June 1987

Adrian R. Haas

This article seeks to review the provision of vocational education available to para‐professional‐level engineering personnel in Australia. This stratum of personnel corresponds…

27

Abstract

This article seeks to review the provision of vocational education available to para‐professional‐level engineering personnel in Australia. This stratum of personnel corresponds to those described as technician‐engineers in the UK.

Details

Journal of European Industrial Training, vol. 11 no. 6
Type: Research Article
ISSN: 0309-0590

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Article
Publication date: 1 May 1978

Adrian R. Haas

This article reviews an attempt by Chinese industry to train skilled technicians during the past ten years. It discusses an alternative to formal tertiary education and comments…

35

Abstract

This article reviews an attempt by Chinese industry to train skilled technicians during the past ten years. It discusses an alternative to formal tertiary education and comments on the success of the July 21st Colleges.

Details

Journal of European Industrial Training, vol. 2 no. 5
Type: Research Article
ISSN: 0309-0590

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Article
Publication date: 20 July 2023

Qais K. Jahanger, David Trejo and Joseph Louis

The health of an economy is heavily dependent on the productivity of the economy's major industries including construction. While most macro-measures of productivity in the USA…

291

Abstract

Purpose

The health of an economy is heavily dependent on the productivity of the economy's major industries including construction. While most macro-measures of productivity in the USA construction industry indicate a decline, corresponding studies at the individual task level indicate an increase in productivity. Therefore, this paper aims to identify areas where productivity challenges exist and thus provide recommendations for improvement in the construction industry.

Design/methodology/approach

A model that relates the way construction projects are executed with the sources of data that inform productivity analyses is developed and presented. This effort/value-flow model informs the data analysis that is performed to determine productivity trends for management and field labor. Further analysis for field labor productivity using field data and management productivity was separately conducted. Management productivity was particularly difficult to gauge, resulting in the use of surrogate measures.

Findings

It was observed that while both field labor and management productivities at the industry level have been decreasing, the decrease in management productivity was five times that of field labor productivity. A similar trend was observed for management productivity at the project level.

Originality/value

The primary contribution of this paper to the body of knowledge and industry is the introduction of a holistic analysis of USA construction productivity. Recommendations to improve management productivity include the use of technology, especially project management software.

Details

Engineering, Construction and Architectural Management, vol. 32 no. 1
Type: Research Article
ISSN: 0969-9988

Keywords

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Book part
Publication date: 4 December 2018

Indranarain Ramlall

Abstract

Details

Tools and Techniques for Financial Stability Analysis
Type: Book
ISBN: 978-1-78756-846-4

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Article
Publication date: 1 January 1975

Frances Neel Cheney

Communications regarding this column should be addressed to Mrs. Cheney, Peabody Library School, Nashville, Tenn. 37203. Mrs. Cheney does not sell the books listed here. They are…

76

Abstract

Communications regarding this column should be addressed to Mrs. Cheney, Peabody Library School, Nashville, Tenn. 37203. Mrs. Cheney does not sell the books listed here. They are available through normal trade sources. Mrs. Cheney, being a member of the editorial board of Pierian Press, will not review Pierian Press reference books in this column. Descriptions of Pierian Press reference books will be included elsewhere in this publication.

Details

Reference Services Review, vol. 3 no. 1
Type: Research Article
ISSN: 0090-7324

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Article
Publication date: 1 May 1981

Bayer AG has become the latest company to license from Rohm and Haas their patented technology on low profile polyester resin systems.

15

Abstract

Bayer AG has become the latest company to license from Rohm and Haas their patented technology on low profile polyester resin systems.

Details

Pigment & Resin Technology, vol. 10 no. 5
Type: Research Article
ISSN: 0369-9420

Available. Open Access. Open Access
Article
Publication date: 26 April 2024

Adela Sobotkova, Ross Deans Kristensen-McLachlan, Orla Mallon and Shawn Adrian Ross

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite…

668

Abstract

Purpose

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Design/methodology/approach

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Findings

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Research limitations/implications

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Practical implications

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Social implications

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Originality/value

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

Details

Journal of Documentation, vol. 80 no. 5
Type: Research Article
ISSN: 0022-0418

Keywords

Available. Open Access. Open Access
Article
Publication date: 1 September 2023

Dhulika Arora and Smita Kashiramka

Shadow banks or non-bank financial intermediaries (NBFIs) are facilitators of credit, especially in emerging market economies (EMEs). However, there are certain risks associated…

1714

Abstract

Purpose

Shadow banks or non-bank financial intermediaries (NBFIs) are facilitators of credit, especially in emerging market economies (EMEs). However, there are certain risks associated with them, such as their unchecked leverage and interconnectedness with the rest of the financial system. In light of this, the present study analyses the impact of the growth of shadow banks on the stability of the banking sector and the overall stability of the financial system. The authors further examine the effect of the growth of finance companies (a type of NBFIs) on financial stability.

Design/methodology/approach

The study employs data of 11 EMEs (monitored by the Financial Stability Board (FSB)) for the period 2002–2020 to examine the above relationships. Panel-corrected standard errors method and Driscoll–Kray standard error estimation are deployed to conduct the analysis.

Findings

The results signify that the growth of the shadow banking sector and the growth of lending to the shadow banking sector are negatively associated with the stability of the banking sector and increases the vulnerability of the financial system (overall instability). This implies that the higher the growth of the shadow banks, the higher the financial fragility. Finance companies are also found to negatively affect financial stability. These findings are validated by different estimation methods and point out the risks posed by the NBFI sector.

Originality/value

The extant study builds a composite index (Financial Vulnerability Index (FVI)) to measure financial stability; thus, the findings contribute to the evolving literature on shadow banks.

Details

China Accounting and Finance Review, vol. 25 no. 4
Type: Research Article
ISSN: 1029-807X

Keywords

Available. Content available
Book part
Publication date: 11 December 2023

Gráinne Perkins

Free Access. Free Access

Abstract

Details

Danger in Police Culture
Type: Book
ISBN: 978-1-83753-113-4

Available. Content available
Book part
Publication date: 14 November 2016

Robert H. Herz

Free Access. Free Access

Abstract

Details

More Accounting Changes
Type: Book
ISBN: 978-1-78635-629-1

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