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Article
Publication date: 10 July 2009

William Riddell, Krishan Kumar Bhatia, Matthew Parisi, Jessica Foote and John Imperatore

The purpose of this paper is to assess the carbon dioxide emissions associated with electric, HVAC, and hot water use from a US university.

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Abstract

Purpose

The purpose of this paper is to assess the carbon dioxide emissions associated with electric, HVAC, and hot water use from a US university.

Design/methodology/approach

First, the total on‐campus electrical, natural gas and oil consumption for an entire year was assessed. For each category of energy use, the carbon associated with consumption of a single unit was calculated. Using this, the total carbon dioxide emissions for the entire university were estimated.

Findings

It was found that the university's activities resulted in approximately 4 tons of carbon dioxide emissions per student per year. In total, the university emitted nearly 38,000 tons of carbon dioxide during the 2007 fiscal year. In addition, it was found that emissions from on‐campus steam production, which account for roughly 57 per cent of total CO2 emissions, would be improved with the addition of two proposed cogeneration facilities.

Originality/value

The originality and value of this paper is attributed to: the recent international concern over CO2 emissions and their global warming impact; the increasing adoption of the American College & University Presidents' Climate Commitment which in part calls for an inventory of campus emissions; and the underdeveloped research area relating to total university campus carbon footprint estimation.

Details

International Journal of Sustainability in Higher Education, vol. 10 no. 3
Type: Research Article
ISSN: 1467-6370

Keywords

Available. Content available
Article
Publication date: 10 July 2009

Dr Judy Walton

645

Abstract

Details

International Journal of Sustainability in Higher Education, vol. 10 no. 3
Type: Research Article
ISSN: 1467-6370

Available. Open Access. Open Access
Article
Publication date: 30 January 2012

Teresa Di Filippo, Lucia Parisi and Michele Roccella

Impairment of intelligence in Duchenne muscular dystrophy (DMD) patients was described by Duchenne de Boulogne himself in 1868. Further studies report intelligence disorders with…

747

Abstract

Impairment of intelligence in Duchenne muscular dystrophy (DMD) patients was described by Duchenne de Boulogne himself in 1868. Further studies report intelligence disorders with mayor impairment of memory. The aim of the present study was to assess the presence of affective and personality disorders in a group of children affected by DMD. Twenty six male DMD patients, mean age eleven and four months years old, were assessed for their affective and personality disorder. Only eight subjects had a total IQ below average with major difficulties in verbal and visual-spatial memory, comprehension, arithmetic and vocabulary. All the subjects presented some disorders: tendency to marginalization and isolation, self-depreciation, sense of insecurity, hypochondriac thoughts and marked state of anxiety. These disorders are often a dynamic prolongation of a psychological process which starts when the diagnosis is made and continues, in a slow and latent fashion, throughout the evolution of the disease.

Details

Mental Illness, vol. 4 no. 1
Type: Research Article
ISSN: 2036-7465

Keywords

Available. Open Access. Open Access
Article
Publication date: 10 October 2024

Fabiane Letícia Lizarelli, Artur Yuiti Ishizaka and José Carlos de Toledo

The objectives of this study are to identify which inputs are most relevant for development and successful introduction of product and process innovations and identify the impacts…

295

Abstract

Purpose

The objectives of this study are to identify which inputs are most relevant for development and successful introduction of product and process innovations and identify the impacts of these two types of innovation on the performance of Brazilian manufacturing companies.

Design/methodology/approach

This study analyzes the relationships between input, output and outcome for a sample of 5,586 Brazilian manufacturing companies by using partial least squares structural equation modeling (PLS-SEM).

Findings

The results indicate that (1) product innovations are favored by internal resources, (2) process innovations are favored by external resources, (3) product innovations mainly affect a range of products offered by companies and (4) process innovations mainly affect performance in manufacturing capacity, flexibility and costs.

Practical implications

By identifying the main efforts to improve the innovation performance and input-output-outcome relationships, the results can contribute to a better decision-making process for innovation investments and management in companies as well as for policymakers. The results are particularly relevant given that the Brazilian case can serve as a reference for other emerging countries.

Originality/value

Analyses of the innovation in input-output-outcome relationships were performed in a comprehensive way by using a set of variables for defining each construct. This allowed each construct to be better measured, which improved the understanding of the relationships between inputs and outcomes mediated by product and process innovations.

Details

Innovation & Management Review, vol. 21 no. 4
Type: Research Article
ISSN: 2515-8961

Keywords

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Article
Publication date: 17 January 2022

Syed Haroon Abdul Gafoor and Padma Theagarajan

Conventional diagnostic techniques, on the other hand, may be prone to subjectivity since they depend on assessment of motions that are often subtle to individual eyes and hence…

130

Abstract

Purpose

Conventional diagnostic techniques, on the other hand, may be prone to subjectivity since they depend on assessment of motions that are often subtle to individual eyes and hence hard to classify, potentially resulting in misdiagnosis. Meanwhile, early nonmotor signs of Parkinson’s disease (PD) can be mild and may be due to variety of other conditions. As a result, these signs are usually ignored, making early PD diagnosis difficult. Machine learning approaches for PD classification and healthy controls or individuals with similar medical symptoms have been introduced to solve these problems and to enhance the diagnostic and assessment processes of PD (like, movement disorders or other Parkinsonian syndromes).

Design/methodology/approach

Medical observations and evaluation of medical symptoms, including characterization of a wide range of motor indications, are commonly used to diagnose PD. The quantity of the data being processed has grown in the last five years; feature selection has become a prerequisite before any classification. This study introduces a feature selection method based on the score-based artificial fish swarm algorithm (SAFSA) to overcome this issue.

Findings

This study adds to the accuracy of PD identification by reducing the amount of chosen vocal features while to use the most recent and largest publicly accessible database. Feature subset selection in PD detection techniques starts by eliminating features that are not relevant or redundant. According to a few objective functions, features subset chosen should provide the best performance.

Research limitations/implications

In many situations, this is an Nondeterministic Polynomial Time (NP-Hard) issue. This method enhances the PD detection rate by selecting the most essential features from the database. To begin, the data set's dimensionality is reduced using Singular Value Decomposition dimensionality technique. Next, Biogeography-Based Optimization (BBO) for feature selection; the weight value is a vital parameter for finding the best features in PD classification.

Originality/value

PD classification is done by using ensemble learning classification approaches such as hybrid classifier of fuzzy K-nearest neighbor, kernel support vector machines, fuzzy convolutional neural network and random forest. The suggested classifiers are trained using data from UCI ML repository, and their results are verified using leave-one-person-out cross validation. The measures employed to assess the classifier efficiency include accuracy, F-measure, Matthews correlation coefficient.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 15 no. 4
Type: Research Article
ISSN: 1756-378X

Keywords

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Book part
Publication date: 27 April 2023

Nicola Capolupo

Abstract

Details

Entrepreneurial Learning Evolutions in Startup Hubs: A Post-Pandemic Perspective for Lean Organizations
Type: Book
ISBN: 978-1-83753-070-0

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Article
Publication date: 6 April 2021

Rahmatina Awaliah Kasri and Adela Miranti Yuniar

This study aims to determine the factors that influence the intention to use online platforms in paying zakat in Indonesia.

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Abstract

Purpose

This study aims to determine the factors that influence the intention to use online platforms in paying zakat in Indonesia.

Design/methodology/approach

This study used the extended unified theory of acceptance and use of technology as the theoretical framework, where zakat literacy is added to the model’s main components (i.e. performance expectancy, effort expectancy, facilitating condition and social influence). Primary data was collected through an online survey involving 223 Indonesian Muslims who have used various online channels to pay zakat and analyzed by using structural equation modeling as the empirical approach.

Findings

The findings indicate that performance expectancy, effort expectancy, facilitating condition and zakat literacy significantly affect the intention to use an online platform to pay zakat in Indonesia. However, social influence is found to be insignificant in this study.

Research limitations/implications

The study used a relatively small sample size compared to the Indonesian population’s size. Thus, the results must be interpreted with the sample observed.

Practical implications

Zakat organizations should make sure that their system is easy for people to make an online zakat payment, as easy access is the most important factor influencing the intention to pay zakat online. They must also increase efficiency and effectiveness of the payment system, enhance quality of the organizational and technical infrastructures and contribute to improving zakat literacy together with other zakat stakeholders.

Originality/value

This study offers new insights related to the quantitative study on digital zakat and behavior of zakat payers, particularly in Indonesia.

Details

Journal of Islamic Accounting and Business Research, vol. 12 no. 3
Type: Research Article
ISSN: 1759-0817

Keywords

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Book part
Publication date: 15 October 2018

M. Selim Yavuz

After the extreme turn of the late 1980s and early 1990s of metal music, three northern England-based bands – My Dying Bride and Paradise Lost from Bradford, and Anathema from…

Abstract

After the extreme turn of the late 1980s and early 1990s of metal music, three northern England-based bands – My Dying Bride and Paradise Lost from Bradford, and Anathema from Liverpool, commonly referred to as ‘the Peaceville Three’ – went on to pioneer the musical style which came to be known as death/doom. Mid-1990s have seen these bands’ stylistic shift into a more gothic rock-influenced sound. This Paradise Lost-led shift gave birth to the style gothic/doom. Around this deviation, these bands also started to employ a different sense, or rather a sense, of locality in their music: Paradise Lost started calling themselves a Yorkshire band, instead of specifically Bradford; Anathema shot a video for their 1995 song ‘The Silent Enigma’ in Saddleworth Moor (historically part of West Riding of Yorkshire) in Manchester; and later, My Dying Bride became more and more ingrained in the Goth culture of Whitby, including releasing an extended-play titled The Barghest o’ Whitby (2011), a Dracula-inspired trail guide, and frequently appearing in festivals in Whitby. This ethnographic research with both musicians and fans further suggests the involvement of the North in making and perception of gothic/doom. Applying Michel de Certau’s idea stating that ‘every story is a spacial practice’ within the context of northern England landscape, gothic/doom metal style emerges as an act of northernness. The author proposes to discuss how this act is performed within these bands’ oeuvre and how it is perceived from the listener perspective using interviews with people from around the world, and musicological analyses of significant songs from the repertoire of this trio.

Details

Subcultures, Bodies and Spaces: Essays on Alternativity and Marginalization
Type: Book
ISBN: 978-1-78756-512-8

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Article
Publication date: 4 October 2022

Carolyn Caffrey, Hannah Lee, Tessa Withorn, Maggie Clarke, Amalia Castañeda, Kendra Macomber, Kimberly M. Jackson, Jillian Eslami, Aric Haas, Thomas Philo, Elizabeth Galoozis, Wendolyn Vermeer, Anthony Andora and Katie Paris Kohn

This paper presents recently published resources on library instruction and information literacy. It provides an introductory overview and a selected annotated bibliography of…

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Abstract

Purpose

This paper presents recently published resources on library instruction and information literacy. It provides an introductory overview and a selected annotated bibliography of publications covering various library types, study populations and research contexts. The selected bibliography is useful to efficiently keep up with trends in library instruction for busy practitioners, library science students and those wishing to learn about information literacy in other contexts.

Design/methodology/approach

This article annotates 424 English-language periodical articles, monographs, dissertations, theses and reports on library instruction and information literacy published in 2021. The sources were selected from the EBSCO platform for Library, Information Science, and Technology Abstracts (LISTA), Education Resources Information Center (ERIC), Scopus, ProQuest Dissertations and Theses, and WorldCat, published in 2021 that included the terms “information literacy,” “library instruction,” or “information fluency” in the title, abstract or keywords. The sources were organized in Zotero. Annotations summarize the source, focusing on the findings or implications. Each source was categorized into one of seven pre-determined categories: K-12 Education, Children and Adolescents; Academic and Professional Programs; Everyday Life, Community, and the Workplace; Libraries and Health Information Literacy; Multiple Library Types; and Other Information Literacy Research and Theory.

Findings

The paper provides a brief description of 424 sources and highlights sources that contain unique or significant scholarly contributions.

Originality/value

The information may be used by librarians, researchers and anyone interested as a quick and comprehensive reference to literature on library instruction and information literacy within 2021.

Details

Reference Services Review, vol. 50 no. 3/4
Type: Research Article
ISSN: 0090-7324

Keywords

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Article
Publication date: 7 March 2024

Nehemia Sugianto, Dian Tjondronegoro and Golam Sorwar

This study proposes a collaborative federated learning (CFL) framework to address personal data transmission and retention issues for artificial intelligence (AI)-enabled video…

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Abstract

Purpose

This study proposes a collaborative federated learning (CFL) framework to address personal data transmission and retention issues for artificial intelligence (AI)-enabled video surveillance in public spaces.

Design/methodology/approach

This study examines specific challenges for long-term people monitoring in public spaces and defines AI-enabled video surveillance requirements. Based on the requirements, this study proposes a CFL framework to gradually adapt AI models’ knowledge while reducing personal data transmission and retention. The framework uses three different federated learning strategies to rapidly learn from different new data sources while minimizing personal data transmission and retention to a central machine.

Findings

The findings confirm that the proposed CFL framework can help minimize the use of personal data without compromising the AI model's performance. The gradual learning strategies help develop AI-enabled video surveillance that continuously adapts for long-term deployment in public spaces.

Originality/value

This study makes two specific contributions to advance the development of AI-enabled video surveillance in public spaces. First, it examines specific challenges for long-term people monitoring in public spaces and defines AI-enabled video surveillance requirements. Second, it proposes a CFL framework to minimize data transmission and retention for AI-enabled video surveillance. The study provides comprehensive experimental results to evaluate the effectiveness of the proposed framework in the context of facial expression recognition (FER) which involves large-scale datasets.

Details

Information Technology & People, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-3845

Keywords

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