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1 – 10 of 297
Content available
Article
Publication date: 3 April 2007

37

Abstract

Details

Sensor Review, vol. 27 no. 2
Type: Research Article
ISSN: 0260-2288

Content available
Article
Publication date: 8 May 2007

60

Abstract

Details

Industrial Robot: An International Journal, vol. 34 no. 3
Type: Research Article
ISSN: 0143-991X

Content available
Article
Publication date: 24 April 2007

65

Abstract

Details

Assembly Automation, vol. 27 no. 2
Type: Research Article
ISSN: 0144-5154

Open Access
Article
Publication date: 12 April 2019

Darlington A. Akogo and Xavier-Lewis Palmer

Computer vision for automated analysis of cells and tissues usually include extracting features from images before analyzing such features via various machine learning and machine…

1158

Abstract

Purpose

Computer vision for automated analysis of cells and tissues usually include extracting features from images before analyzing such features via various machine learning and machine vision algorithms. The purpose of this work is to explore and demonstrate the ability of a Convolutional Neural Network (CNN) to classify cells pictured via brightfield microscopy without the need of any feature extraction, using a minimum of images, improving work-flows that involve cancer cell identification.

Design/methodology/approach

The methodology involved a quantitative measure of the performance of a Convolutional Neural Network in distinguishing between two cancer lines. In their approach, they trained, validated and tested their 6-layer CNN on 1,241 images of MDA-MB-468 and MCF7 breast cancer cell line in an end-to-end fashion, allowing the system to distinguish between the two different cancer cell types.

Findings

They obtained a 99% accuracy, providing a foundation for more comprehensive systems.

Originality/value

Value can be found in that systems based on this design can be used to assist cell identification in a variety of contexts, whereas a practical implication can be found that these systems can be deployed to assist biomedical workflows quickly and at low cost. In conclusion, this system demonstrates the potentials of end-to-end learning systems for faster and more accurate automated cell analysis.

Details

Journal of Industry-University Collaboration, vol. 1 no. 1
Type: Research Article
ISSN: 2631-357X

Keywords

Content available
Article
Publication date: 1 November 2006

96

Abstract

Details

Industrial Robot: An International Journal, vol. 33 no. 6
Type: Research Article
ISSN: 0143-991X

Content available
Article
Publication date: 20 June 2008

53

Abstract

Details

Industrial Robot: An International Journal, vol. 35 no. 4
Type: Research Article
ISSN: 0143-991X

Content available
Article
Publication date: 17 October 2008

60

Abstract

Details

Industrial Robot: An International Journal, vol. 35 no. 6
Type: Research Article
ISSN: 0143-991X

Open Access
Article
Publication date: 22 March 2021

Manel González-Piñero, Cristina Páez-Avilés, Esteve Juanola-Feliu and Josep Samitier

This paper aims to explore how the cross-fertilization of knowledge and technologies in EU-funded research projects, including serious games and gamification, is influenced by the…

5876

Abstract

Purpose

This paper aims to explore how the cross-fertilization of knowledge and technologies in EU-funded research projects, including serious games and gamification, is influenced by the following variables: multidisciplinarity, knowledge base and organizations (number and diversity). The interrelation of actors and projects form a network of innovation. The largest contribution to cross-fertilization comes from the multidisciplinary nature of projects and the previous knowledge and technology of actors. The analysis draws on the understanding of how consortia perform as an innovation network, what their outcomes are and what capabilities are needed to reap value.

Design/methodology/approach

All the research projects including serious games and/or gamification, funded by the EU-Horizon 2020 work programme, have been analyzed to test the hypotheses in this paper. The study sample covers the period between 2014 and 2016 (June), selecting the 87 research projects that comprised 519 organizations as coordinators and participants, and 597 observations – because more organizations participate in more than one project. The data were complemented by documentary and external database analysis.

Findings

To create cross-fertilization of knowledge and technologies, the following emphasis should be placed on projects: partners concern various disciplines; partners have an extensive knowledge base for generating novel combinations and added-value technologies; there is a diverse typology of partners with unique knowledge and skills; and there is a limited number of organizations not too closely connected to provide cross-fertilization.

Research limitations/implications

First, the database sample covers a period of 30 months. The authors’ attention was focused on this period because H2020 prioritized for the first time the serious games and gamification with two specific calls (ICT-21–14 and ICT-24–16) and, second, for the explosion of projects including these technologies in the past years (Adkins, 2017). These facts can be understood as a way to push the research to higher technology readiness levels (TRLs) and introducing the end-user in the co-creation and co-development along the value chain. Second, an additional limitation makes reference to the European focus of the projects, missing strong regional initiatives not identified and studied.

Originality/value

This paper has attempted to explore and define theoretically and empirically the characteristics found in the cross-fertilization of collaborative research projects, emphasizing which variables, and how, need to be stimulated to benefit more multidisciplinary consortia and accelerate the process of innovation.

Details

Journal of Knowledge Management, vol. 25 no. 11
Type: Research Article
ISSN: 1367-3270

Keywords

Open Access
Article
Publication date: 24 October 2023

Ilpo Helén and Hanna Lehtimäki

The paper contributes to the discussion on valuation in organization studies and strategic management literature. The nascent literature on valuation practices has examined…

Abstract

Purpose

The paper contributes to the discussion on valuation in organization studies and strategic management literature. The nascent literature on valuation practices has examined established markets where producers and consumers are known and rivalry in the market is a given. Furthermore, previous research has operated with a narrow meaning of value as either a financial profit or a subjective consumer preference. Such a narrow view on value is problematic and insufficient for studying the interlacing of innovation and value creation in emerging technoscientific business domains.

Design/methodology/approach

The authors present an empirical study about value creation in an emerging technoscience business domain formed around personalized medicine and digital health data.

Findings

The results of this analysis show that in a technoscientific domain, valuation of innovations is multiple and malleable, entails pursuing attractiveness in collaboration and partnerships and is performative, and due to emphatic future orientation, values are indefinite and promissory.

Research limitations/implications

As research implications, this study shows that valuation practices in an emerging technoscience business domain focus on defining the potential economic value in the future and attracting partners as probable future beneficiaries. Commercial value upon innovation in an embryonic business milieu is created and situated in valuation practices that constitute the prospective market, the prevalent economic discourse, and rationale. This is in contrast to an established market, where valuation practices are determined at the intersection of customer preferences and competitive arenas where suppliers, producers, service providers and new entrants to the market present value propositions.

Practical implications

The study findings extend discussion on valuation from established business domains to emerging technoscience business domains which are in a “pre-competition” phase where suppliers, customers, producers and their collaborative and competitive relations are not yet established.

Social implications

As managerial implications, this study provides insights into health innovation stakeholders, including stakeholders in the public, private and academic sectors, about the ecosystem dynamics in a technoscientific innovation. Such insight is useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To business managers, the findings of this study about valuation practices are useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To policy makers, this study provides an in-depth analysis of an overall business ecosystem in an emerging technoscience business that can be propelled to increase the financial investments in the field. As a policy implication, this study provides insights into the various dimensions of valuation in technoscience business to policy makers, who make governance decisions to guide and control the development of medical innovation using digital health data.

Originality/value

This study's results expand previous theorizing on valuation by showing that in technoscientific innovation all types of value created – scientific, clinical, social or economic – are predominantly promissory. This study complements the nascent theorizing on value creation and valuation practices of technoscientific innovation.

Details

European Journal of Innovation Management, vol. 26 no. 7
Type: Research Article
ISSN: 1460-1060

Keywords

Content available
Article
Publication date: 1 December 2005

196

Abstract

Details

Industrial Robot: An International Journal, vol. 32 no. 6
Type: Research Article
ISSN: 0143-991X

1 – 10 of 297