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1 – 10 of 16
Article
Publication date: 1 March 2001

K.G.B. Bakewell

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes…

16992

Abstract

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Details

Structural Survey, vol. 19 no. 3
Type: Research Article
ISSN: 0263-080X

Article
Publication date: 1 September 2001

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property…

14392

Abstract

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Details

Facilities, vol. 19 no. 9
Type: Research Article
ISSN: 0263-2772

Article
Publication date: 1 September 2000

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property…

26781

Abstract

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Details

Facilities, vol. 18 no. 9
Type: Research Article
ISSN: 0263-2772

Article
Publication date: 1 March 2000

K.G.B. Bakewell

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes…

23500

Abstract

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐17; Journal of Property Investment & Finance Volumes 8‐17; Property Management Volumes 8‐17; Structural Survey Volumes 8‐17.

Details

Structural Survey, vol. 18 no. 3
Type: Research Article
ISSN: 0263-080X

Article
Publication date: 13 November 2009

George K. Stylios

Examines the fifthteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched…

1010

Abstract

Examines the fifthteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Details

International Journal of Clothing Science and Technology, vol. 21 no. 6
Type: Research Article
ISSN: 0955-6222

Keywords

Content available
Article
Publication date: 1 June 2004

33

Abstract

Details

Pigment & Resin Technology, vol. 33 no. 3
Type: Research Article
ISSN: 0369-9420

Keywords

Abstract

Details

Documents from the History of Economic Thought
Type: Book
ISBN: 978-0-7623-1423-2

Abstract

Details

Ideators
Type: Book
ISBN: 978-1-80262-830-2

Article
Publication date: 30 April 2021

J Aruna Santhi and T Vijaya Saradhi

This paper tactics to implement the attack detection in medical Internet of things (IoT) devices using improved deep learning architecture for accomplishing the concept…

Abstract

Purpose

This paper tactics to implement the attack detection in medical Internet of things (IoT) devices using improved deep learning architecture for accomplishing the concept bring your own device (BYOD). Here, a simulation-based hospital environment is modeled where many IoT devices or medical equipment are communicated with each other. The node or the device, which is creating the attack are recognized with the support of attribute collection. The dataset pertaining to the attack detection in medical IoT is gathered from each node that is considered as features. These features are subjected to a deep belief network (DBN), which is a part of deep learning algorithm. Despite the existing DBN, the number of hidden neurons of DBN is tuned or optimized correctly with the help of a hybrid meta-heuristic algorithm by merging grasshopper optimization algorithm (GOA) and spider monkey optimization (SMO) in order to enhance the accuracy of detection. The hybrid algorithm is termed as local leader phase-based GOA (LLP-GOA). The DBN is used to train the nodes by creating the data library with attack details, thus maintaining accurate detection during testing.

Design/methodology/approach

This paper has presented novel attack detection in medical IoT devices using improved deep learning architecture as BYOD. With this, this paper aims to show the high convergence and better performance in detecting attacks in the hospital network.

Findings

From the analysis, the overall performance analysis of the proposed LLP-GOA-based DBN in terms of accuracy was 0.25% better than particle swarm optimization (PSO)-DBN, 0.15% enhanced than grey wolf algorithm (GWO)-DBN, 0.26% enhanced than SMO-DBN and 0.43% enhanced than GOA-DBN. Similarly, the accuracy of the proposed LLP-GOA-DBN model was 13% better than support vector machine (SVM), 5.4% enhanced than k-nearest neighbor (KNN), 8.7% finer than neural network (NN) and 3.5% enhanced than DBN.

Originality/value

This paper adopts a hybrid algorithm termed as LLP-GOA for the accurate detection of attacks in medical IoT for improving the enhanced security in healthcare sector using the optimized deep learning. This is the first work which utilizes LLP-GOA algorithm for improving the performance of DBN for enhancing the security in the healthcare sector.

Book part
Publication date: 8 April 2005

Magnar Forbord

In every industry there are resources. Some are moving, others more fixed; some are technical, others social. People working with the resources, for example, as buyers or…

Abstract

In every industry there are resources. Some are moving, others more fixed; some are technical, others social. People working with the resources, for example, as buyers or sellers, or users or producers, may not make much notice of them. A product sells. A facility functions. The business relationship in which we make our money has “always” been there. However, some times this picture of order is disturbed. A user having purchased a product for decades may “suddenly” say to the producer that s/he does not appreciate the product. And a producer having received an order of a product that s/he thought was well known, may find it impossible to sell it. Such disturbances may be ignored. Or they can be used as a platform for development. In this study we investigate the latter option, theoretically and through real world data. Concerning theory we draw on the industrial network approach. We see industrial actors as part of (industrial) networks. In their activities actors use and produce resources. Moreover, the actors interact − bilaterally and multilaterally. This leads to development of resources and networks. Through “thick” descriptions of two cases we illustrate and try to understand the interactive character of resource development and how actors do business on features of resources. The cases are about a certain type of resource, a product − goat milk. The main message to industrial actors is that they should pay attention to that products can be co-created. Successful co-creation of products, moreover, may require development also of business relationships and their connections (“networking”).

Details

Managing Product Innovation
Type: Book
ISBN: 978-1-84950-311-2

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