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Article
Publication date: 17 September 2019

Chérif Taouche and Hacene Belhadef

Palmprint recognition is a very interesting and promising area of research. Much work has already been done in this area, but much more needs to be done to make the…

Abstract

Purpose

Palmprint recognition is a very interesting and promising area of research. Much work has already been done in this area, but much more needs to be done to make the systems more efficient. In this paper, a multimodal biometrics system based on fusion of left and right palmprints of a person is proposed to overcome limitations of unimodal systems.

Design/methodology/approach

Features are extracted using some proposed multi-block local descriptors in addition to MBLBP. Fusion of extracted features is done at feature level by a simple concatenation of feature vectors. Then, feature selection is performed on the resulting global feature vector using evolutionary algorithms such as genetic algorithms and backtracking search algorithm for a comparison purpose. The benefits of such step selecting the relevant features are known in the literature, such as increasing the recognition accuracy and reducing the feature set size, which results in runtime saving. In matching step, Chi-square similarity measure is used.

Findings

The resulting feature vector length representing a person is compact and the runtime is reduced.

Originality/value

Intensive experiments were done on the publicly available IITD database. Experimental results show a recognition accuracy of 99.17 which prove the effectiveness and robustness of the proposed multimodal biometrics system than other unimodal and multimodal biometrics systems.

Details

Information Discovery and Delivery, vol. 48 no. 1
Type: Research Article
ISSN: 2398-6247

Keywords

Content available
Article
Publication date: 1 February 2018

Xuhui Ye, Gongping Wu, Fei Fan, XiangYang Peng and Ke Wang

An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the…

Abstract

Purpose

An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the inspection robot cross obstacle automatically. This paper aims to propose an improved approach which is called adaptive homomorphic filter and supervised learning (AHSL) for overhead ground wire detection.

Design/methodology/approach

First, to decrease the influence of the varying illumination caused by the open work environment of the inspection robot, the adaptive homomorphic filter is introduced to compensation the changing illumination. Second, to represent ground wire more effectively and to extract more powerful and discriminative information for building a binary classifier, the global and local features fusion method followed by supervised learning method support vector machine is proposed.

Findings

Experiment results on two self-built testing data sets A and B which contain relative older ground wires and relative newer ground wire and on the field ground wires show that the use of the adaptive homomorphic filter and global and local feature fusion method can improve the detection accuracy of the ground wire effectively. The result of the proposed method lays a solid foundation for inspection robot grasping the ground wire by visual servo.

Originality/value

This method AHSL has achieved 80.8 per cent detection accuracy on data set A which contains relative older ground wires and 85.3 per cent detection accuracy on data set B which contains relative newer ground wires, and the field experiment shows that the robot can detect the ground wire accurately. The performance achieved by proposed method is the state of the art under open environment with varying illumination.

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Article
Publication date: 14 August 2017

Sudeep Thepade, Rik Das and Saurav Ghosh

Current practices in data classification and retrieval have experienced a surge in the use of multimedia content. Identification of desired information from the huge image…

Abstract

Purpose

Current practices in data classification and retrieval have experienced a surge in the use of multimedia content. Identification of desired information from the huge image databases has been facing increased complexities for designing an efficient feature extraction process. Conventional approaches of image classification with text-based image annotation have faced assorted limitations due to erroneous interpretation of vocabulary and huge time consumption involved due to manual annotation. Content-based image recognition has emerged as an alternative to combat the aforesaid limitations. However, exploring rich feature content in an image with a single technique has lesser probability of extract meaningful signatures compared to multi-technique feature extraction. Therefore, the purpose of this paper is to explore the possibilities of enhanced content-based image recognition by fusion of classification decision obtained using diverse feature extraction techniques.

Design/methodology/approach

Three novel techniques of feature extraction have been introduced in this paper and have been tested with four different classifiers individually. The four classifiers used for performance testing were K nearest neighbor (KNN) classifier, RIDOR classifier, artificial neural network classifier and support vector machine classifier. Thereafter, classification decisions obtained using KNN classifier for different feature extraction techniques have been integrated by Z-score normalization and feature scaling to create fusion-based framework of image recognition. It has been followed by the introduction of a fusion-based retrieval model to validate the retrieval performance with classified query. Earlier works on content-based image identification have adopted fusion-based approach. However, to the best of the authors’ knowledge, fusion-based query classification has been addressed for the first time as a precursor of retrieval in this work.

Findings

The proposed fusion techniques have successfully outclassed the state-of-the-art techniques in classification and retrieval performances. Four public data sets, namely, Wang data set, Oliva and Torralba (OT-scene) data set, Corel data set and Caltech data set comprising of 22,615 images on the whole are used for the evaluation purpose.

Originality/value

To the best of the authors’ knowledge, fusion-based query classification has been addressed for the first time as a precursor of retrieval in this work. The novel idea of exploring rich image features by fusion of multiple feature extraction techniques has also encouraged further research on dimensionality reduction of feature vectors for enhanced classification results.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 10 no. 3
Type: Research Article
ISSN: 1756-378X

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Book part
Publication date: 30 July 2018

Abstract

Details

Marketing Management in Turkey
Type: Book
ISBN: 978-1-78714-558-0

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Article
Publication date: 11 December 2019

Chunyan Nie and Tao Wang

The purpose of this paper is to examine the effect of the interpretation strategy of cultural mixing on consumers’ evaluations of global brands that incorporate local

Abstract

Purpose

The purpose of this paper is to examine the effect of the interpretation strategy of cultural mixing on consumers’ evaluations of global brands that incorporate local cultural elements. Specifically, this paper examines whether a property interpretation and a relational interpretation have different influences on consumers’ evaluations of global brands that incorporate local cultural elements.

Design/methodology/approach

Two experiments were conducted as part of this research. Experiment 1 adopted a two (interpretation strategy: property interpretation vs relational interpretation) single-factor between-subjects design. Experiment 2 adopted a 2 (interpretation strategy: property interpretation vs relational interpretation) × 2 (polyculturalist beliefs: high vs low) between-subjects design. The data were analyzed using ANOVA and PROCESS 213.

Findings

A property interpretation (emphasizing that some features of a global brand transfer to local cultural elements) leads to a less favorable evaluation of global brands that incorporate local cultural elements than a relational interpretation (emphasizing a relation between global brands and local cultural elements). This effect is fully mediated by perceived cultural intrusion, and it exists only when consumers have a low level of polyculturalist beliefs.

Originality/value

This paper reveals that the phenomenon of cultural mixing occurs when global brands incorporate local cultural elements. In addition, the way that consumers perceive the relationship between global brands and local cultural elements will determine their reactions to global brands that incorporate local cultural elements.

Details

International Marketing Review, vol. 38 no. 1
Type: Research Article
ISSN: 0265-1335

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Article
Publication date: 12 May 2020

Suraiya Hameed

This paper reports a qualitative research study of comparative analysis of global citizenship education (GCE) in two primary schools, one international school in Singapore…

Abstract

Purpose

This paper reports a qualitative research study of comparative analysis of global citizenship education (GCE) in two primary schools, one international school in Singapore (Stamford International) and an independent school in Australia (Coastal College). The research focussed on how these two schools implemented GCE through the adoption of international education models, utilising the International Primary Curriculum (IPC) or the International Baccalaureate Programme (IB), creating hybrid curricula. Central to this research is the examination of educational practices, which address global citizenship education in each of the two schools.

Design/methodology/approach

Qualitative data from interview transcripts, document analysis, website analysis as well as field notes were analysed both inductively and deductively, teasing out the key themes from interviews, various documents such as policy papers, curriculum materials, syllabuses, the websites and other forms of documents that shed more light on the issues presented. The analysis of each case study began with a brief overview of the global citizenship education policies in the two schools and of their international curricula models, followed by a separate interpretation and juxtaposition of interview data (Phillips and Schweisfurth, 2014).

Findings

The key focus is examining the interplay between the global and national, which both schools have acknowledged in their design of the curricula. It is integral to note that globalization differs within different communities around the world with a unique and multifaceted interplay of global and national factors termed as a “global-local nexus”. A key overarching finding relates to the tensions between educational domains and neo-liberal market rationales, which had affected the schools' decisions in curricula and GCE enactment within both schools. Despite their commitment to GCE ideals, schools were mindful about being distinctive and remaining competitive within their educational markets.

Research limitations/implications

In the study, the ideas of hybridity and “mixture and fusion” of curricula elements to generate new practices in local contexts against global influences have been explored. These ideas form the key features of the curriculum design in both schools and of the contexts in which the schools were situated. Even though the selected case study schools were international and independent and were not expected to fully adhere to government guidelines from their respective country’s policies, they were staged against these policies, which in turn influenced the curriculum initiatives and pedagogical approaches of these schools. Thus studying the landscape in which these two schools are situated provided a better understanding of the various influences – geo-political, formal policy, school-specific factors – which contributed to the knowledge base of global citizenship education studies for multi-ethnic nations such as Singapore and Australia.

Practical implications

As more national school systems embrace diversity, an international education approach has been adopted. This study affirms the idea proposed by Hayden, Thompson and Bunnell (2016), that the use of “international” is less relevant in categorising schools that seek to embrace GCE. It is more appropriate to use “cosmopolitan,” as proposed by Rizvi (2008), where the focus is more broadly on acquiring knowledge about cultural trajectories and social identities and reinforcing the idea of global connectivity as is evident in both case study schools. The focus is on understanding and acting on local issues within the “broader context of the global shifts that are reshaping the very nature of localities” (Rizvi, 2008, p. 21). One of the key things to note is that the global and international approaches are seldom enacted in their pure form. Schools that have adopted international education are usually unique and heterogeneous in nature, and what they have done is very much dependent on their histories, their geographical locations and the economic and political statuses. This is evident in both case study schools.

Social implications

This study has added to the existing literature by providing a rich comparative investigation of global citizenship education in two countries, Australia and Singapore. The research provided the opportunity to study different models of internationally minded schools, with similar GCE ambitions. As the study explored two types of schools in two different countries, there is no claim of generalisability of findings to all the schools in these two countries. However, educators and researchers who are interested in this field could reflect on the themes that have emerged from this study and make an informed decision on the possible transferability to their own contexts.

Originality/value

Besides its contribution to existing literature, the study has also shown that for effective integration of GCE in schools, either in a national or international education system, it is necessary for a comprehensive understanding of the GCE principles. The results drawn from the study indicate that the ambiguity of the concept of GCE can result in different interpretations by school leaders, teachers and students, thus affecting its enactment in schools. In order to better understand and apply GCE, an effective conceptual model would provide a critical understanding of the multi-faceted nature of global citizenship education. A critical GCE requires schools to reflect on the entire curriculum, ensuring a seamless integration of GCE into curricula and practices.

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Article
Publication date: 3 July 2007

Jürgen Bohn

To describe the architecture of iPOS (short for iPAQ positioning system), a novel fault‐tolerant and adaptive self‐positioning system with quality‐of‐service (QoS…

Abstract

Purpose

To describe the architecture of iPOS (short for iPAQ positioning system), a novel fault‐tolerant and adaptive self‐positioning system with quality‐of‐service (QoS) guarantees for resource‐limited mobile devices.

Design/methodology/approach

The iPOS architecture is based on a novel sensor modelling technique in combination with a probabilistic data‐fusion engine, which is capable of efficiently combining the location information obtained from an arbitrary number of heterogeneous location sensors. As a proof of concept, the paper present a prototypical implementation for handheld devices, which was evaluated by means of practical experiments.

Findings

A major advantage of the iPOS positioning system is its extensibility and flexibility, which is achieved by means of an open plugin architecture and the support of global positioning coordinates according to the WGS‐84 standard. The iPOS system scales very well with respect to the number of sensor plugins that can be operated in parallel. The main limiting factor for the number of supported active plugins is the amount of available system resources on the MoD. With regard to recognition, the experimental results indicate a good accuracy of the fusion‐based positioning system in comparison to the accuracy of the individual sensing technologies. Thanks to the explicit modelling of reliable sensor events, the iPOS system is capable of providing QoS guarantees to applications with regard to the achieved positioning accuracy.

Research limitations/implications

During the experiments, the author recognized time synchronisation as an important challenge that should be addressed as part of future work.

Practical implications

The system enables resource‐restricted mobile devices and computerised objects to exploit computing resources found in their immediate physical vicinity (locality).

Originality/value

The paper presents a novel lightweight sensor‐fusion architecture for fault‐tolerant and adaptive self‐positioning that performs well on resource‐limited mobile devices. A special feature of the developed data‐fusion architecture is the application of a novel event modelling technique that enables the positioning system to give QoS guarantees under certain conditions.

Details

Sensor Review, vol. 27 no. 3
Type: Research Article
ISSN: 0260-2288

Keywords

Content available
Article
Publication date: 17 July 2020

Sheryl Brahnam, Loris Nanni, Shannon McMurtrey, Alessandra Lumini, Rick Brattin, Melinda Slack and Tonya Barrier

Diagnosing pain in neonates is difficult but critical. Although approximately thirty manual pain instruments have been developed for neonatal pain diagnosis, most are…

Abstract

Diagnosing pain in neonates is difficult but critical. Although approximately thirty manual pain instruments have been developed for neonatal pain diagnosis, most are complex, multifactorial, and geared toward research. The goals of this work are twofold: 1) to develop a new video dataset for automatic neonatal pain detection called iCOPEvid (infant Classification Of Pain Expressions videos), and 2) to present a classification system that sets a challenging comparison performance on this dataset. The iCOPEvid dataset contains 234 videos of 49 neonates experiencing a set of noxious stimuli, a period of rest, and an acute pain stimulus. From these videos 20 s segments are extracted and grouped into two classes: pain (49) and nopain (185), with the nopain video segments handpicked to produce a highly challenging dataset. An ensemble of twelve global and local descriptors with a Bag-of-Features approach is utilized to improve the performance of some new descriptors based on Gaussian of Local Descriptors (GOLD). The basic classifier used in the ensembles is the Support Vector Machine, and decisions are combined by sum rule. These results are compared with standard methods, some deep learning approaches, and 185 human assessments. Our best machine learning methods are shown to outperform the human judges.

Details

Applied Computing and Informatics, vol. no.
Type: Research Article
ISSN: 2634-1964

Keywords

Content available
Article
Publication date: 16 July 2020

Loris Nanni, Stefano Ghidoni and Sheryl Brahnam

This work presents a system based on an ensemble of Convolutional Neural Networks (CNNs) and descriptors for bioimage classification that has been validated on different…

Abstract

This work presents a system based on an ensemble of Convolutional Neural Networks (CNNs) and descriptors for bioimage classification that has been validated on different datasets of color images. The proposed system represents a very simple yet effective way of boosting the performance of trained CNNs by composing multiple CNNs into an ensemble and combining scores by sum rule. Several types of ensembles are considered, with different CNN topologies along with different learning parameter sets. The proposed system not only exhibits strong discriminative power but also generalizes well over multiple datasets thanks to the combination of multiple descriptors based on different feature types, both learned and handcrafted. Separate classifiers are trained for each descriptor, and the entire set of classifiers is combined by sum rule. Results show that the proposed system obtains state-of-the-art performance across four different bioimage and medical datasets. The MATLAB code of the descriptors will be available at https://github.com/LorisNanni.

Details

Applied Computing and Informatics, vol. 17 no. 1
Type: Research Article
ISSN: 2634-1964

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Article
Publication date: 2 October 2018

David Bright and Chad Whelan

The purpose of this paper is to adopt an organisational network perspective to examine the structural properties underpinning the design and governance of multi-agency…

Abstract

Purpose

The purpose of this paper is to adopt an organisational network perspective to examine the structural properties underpinning the design and governance of multi-agency fusion centres and related environments, focussing particularly on how they are formed and internally managed.

Design/methodology/approach

The authors conducted several focus groups and follow-up interviews with executive and operational members of Australia’s principal fusion centres and related environments.

Findings

The authors argue that in order to understand the internal dynamics of fusion centres, and the ways in which they form and function, the analysis of interrelationships between partners and potential partners is critical. The authors have demonstrated that a network model can assist in this type of analysis. For example, hub-and-spoke network structures appear to be a particularly effective solution to the centralisation-density trade-off for such inter-agency networks.

Originality/value

The authors use a novel approach that combines a goal-oriented network framework with the existing literature on fusion centres to synthesise key features of the network structure of fusion centres and associated processes of information sharing.

Details

Policing: An International Journal, vol. 42 no. 3
Type: Research Article
ISSN: 1363-951X

Keywords

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