Iwin Thanakumar Joseph S., Sasikala J. and Sujitha Juliet D.
The purpose of this paper is to study various ship detection methodologies. The accuracy of ship detection using satellite images still suffers from disturbances due to cluttered…
Abstract
Purpose
The purpose of this paper is to study various ship detection methodologies. The accuracy of ship detection using satellite images still suffers from disturbances due to cluttered scenes and varying ship sizes. The suitability of the techniques for various applications is explained in this survey.
Design/methodology/approach
A list of data on the subject was gathered and processed into tables. The test outcomes were then discussed to determine the most effective ship detection technique under various complex environments.
Findings
In this work, the advantages and disadvantages of different classification techniques of ship detection are highlighted. The suitability of the techniques for various applications is also explained in this survey. Several hybrid approaches can be developed in order to increase the accuracy of ship detection system. This survey also aids in highlighting the significant contributions of satellite images to effective ship detection system.
Originality/value
In this paper, studying various ship detection methodologies is given specific attention. A survey on ship detection and recognition is clarified with the detailed comparative analysis of various classifier techniques.
Details
Keywords
J. Sasikala, G. Shylaja, Naidu V. Kesavulu, B. Venkatesh and S.M. Mallikarjunaiah
A finite element computational methodology on a curved boundary using an efficient subparametric point transformation is presented. The proposed collocation method uses one-side…
Abstract
Purpose
A finite element computational methodology on a curved boundary using an efficient subparametric point transformation is presented. The proposed collocation method uses one-side curved and two-side straight triangular elements to derive exact subparametric shape functions.
Design/methodology/approach
Our proposed method builds upon the domain discretization into linear, quadratic and cubic-order elements using subparametric spaces and such a discretization greatly reduces the computational complexity. A unique subparametric transformation for each triangle is derived from the unique parabolic arcs via a one-of-a-kind relationship between the nodal points.
Findings
The novel transformation derived in this paper is shown to increase the accuracy of the finite element approximation of the boundary value problem (BVP). Our overall strategy is shown to perform well for the BVP considered in this work. The accuracy of the finite element approximate solution increases with higher-order parabolic arcs.
Originality/value
The proposed collocation method uses one-side curved and two-side straight triangular elements to derive exact subparametric shape functions.
Details
Keywords
S.A. Krishnan, G. Sasikala, A. Moitra, S.K. Albert and A.K. Bhaduri
The purpose of this paper is to present a methodology to assess material damage parameters for ductile crack initiation and growth ahead of a crack/notch tip in high hardening…
Abstract
Purpose
The purpose of this paper is to present a methodology to assess material damage parameters for ductile crack initiation and growth ahead of a crack/notch tip in high hardening steel like AISI type 316L(N) stainless steel.
Design/methodology/approach
Ductile damage parameter and far field J-integral have been obtained from standard FEM analysis for a crack/notch tip undergoing large plastic deformation and resulting in crack initiation/growth. In conjunction with experimental results, the damage variable for low strength and high hardening material has been derived in terms of continuum parameters: equivalent plastic strain (εeq) and stress triaxiality (φ). The material parameters for damage initiation and growth in 316LN SS have been evaluated from tensile and fracture tests. With these material tensile/fracture parameters as input, elastic-plastic eXtended Finite Element Method (X-FEM) simulations were carried out on compact tension (CT) specimen geometry under varying initial stress triaxiality conditions.
Findings
The material parameters for damage initiation and growth have been assessed and calibrated by comparing the X-FEM predicted load-displacement responses with the experimental results. It is observed that the deviations in the predicted load values from the experimental data are within 6 percent for specimens with a/W=0.39, 0.55, 0.64, while for a/W=0.72, it is 17 percent.
Originality/value
The present study is a part of developing methods to obtain calibrated material damage parameters for crack growth simulation of components made of AISI 316L(N) stainless steel. This steel is used for fast breeder reactor-based power plant being built at Kalpakkam, India.
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Rajasekar Velswamy, Sorna Chandra Devadass, Karunakaran Velswamy and Jeyakrishnan Venugopal
The purpose of this paper is to classify the given image as indoor or outdoor with higher success rate by mixing various features like brightness, number of straight lines, number…
Abstract
Purpose
The purpose of this paper is to classify the given image as indoor or outdoor with higher success rate by mixing various features like brightness, number of straight lines, number of Euclidean shapes and recursive shapes.
Design/methodology/approach
For annotating an image, it is very easy, if the image is categorized as indoor or outdoor. Many methods are proposed to classify the given image in these criteria but still the rate of uncategorized images occupies considerable area. This proposed work is the extension of the existing works already proposed by experts in this field. Some of the parameters mainly focused to classify are color histogram, orientation of edges, straightness of edges, discrete cosine transform coefficients, etc. In addition to that, this work includes finding of Euclidean shapes i.e. closed contours and recursive shapes in the given image. When the Euclidean shaped object dominates the recursive shapes then it is classified as indoor object and if the recursive shapes dominates, it is categorized as outdoor object.
Findings
This work is carried out on the standard image data sets. The data sets are Microsoft Research Cambridge (MRC) object recognition image database 1.0. and Kodak and Coral image data set. Totally 540 images are taken into account and the images are classified 95.4 percent correctly.
Originality/value
Many methods are proposed to classify the given image in these criteria but still the rate of uncategorized images occupies considerable area. This proposed work is the extension of the existing works already proposed by experts in this field. Some of the parameters mainly focused to classify are color histogram, orientation of edges, straightness of edges, discrete cosine transform coefficients, etc. In addition to that, this work includes finding of Euclidean shapes i.e. closed contours and recursive shapes in the given image. When the Euclidean shaped object dominates the recursive shapes then it is classified as indoor object and if the recursive shapes dominates, it is categorized as outdoor object. This work is carried out on the standard image data sets. The data sets are MRC object recognition image database 1.0. and Kodak and Coral image data set. Totally 540 images are taken into account and the images are classified 95.4 percent correctly.
Details
Keywords
Renuka Devi D. and Sasikala S.
The purpose of this paper is to enhance the accuracy of classification of streaming big data sets with lesser processing time. This kind of social analytics would contribute to…
Abstract
Purpose
The purpose of this paper is to enhance the accuracy of classification of streaming big data sets with lesser processing time. This kind of social analytics would contribute to society with inferred decisions at a correct time. The work is intended for streaming nature of Twitter data sets.
Design/methodology/approach
It is a demanding task to analyse the increasing Twitter data by the conventional methods. The MapReduce (MR) is used for quickest analytics. The online feature selection (OFS) accelerated bat algorithm (ABA) and ensemble incremental deep multiple layer perceptron (EIDMLP) classifier is proposed for Feature Selection and classification. Three Twitter data sets under varied categories are investigated (product, service and emotions). The proposed model is compared with Particle Swarm Optimization, Accelerated Particle Swarm Optimization, accelerated simulated annealing and mutation operator (ASAMO). Feature Selection algorithms and classifiers such as Naïve Bayes, support vector machine, Hoeffding tree and fuzzy minimal consistent class subset coverage with the k-nearest neighbour (FMCCSC-KNN).
Findings
The proposed model is compared with PSO, APSO, ASAMO. Feature Selection algorithms, and classifiers such as Naïve Bayes (NB), support vector machine (SVM), Hoeffding Tree (HT), and Fuzzy Minimal Consistent Class Subset Coverage with the K-Nearest Neighbour (FMCCSC-KNN). The outcome of the work has achieved an accuracy of 99%, 99.48%, 98.9% for the given data sets with the processing time of 0.0034, 0.0024, 0.0053, seconds respectively.
Originality/value
A novel framework is proposed for Feature Selection and classification. The work is compared with the authors’ previously developed classifiers with other state-of-the-art Feature Selection and classification algorithms.
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Keywords
Visalakshy Sasikala, Venkataraman Sankaranarayanan, Deepak Dhayanithy and Geetha Mohan
This paper aims to critically examine how dual-listed multinational enterprises (MNEs) that are embedded across multiple national contexts interact with other actors to shape the…
Abstract
Purpose
This paper aims to critically examine how dual-listed multinational enterprises (MNEs) that are embedded across multiple national contexts interact with other actors to shape the diversity, equality and inclusion (DEI) narrative, outcomes and the associated dynamics of social change in the mining industry.
Design/methodology/approach
The authors use data from the publicly available sustainability reports of two global mining conglomerates with dual-listing structure, Rio Tinto and Anglo American, alongside prevalent DEI regulations in the UK, Australia and South Africa to understand how DEI discourse and practice and the corresponding role of key actors have evolved since 2015. The authors combine a case study approach with topic modelling and qualitative content analysis to critically analyse the linkage between actors’ stated posture and actions in their DEI field and their impact upon various exchange relationships within the mining industry exchange field over the period 2015–2021.
Findings
The analysis revealed three broad phases of evolution in the DEI involvement of the MNEs emphasizing on diversity, equality and inclusion, respectively. Both firms progressed at a different pace across the three phases highlighting the need for a systemic perspective when addressing DEI concerns.
Originality/value
This paper is one of the earliest to adopt an issue and exchange field perspective towards examining the complexity of DEI. Taking a critical performative stance, the authors argue that for improving convergence between MNEs’ DEI rhetoric and reality and to advance DEI in new ways organizations and policymakers must devise structural interventions in the DEI field that substantively impact MNEs’ industry exchange field relationships.
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R. Prathiba Devi, L. Sasikala, R. Rathinamoorthy and Dr. J. Jeyakodi Moses
The effect of enzyme treatments with consecutive softening by the use of silicone – polyurethane on low stress mechanical properties and hand values of jute/cotton union fabric…
Abstract
The effect of enzyme treatments with consecutive softening by the use of silicone – polyurethane on low stress mechanical properties and hand values of jute/cotton union fabric have been studied on the Kawabata evaluation system (KES). The results indicate that the enzyme treated, silicone – polyurethane finished fabric has significant (p<0.05) improvement in tensile resilience, fabric extensibility, compressional resistance and friction co efficient, whereas fabric thickness, linearity of tensile, surface roughness, bending and shear rigidity and their hysteresis are reduced compared to the untreated fabric. Under the Kawabata system, the Koshi (stiffness) value of the finished fabric is decreased by 1-9%. Numeri (smoothness) and Fukurami (fullness and softness) values are increased by 11-20% and 3-4% respectively compared to the untreated fabric. The variation in primary hand values are significant (p<0.05). The total hand value (THV) is also increased by 6% and 44% for the case of 40/60 and 50/50 jute/cotton union fabrics, respectively. This study confirms the possible usage of jute/cotton fabric in the apparel segment.
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Keywords
Matevž Matt Rašković, Fiona Hurd and Theresa Onaji-Benson
The purpose of this paper is to provide a scene-setting viewpoint that critically examines various diversity, equity and inclusion (DEI) blind spots within the field of…
Abstract
Purpose
The purpose of this paper is to provide a scene-setting viewpoint that critically examines various diversity, equity and inclusion (DEI) blind spots within the field of international business (IB). These include issues such as social justice, intersectionality, de-colonization, the co-creation of inclusive research practices in indigenous spaces, social dialogue and the gap between DEI rhetoric and reality. An additional aim of the viewpoint is also to contextualise the discussion of DEI blind spots in terms of the six papers which make up the first part of a two-part special issue on DEI in IB".
Design/methodology/approach
The authors build on existing DEI overview works and comment on specific DEI blind spots. The authors also discuss the role of positionality as critical reflexive scholarship practice, which they see as an essential step in problematizing structural inequalities. The authors then discuss six specific areas where DEI blindspots persist within the IB literature and link their discussion to the six papers included in the first part of their DEI special issue.
Findings
Addressing the contradictions between the business and social justice cases for DEI requires addressing the ontological contradictions between the two perspectives through problematizing structural inequalities. A key contribution of the paper is also the discussion around positionality in DEI research and the relevance of positionality statements as part of critical reflexive scholarship in support of a socially just DEI research agenda.
Originality/value
The authors discuss the role DEI research plays and can play within the evolution of the IB discipline. The authors apply a critical management studies perspective to pervasive DEI issues, as well as engage with the topics in the special issue through a unique critical reflexive epistemology which includes their own positionality statements as guest editors and researchers. Their critical discussion and recommendations for future research serve as a kind of whetstone to sharpen IB’s DEI research tools and in turn for IB to help sharpen DEI research’s tools, supporting it to become more socially just.
Details
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Grant Samkin, Dessalegn Getie Mihret and Tesfaye Lemma
We develop a conceptual framework as a basis for thinking about the impact of extractive industries and emancipatory potential of alternative accounts. We then review selected…
Abstract
Purpose
We develop a conceptual framework as a basis for thinking about the impact of extractive industries and emancipatory potential of alternative accounts. We then review selected alternative accounts literature on some contemporary issues surrounding the extractive industries and identify opportunities for accounting, auditing, and accountability research. We also provide an overview of the other contributions in this special issue.
Design/methodology/approach
Drawing on alternative accounts from the popular and social media as well as the alternative accounting literature, this primarily discursive paper provides a contemporary literature review of identified issues within the extractive industries highlighting potential areas for future research. The eight papers that make up the special issue are located within a conceptual framework is employed to illustrate each paper’s contribution to the field.
Findings
While accounting has a rich literature covering some of the issues detailed in this paper, this has not necessarily translated to the extractive industries. Few studies in accounting have got “down and dirty” so to speak and engaged directly with those impacted by companies operating in the extractive industries. Those that have, have focused on specific areas such as the Niger Delta. Although prior studies in the social governance literature have tended to focus on disclosure issues, it is questionable whether this work, while informative, has resulted in any meaningful environmental, social or governance (ESG) changes on the part of the extractive industries.
Research limitations/implications
The extensive extractive industries literature both from within and outside the accounting discipline makes a comprehensive review impractical. Drawing on both the accounting literature and other disciplines, this paper identifies areas that warrant further investigation through alternative accounts.
Originality/value
This paper and other contributions to this special issue provide a basis and an agenda for accounting scholars seeking to undertake interdisciplinary research into the extractive industries.
Details
Keywords
Yi-Hung Liu, Sheng-Fong Chen and Dan-Wei (Marian) Wen
Online medical repositories provide a platform for users to share information and dynamically access abundant electronic health data. It is important to determine whether case…
Abstract
Purpose
Online medical repositories provide a platform for users to share information and dynamically access abundant electronic health data. It is important to determine whether case report information can assist the general public in appropriately managing their diseases. Therefore, this paper aims to introduce a novel deep learning-based method that allows non-professionals to make inquiries using ordinary vocabulary, retrieving the most relevant case reports for accurate and effective health information.
Design/methodology/approach
The dataset of case reports was collected from both the patient-generated research network and the digital medical journal repository. To enhance the accuracy of obtaining relevant case reports, the authors propose a retrieval approach that combines BERT and BiLSTM methods. The authors identified representative health-related case reports and analyzed the retrieval performance, as well as user judgments.
Findings
This study aims to provide the necessary functionalities to deliver relevant health case reports based on input from ordinary terms. The proposed framework includes features for health management, user feedback acquisition and ranking by weights to obtain the most pertinent case reports.
Originality/value
This study contributes to health information systems by analyzing patients' experiences and treatments with the case report retrieval model. The results of this study can provide immense benefit to the general public who intend to find treatment decisions and experiences from relevant case reports.