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Article
Publication date: 23 November 2021

Srinivas Talasila, Kirti Rawal and Gaurav Sethi

Extraction of leaf region from the plant leaf images is a prerequisite process for species recognition, disease detection and classification and so on, which are required for crop…

164

Abstract

Purpose

Extraction of leaf region from the plant leaf images is a prerequisite process for species recognition, disease detection and classification and so on, which are required for crop management. Several approaches were developed to implement the process of leaf region segmentation from the background. However, most of the methods were applied to the images taken under laboratory setups or plain background, but the application of leaf segmentation methods is vital to be used on real-time cultivation field images that contain complex backgrounds. So far, the efficient method that automatically segments leaf region from the complex background exclusively for black gram plant leaf images has not been developed.

Design/methodology/approach

Extracting leaf regions from the complex background is cumbersome, and the proposed PLRSNet (Plant Leaf Region Segmentation Net) is one of the solutions to this problem. In this paper, a customized deep network is designed and applied to extract leaf regions from the images taken from cultivation fields.

Findings

The proposed PLRSNet compared with the state-of-the-art methods and the experimental results evident that proposed PLRSNet yields 96.9% of Similarity Index/Dice, 94.2% of Jaccard/IoU, 98.55% of Correct Detection Ratio, Total Segmentation Error of 0.059 and Average Surface Distance of 3.037, representing a significant improvement over existing methods particularly taking into account of cultivation field images.

Originality/value

In this work, a customized deep learning network is designed for segmenting plant leaf region under complex background and named it as a PLRSNet.

Details

International Journal of Intelligent Unmanned Systems, vol. 11 no. 1
Type: Research Article
ISSN: 2049-6427

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Case study
Publication date: 26 June 2018

M. R. Dixit and Sanjay Kumar Jena

The AirAsia India 2017 (AAI) case presents the situation faced by Tony Fernandes, the CEO of the AirAsia group of companies, in 2017, when he had to respond to the changes in…

Abstract

The AirAsia India 2017 (AAI) case presents the situation faced by Tony Fernandes, the CEO of the AirAsia group of companies, in 2017, when he had to respond to the changes in aviation policy made by the Ministry of Civil Aviation (MCA). As per the changes, an airline operating in India could start its international operations without having five years of domestic flying experience provided it deployed 20 of its aircraft or 20% of the total capacity, whichever was higher, for domestic operations. The objective of this case is to help discuss issues relating to sustaining late entry and exploring new growth opportunities in the context of regulatory changes.

Details

Indian Institute of Management Ahmedabad, vol. no.
Type: Case Study
ISSN: 2633-3260
Published by: Indian Institute of Management Ahmedabad

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Article
Publication date: 1 November 2024

Anum Paracha and Junaid Arshad

Advances in machine learning (ML) have made significant contributions to the development of intelligent and autonomous systems leading to concerns about resilience of such systems…

10

Abstract

Purpose

Advances in machine learning (ML) have made significant contributions to the development of intelligent and autonomous systems leading to concerns about resilience of such systems against cyberattacks. This paper aims to report findings from a quantitative analysis of literature within ML security to assess current research trends in ML security.

Design/methodology/approach

The study focuses on statistical analysis of literature published between 2000 and 2023, providing quantitative research contributions targeting authors, countries and interdisciplinary studies of organizations. This paper reports existing surveys and a comparison of publications of attacks on ML and its in-demand security. Furthermore, an in-depth study of keywords, citations and collaboration is presented to facilitate deeper analysis of this literature.

Findings

Trends identified between 2021 and 2022 highlight an increase in focus on adversarial ML – 40\% more publications compared to 2020–2022 with more than 90\% publications in journals. This paper has also identified trends with respect to citations, keywords analysis, annual publications, co-author citations and geographical collaboration highlighting China and the USA as the countries with highest publications count and Biggio B. as the researcher with collaborative strength of 143 co-authors which highlight significant pollination of ideas and knowledge. Keyword analysis highlighted deep learning and computer vision as the most common domains for adversarial attacks due to the potential to perturb images whilst being challenging to identify issues in deep learning because of complex architecture.

Originality/value

The study presented in this paper identifies research trends, author contributions and open research challenges that can facilitate further research in this domain.

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Case study
Publication date: 12 June 2015

Gaurav Shobhane, Bhaumik Jain, Gautam Anchalia and Ayush Agrawal

In December 2015, 196 countries will meet in Paris to reach a new global climate change agreement. This case looks at the climate negotiation process from the eyes of India's…

Abstract

In December 2015, 196 countries will meet in Paris to reach a new global climate change agreement. This case looks at the climate negotiation process from the eyes of India's environment minister Mr Prakash Javadekar. In India's context, the energy sector has a big role to play in emission reduction as it is the largest emitter of the GHGs. When compared to US and China, India's per-capita emissions are miniscule but they are expected to rise substantially as the GoI is investing heavily in the infrastructure sector which has a substantial carbon footprint. The case discusses the mandatory emission cuts that India will announce considering the fulfillment of sustainable development goals. The case also points out, the government's promise of providing 24*7 electricity by 2019 which it feels can be an impediment in setting an aggressive emission cut target. The case questions if changes in the portfolio mix can be a part of the solution.

Details

Indian Institute of Management Ahmedabad, vol. no.
Type: Case Study
ISSN: 2633-3260
Published by: Indian Institute of Management Ahmedabad

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Article
Publication date: 3 August 2023

Gaurav Kabra

Blockchain technology (BCT) has multiple benefits across industries in varied contexts, but limited organizations have adopted such disruptive innovative technologies in the…

236

Abstract

Purpose

Blockchain technology (BCT) has multiple benefits across industries in varied contexts, but limited organizations have adopted such disruptive innovative technologies in the healthcare industry in India. The research on advancing the understanding of blockchain adoption (BCA) determinants in India's healthcare industry is limited. Thus, the study aims to identify the BCA determinants in the healthcare sector in India. Further, the impact of BCA was examined on organizational performance (OP).

Design/methodology/approach

The study utilizes Technology, Organization, and Environment (TOE) framework to investigate the determinants of BCA in the healthcare sector in India. The data were gathered using a seven-point Likert seven-point ranging from “strongly agree” to “strongly disagree” from 272 respondents working in the healthcare industry in India. The relationship within the framework was investigated using structural equation modeling.

Findings

The results demonstrate the positive impact of top management support, organizational size, organizational readiness, competitive pressure and government support on BCA in the healthcare sector. On the other hand, compatibility, security and privacy issues do not affect BCA. The results emphasize and validate blockchain’s importance in improving OP in the healthcare sector. Further, the results indicate that non-technological factors are paramount to improving BCA within the healthcare sector. Organizations should invest in employee training and development to ensure their staff have the necessary knowledge and skills to effectively manage BCT.

Research limitations/implications

The model was developed for BCA in the healthcare sector in the Indian context; however, the model applies to other countries with the same business environment. Hence, the model can be further examined in diverse countries to generalize the findings.

Practical implications

The study offers valuable insights into the factors that influence BCA and OP in the healthcare sector. The results of this research can be used to inform policy decisions and guide practitioners toward promoting and facilitating the use of BCT in healthcare organizations.

Originality/value

To the best of the author’s knowledge, the present study is the first of its kind to examine the TOE framework in BCA within the healthcare sector and its implications on OP.

Details

American Journal of Business, vol. 38 no. 3
Type: Research Article
ISSN: 1935-519X

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Article
Publication date: 19 June 2020

Priyanka Pathak, M.P. Singh and Gaurav Kumar Badhotiya

Manufacturing organization has adopted the concept of sustainability to improve the performance of product and process as well as to focus on environmental issues. Despite…

277

Abstract

Purpose

Manufacturing organization has adopted the concept of sustainability to improve the performance of product and process as well as to focus on environmental issues. Despite technological advancements and awareness, there exist several performance obstacles for the implementation of sustainable manufacturing in an organization. The objective of the current study is to identify the performance obstacles, propose a structural model and validate the proposed model.

Design/methodology/approach

Twelve performance obstacles are identified through critical literature review and discussion with field experts. Primary and secondary factor analysis, that is, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), are used for the creation of the structural model, and further, structural equation modeling is used as a validating tool. EFA deals with the categorization of all performance obstacles in four major criteria, and CFA works for proposing a model for a relationship among all obstacles.

Findings

A validated structural model is provided through hypothesis acceptance for structural equation modeling. The outcome of this study can be helpful for decision-makers to incorporate sustainable practices in the manufacturing organization.

Originality/value

This study has extracted and identified performance obstacles for the implementation of sustainable manufacturing based on critical literature review and discussion with field experts. The study proposes as well as validates the structural equation model.

Details

Journal of Advances in Management Research, vol. 17 no. 4
Type: Research Article
ISSN: 0972-7981

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Article
Publication date: 26 January 2022

Vineet Tambe, Gaurav Bansod, Soumya Khurana and Shardul Khandekar

The purpose of this study is to test the Internet of things (IoT) devices with respect to reliability and quality.

224

Abstract

Purpose

The purpose of this study is to test the Internet of things (IoT) devices with respect to reliability and quality.

Design/methodology/approach

In this paper, the authors have presented the analysis on design metrics such as perception, communication and computation layers for a constrained environment. In this paper, based on their literature survey, the authors have also presented a study that shows multipath routing is more efficient than single-path, and the retransmission mechanism is not preferable in an IoT environment.

Findings

This paper discusses the reliability of various layers of IoT subject methodologies used in those layers. The authors ran performance tests on Arduino nano and raspberry pi using the AES-128 algorithm. It was empirically determined that the time required to process a message increases exponentially and is more than what benchmark time estimates as the message size is increased. From these results, the authors can accurately determine the optimal size of the message that can be processed by an IoT system employing controllers, which are running 8-bit or 64-bit architectures.

Originality/value

The authors have tested the performance of standard security algorithms on different computational architectures and discuss the implications of the results. Empirical results demonstrate that encryption and decryption times increase nonlinearly rather than linearly as message size increases.

Details

International Journal of Quality & Reliability Management, vol. 39 no. 7
Type: Research Article
ISSN: 0265-671X

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Article
Publication date: 24 August 2021

Richard Boachie, Godfred Aawaar and Daniel Domeher

The purpose of this paper is to analyse the relationship between financial inclusion, banking stability and economic growth in sub-Saharan African countries given the…

944

Abstract

Purpose

The purpose of this paper is to analyse the relationship between financial inclusion, banking stability and economic growth in sub-Saharan African countries given the interconnectedness between them. Globally, financial inclusion has gained recognition as a critical channel for promoting economic growth by bringing a large proportion of the unbanked population into the formal financial system. This cannot be achieved exclusive of the banking sector.

Design/methodology/approach

This paper focussed on 18 countries in sub-Saharan Africa. Data on financial inclusion and the economy were obtained from the World Bank, and bank soundness indicators data were also obtained from International Monetary Fund covering the 11-year period from 2008 through 2018. Panel system generalised method of moments is employed for the regression analysis because it has the capability to produce unbiased and consistent results even if there is endogeneity in the model.

Findings

The results show that economic growth drives banking stability and not vice versa; confirming a unidirectional causality from gross domestic product to banking stability. So, this study finds support for the demand-following hypothesis. The paper further observed that financial inclusion positively and significantly influences the stability of banks and economic growth. The study established that bank capital regulation negatively influences banking stability in sub-Saharan African countries.

Research limitations/implications

This study does not capture the unique country-specific relationship.

Practical implications

The policy implication is that policymakers in sub-Saharan African countries should focus on growth-enhancing policies that improve the level of financial inclusion. The central banks in sub-Saharan African countries should take advantage of the positive effect of financial inclusion to develop regulatory frameworks and policies that make it attractive for banks to continue to expand their operations to the unbanked.

Originality/value

This is, as far as the authors know, the explanation of the interconnection of financial inclusion, banking stability and economic growth in sub-Saharan Africa.

Details

Journal of Economic and Administrative Sciences, vol. 39 no. 3
Type: Research Article
ISSN: 2054-6238

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Article
Publication date: 14 August 2017

Neha Verma and Jatinder Singh

The purpose of this paper is to explore various limitations of conventional mining systems in extracting useful buying patterns from retail transactional databases flooded with…

1921

Abstract

Purpose

The purpose of this paper is to explore various limitations of conventional mining systems in extracting useful buying patterns from retail transactional databases flooded with Big Data. The key objective is to assist retail business owners to better understand the purchase needs of their customers and hence to attract customers to physical retail stores away from competitor e-commerce websites.

Design/methodology/approach

This paper employs a systematic and category-based review of relevant literature to explore the challenges possessed by Big Data for retail industry followed by discussion and implementation of association between MapReduce based Apriori association mining and Hadoop-based intelligent cloud architecture.

Findings

The findings reveal that conventional mining algorithms have not evolved to support Big Data analysis as required by modern retail businesses. They require a lot of resources such as memory and computational engines. This study aims to develop MR-Apriori algorithm in the form of IRM tool to address all these issues in an efficient manner.

Research limitations/implications

The paper suggests that a lot of research is yet to be done in market basket analysis, if full potential of cloud-based Big Data framework is required to be utilized.

Originality/value

This research arms the retail business owners with innovative IRM tool to easily extract comprehensive knowledge of useful buying patterns of customers to increase profits. This study experimentally verifies the effectiveness of proposed algorithm.

Details

Industrial Management & Data Systems, vol. 117 no. 7
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 11 November 2019

Brijesh Kumar, Veer Pal Singh, Vikas Pathak and Akhilesh K. Verma

This paper aims to assess the effect of natural antioxidants (Tulsi, Lemon grass and Aloevera) on sensory and microbiological quality as well as on Thiobarbituric acid (TBA…

157

Abstract

Purpose

This paper aims to assess the effect of natural antioxidants (Tulsi, Lemon grass and Aloevera) on sensory and microbiological quality as well as on Thiobarbituric acid (TBA) values of Redplum and Sahiwal-based milk smoothies stored under refrigeration.

Design/methodology/approach

The smoothies were developed by incorporating optimum level of natural antioxidants, fresh red plum and Sahiwal milk. They were aerobically packaged in low-density polyethylene pouches and stored under refrigeration (4 ± 2°C) till its spoilage. These smoothies were assessed for various storage quality parameters like sensory parameters, microbiological quality and TBA values at regular interval of two days.

Findings

Smoothies made without using natural antioxidants were in good condition for four days, and treated smoothies were stored well for six days. The microbial profile showed significant (p < 0.05) increase in SPC and psychrophilic counts on advancement of storage days. However, no coliform and yeast and mould were detected in all variants of smoothies during storage. TBA values were also increased during storage. But microbial counts and TBA both were under the prescribed limit as described by various organizations. Smoothies treated with Tulsi were found best followed by lemongrass- and aloevera-treated products.

Research limitations/implications

Amino acid and fatty acid profiling may be incorporated to known how the exact nutritional value.

Practical implications

Developed milk smoothies using natural antioxidants may serve the purpose of functional food.

Social implications

As per the authors, today, world is seeking for health providing components with longer product shelf life. Therefore, the product may serve the purpose.

Originality/value

The paper has demonstrated that the Sahiwal milk and red plum-based smoothies were of high acceptability. Their shelf life was found best when treated with Tulsi, Lemon grass and Aloevera natural antioxidants. It was better in all spectrums like lower microbial counts, higher sensory attributes and lower TBA counts as compared to untreated products.

Details

Nutrition & Food Science , vol. 49 no. 6
Type: Research Article
ISSN: 0034-6659

Keywords

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