Search results

The field of machine vision, or computer vision, has been growing at fast pace. The growth in this field, unlike most established fields, has been both in breadth and depth of concepts and techniques. Machine vision techniques are being applied in areas ranging from medical imaging to remote sensing, industrial inspection to document processing and nanotechnology to multimedia databases. The goal of a machine vision system is to create a model of the real world from images. Computer vision recognition has attracted the attention of researchers in many application areas and has been used to solve many ranges of problems. The purpose of this paper is to consider recognition of objects manufactured in mechanical industry. Mechanically manufactured parts have recognition difficulties due to manufacturing process including machine malfunctioning, tool wear and variations in raw material. This paper considers the problem of recognizing and classifying the objects of such parts. RGB images of five objects are used as an input. The Fourier descriptor technique is used for recognition of objects. Artificial neural network (ANN) is used for classification of five different objects. These objects are kept in different orientations for invariant rotation, translation and scaling. The feed forward neural network with back-propagation learning algorithm is used to train the network. This paper shows the effect of different network architecture and numbers of hidden nodes on the classification accuracy of objects.

The overall goal of this research is to develop algorithms for feature-based recognition of 2D parts from intensity images. Most present industrial vision systems are custom-designed systems, which can only handle a specific application. This is not surprising, since different applications have different geometry, different reflectance properties of the parts.

Classification accuracy is affected by the changing network architecture. ANN is computationally demanding and slow. A total of 20 hidden nodes network structure produced the best results at 500 iterations (90 percent accuracy based on overall accuracy and 87.50 percent based on κ coefficient). So, 20 hidden nodes are selected for further analysis. The learning rate is set to 0.1, and momentum term used is 0.2 that give the best results architectures. The confusion matrix also shows the accuracy of the classifier. Hence, with these results the proposed system can be used efficiently for more objects.

After calculating the variation of overall accuracy with different network architectures, the results of different configuration of the sample size of 50 testing images are taken. Table II shows the results of the confusion matrix obtained on these testing samples of objects.

The rapid expansion of artificial intelligence (AI) is progressively reshaping the dynamics of human interaction, communication, lifestyle, education and professional endeavors. The purpose of the study is to comprehend and address the barriers which are impeding the implementation of Generative AI Technologies, such as ChatGPT in the educational landscape.

The study used the Fuzzy analytic hierarchy process (AHP) model to analyze the responses gathered from 149 academicians belonging to the northern states of India.

The study established that the three most important criteria that influence the adoption of generative AI in the education sector are Risk of Academic Integrity, Risk of biased outcomes and Erosion of Critical Thinking.

The present study was confined to Fuzzy AHP to extract the critical criteria influencing the decision-making. Various other techniques such as PF-Delphi and PF-CoCoSo can be used further. The results provide significant inputs for future research to understand the effect of adoption of Generative AI in different contexts including both opportunities and the challenges faced by them.

The study will be beneficial to various stakeholders including students, educators, society and policymakers as the study will highlight the importance of AI tools, introduce the various challenges associated with and explain the use of these tools as productivity-enhancing tools.

To the best of the author’s knowledge, the present study is a novice as the use of AI in Academia is unexplored and the major criteria influencing the choices have yet been undiscovered.

This paper aims to explore knowledge management (KM) literature to understand the relationships among different KM practices and organizational performance (OP) in terms of the four balanced scorecard (BSC) outcomes, i.e. learning and growth, internal process, customer satisfaction and financial performance, as a measure of OP.

A systematic review of peer-reviewed journal articles has been carried out of theoretical and empirical articles to understand the linkages between KM practices and OP, accessed mainly through sources, such as ProQuest, EBSCO host, Google Scholar and other e-databases. Measures of OP have also been extracted from the literature and grouped under the four BSC outcomes to gauge the gravity of the effect. An integrated conceptual framework helps to explore the relationship between the said variables.

This study provides a conceptual model of the effect of various KM practices on different aspects of OP measured through BSC. It contributes to organizations by helping them understand the importance of integration of the KM efforts to obtain desirable results. It will, for the first time, put the entire organization in perspective and help managers draw a bigger picture to understand the overall effect of KM practices.

First, the KM practices shortlisted for this research are extensive but the list may not be exhaustive. Second, the model is not empirically proved. Findings of the study would help in creating a roadmap to enhance performance by a successful implementation of KM practices.

This paper contributes to KM literature by adding the fact that KM practices not only affect learning and growth perspective of an organization but also have far-reaching effects on OP in terms of customer service perspective, internal process perspective and financial perspective.

The digital content distribution environment is undergoing a dramatic transformation due to the convergence of internet of things (IoT) and over-the-top (OTT) platforms, which provide users with personalised and immersive experiences. OTT streaming platforms have not only grabbed the attention of customers for entertainment and quality content for binge-watch but also successfully changed the industry market trends. An empirical analysis of the deployment of IoT technology in OTT platforms is presented in this chapter. This chapter tries to explore the perception of viewers towards adoption of IoT in OTT streaming platforms. The unified theory of acceptance and use of technology-2 (UTAUT2) model is the main framework for this chapter, and one-way analysis of variance (ANOVA) and stepwise regression is applied to analyse the responses. Findings suggested the consumer characteristics have significant effect on the attitude of the consumers. On the other hand, security and privacy issues with data become major obstacles. In order to balance innovation and user protection, the study concluded with recommendations for OTT service providers and legislators on how to support the responsible and successful implementation of IoT technology in the media and entertainment sector. The findings highlighted that viewers are adopting IoT while streaming OTT platforms. This chapter will help the interested parties and organisations by providing them insights regarding consumer behaviour across OTT services which they can utilise to formulate strategies.

The purpose of this study is to develop a decomposed model to inspect the effect of knowledge management practices (knowledge sharing culture [KSC], knowledge-based human resource management [KHRM], strategy and leadership [S&L], information and communication technology [ICT] on organizational performance [OP]) by using the four balanced scorecard outcomes (BSC) (learning and growth [L&G], internal process [IP] perspective, customer satisfaction [CS] perspective and financial performance [FP]).

The research methodology included development of a research model based on comprehensive literature review followed by survey of knowledge-intensive organizations. A sample of 277 employees was obtained and structured equation modeling analysis using SPSS AMOS was conducted to test the proposed hypotheses.

The study shows that KSC and KHRM have a highly significant effect on all the four aspects of OP; S&L positively and significantly affects only L&G and IP but does not have any significant effect on the other two, i.e. CS and FP, while ICT practices did not affect any of the measures significantly.

The data are limited to 277 middle and senior level managers of Indian firms, which may be a limiting factor for generalizability.

The proposed model uncovers the dynamics of individual relationships between KM practices and measures of performance (proposed by BSC) in comparison to existing models which have mainly focused on the overall effect.

This study is the maiden attempt to understand the effect of specific human resource practices (HRPs) on employee retention (ER) with the mediation of job satisfaction (JS) and moderation of work experience (WE) and job hopping (JH) in the context of the textile industry.

This study adopted a quantitative methodology and applied quota sampling to gather data from employees (n = 365) of leading textile companies in India. The conceptual model and hypotheses were tested with the help of Partial Least Squares-Structural Equation Modelling (PLS-SEM).

The findings of a path analysis revealed that compensation and performance appraisal (CPA) have the highest impact on JS followed by employee work participation (EWP). On the other hand, EWP had the highest impact on ER followed by grievance handling (GRH). The study revealed that JS significantly mediates between HRPs like CPA and ER. During Multi-group analysis (MGA) it was found that the importance of EWP and health and safety (HAS) was more in employee groups with higher WE, but it was the opposite in the case of CPA. In the case of JH behavior, the study observed that EWP leads to JS in loyal employees. Similarly, JS led to ER, and the effect was more pronounced for loyal employees.

In the context of the Indian textile industry, this work is the first attempt to comprehend how HRPs affect ER. Secondly, it confirmed that JS is not a guaranteed mediator between HRPs and ER, it could act as an insignificant, partial or full mediator. Additionally, this study establishes the moderating effects of WE and JH in the model through multigroup analysis.

Optifit, an international brand of fitness equipment, had entered the Indian market in 2010 and had rapidly opened 45 stores in 8 years in the four metros (NCR region, Mumbai, Chennai and Kolkata). Jaiveer Roy was identified by Pravin Gupta (South Zone head) and Raghav Mehta (HR head) to join as Optifit's Store Manager for its Alwarpet branch, Chennai, a store that had leadership difficulties from the day it started in May 2018. Roy joined the store in May 2018 and did very well soon after his appointment to the store. However, in less than three months, both Roy's and his store's performance began to suffer and his relationship with Gupta began to crumble. This case highlights issues in people management, especially support for people selected for leadership positions and examines the performance indicators of an individual's performance at a broader level. The case also points towards the mistakes or errors leaders may commit vis-a-vis their own role as a leader and mentor.

The purpose of this paper is to determine the role of service quality (SQ), trust and commitment to customer loyalty (CL) for telecom service users. Further, the moderating role of gender, marital status and connection type within the model was tested.

A measurement model was created based on valid 615 responses from Indian TSUs for SQ, trust, commitment and loyalty with the help of partial least squares structural equation modeling (PLS-SEM). Multi-group analysis (MGA) was conducted to understand the moderating effect of marital status, gender and connection type within the model.

The results suggest that, out of five dimensions of SQ, only responsiveness, assurance and empathy have a significant positive relationship with both commitment and trust. Tangibility has a significant positive relationship with trust only. Both commitment and trust have a significant impact on loyalty. It was noticed that both commitment and trust act as mediators between three SQ dimensions (assurance, empathy and responsiveness) and CL. MGA revealed that empathy and responsiveness positively induce trust in telecom users who are single. Whereas, assurance increases commitment toward telecom service providers in married users. Assurance and empathy significantly contribute toward commitment and trust, respectively, in male users as compared to females. Empathy was found important for postpaid users for trust-building, whereas trust was found to be more important for prepaid users to stay loyal to the service provider.

This article contributes toward understanding the role of SQ, trust and commitment to CL moderated by marital status, gender and connection type in an integrated model concerning telecom service.

The objective of this study is to investigate how country risk, different political actions from the government and bureaucratic behavior influence the activities in industry supply chains (SCs) in emerging markets. The main objective of this study is to investigate the influence of these external stakeholders’ elements to the demand-side and supply-side drivers and barriers for improving competitiveness of Ready-Made Garment (RMG) industry in the way of analyzing supply chain. Considering the phenomenon of recent change in the RMG business environment and the competitiveness issues this study uses the principles of stakeholder and resource dependence theory and aims to find out some factors which influence to make an efficient supply chain for improving competitiveness. The RMG industry of Bangladesh is the case application of this study. Following a positivist paradigm, this study adopts a two phase sequential mixed-method research design consisting of qualitative and quantitative approaches. A tentative research model is developed first based on extensive literature review. Qualitative field study is then carried out to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. A survey is carried out with sample of top and middle level executives of different garment companies of Dhaka city in Bangladesh and the collected quantitative data are analyzed by partial least square-based structural equation modeling. The findings support eight hypotheses. From the analysis the external stakeholders’ elements like bureaucratic behavior and country risk have significant influence to the barriers. From the internal stakeholders’ point of view the manufacturers’ and buyers’ drivers have significant influence on the competitiveness. Therefore, stakeholders need to take proper action to reduce the barriers and increase the drivers, as the drivers have positive influence to improve competitiveness.

This study has both theoretical and practical contributions. This study represents an important contribution to the theory by integrating two theoretical perceptions to identify factors of the RMG industry’s SC that affect the competitiveness of the RMG industry. This research study contributes to the understanding of both external and internal stakeholders of national and international perspectives in the RMG (textile and clothing) business. It combines the insights of stakeholder and resource dependence theories along with the concept of the SC in improving effectiveness. In a practical sense, this study certainly contributes to the Bangladeshi RMG industry. In accordance with the desire of the RMG manufacturers, the research has shown that some influential constructs of the RMG industry’s SC affect the competitiveness of the RMG industry. The outcome of the study is useful for various stakeholders of the Bangladeshi RMG industry sector ranging from the government to various private organizations. The applications of this study are extendable through further adaptation in other industries and various geographic contexts.