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This study aims to design a facility network for the weavers to do direct business in the Indian handloom industry by using tourists as potential customers.

Data from 4,001 weavers of the handloom industry and 82 tourist locations of Varanasi city were collected. This data was analysed using the k-mean and elbow methods to determine the locations and the optimal number of collection centres, selling stores and warehouses to provide opportunities for the weavers to do direct business.

The study's findings showed that a greater opportunity could be provided with four optimal collection centres and selling stores, along with two warehouses in the handloom industry of Varanasi city. These results provide valuable guidance for policymakers to plan the Varanasi handloom network of facilities efficiently and effectively to improve the conditions of weavers.

Determining the optimal locations is crucial for designing a facility network. The proposed network will aid the government and policymakers in comprehending and pinpointing potential sites to establish new facilities in the handloom industry in Varanasi, a city with tourism potential.

This paper aims to identify and analyze the challenges for the Varanasi handloom industry after the COVID pandemic by considering their impact on different sections of the weavers and subsequently suggest the best possible solution for the same.

A combined approach of expert opinion and in-depth literature reviews are used to identify the challenges, and a multicriteria decision-making tool is used to rank the challenges for the type of weaver.

This research provides an elaborated view of the problems faced by the handloom industry after the COVID pandemic and suggests that the success of the handloom business is subjected to the eradication of a wide number of challenges according to the type of weaver.

The findings of this research will help the policymakers to make and align their policies and strategies for the upliftment of the Varanasi handloom industry efficiently and effectively.

To the best of the authors’ knowledge, this is the first kind of study that focuses on identifying and prioritizing the barriers affecting the success of the Varanasi handloom industry after the COVID pandemic. Furthermore, the uniqueness of this research lies in its ability to study all three independent sections of the handloom industry, having different capabilities and limitations.

This study aims to explore the essence of the omnichannel in the handloom industry’s development and to identify, analyse and estimate the barriers obstructing the implementation of the omnichannel in the handloom industry of India.

A descriptive literature review and expert opinion are used to identify the barriers obstructing the successful realisation of the omnichannel in the handloom industry of India. Moreover, interpretive structural modeling and the matrix of cross-impact multiplications applied to classification are used to analyse and estimate the impact of these barriers.

This research suggests the implementation of the omnichannel is subjected to several barriers, specifically lack of government support and policies, uncertainty in business contract partners, poor reverse logistics system, etc.

This research explores the contribution of the handloom industry to the socioeconomic development of the rural and semi-urban Indian population. It also explores the need for government support for the survival and growth of the handloom industry. It also explains how omnichannel can support this industry for its survival and its overall development. Furthermore, factors inhibiting the implementation of the omnichannel in the handloom industry are identified and evaluated based on their over impact.

The study aims to analyze factors impacting firms’ success and persistence in a digital platform competition using the structure-conduct-performance (SCP) framework. The study also includes real-life cases that are beneficial to academicians and practitioners to understand and develop strategies for success and persistence during uncertainty.

A literature review to identify the factors that impact success and persistence in a digital platform competition was conducted following Webster and Watson (2002). Findings were integrated into a SCP framework to examine and understand the identified factors’ relational impact.

While analyzing factors under the SCP framework, all factors were divided into three categories: those impacting positively, those impacting negatively and those with ambiguous impact on the success and persistence in digital platform competition. Digital platform firms can exploit the positively impacting factors to increase market share by being distinctive from other digital platform firms and becoming dominant by withstanding competition. On the other hand, negatively impacting factors increase barriers to entry, intensify competition and reduce the distinctiveness of digital platform firms. Lastly, a few factors may have either a positive or a negative impact depending upon the particular characteristics of the firm/industry.

The study opens the scope for future research on empirically testing the developed conceptual framework and relationships by developing propositions to posit the possible impact of these factors on digital platforms’ success and persistence.

The study contributed to the existing literature by using SCP framework to analyze the factors affecting firm’s success and persistence in a digital platform competition. Also, the study has discussed the relational impact of factors rather than their impact in isolation.

There are various system techniques or models which are used for access control by performing cryptographic operations and characterizing to provide an efficient cloud and in Internet of Things (IoT) access control. Particularly in cloud computing environment, there is a large-scale distribution of these traditional symmetric cryptographic techniques. These symmetric cryptographic techniques use the same key for encryption and decryption processes. However, during the execution of these phases, they are under the problems of key distribution and management. The purpose of this study is to provide efficient key management and key distribution in cloud computing environment.

This paper uses the Cipher text-Policy Attribute-Based Encryption (CP-ABE) technique with proper access control policy which is used to provide the data owner’s control and share the data through encryption process in Cloud and IoT environment. The data are shared with the the help of cloud storage, even in presence of authorized users. The main method used in this research is Enhanced CP-ABE Serialization (E-CP-ABES) approach.

The results are measured by means of encryption, completion and decryption time that showed better results when compared with the existing CP-ABE technique. The comparative analysis has showed that the proposed E-CP-ABES has obtained better results of 2373 ms for completion time for 256 key lengths, whereas the existing CP-ABE has obtained 3129 ms of completion time. In addition to this, the existing Advanced Encryption Standard (AES) scheme showed 3449 ms of completion time.

The proposed research work uses an E-CP-ABES access control technique that verifies the hidden attributes having a very sensitive dataset constraint and provides solution to the key management problem and access control mechanism existing in IOT and cloud computing environment. The novelty of the research is that the proposed E-CP-ABES incorporates extensible, partially hidden constraint policy by using a process known as serialization procedure and it serializes to a byte stream. Redundant residue number system is considered to remove errors that occur during the processing of bits or data obtained from the serialization. The data stream is recovered using the Deserialization process.

This study aims to examine the factors that impact the choice of paddy marketing channels in India at the farm level and household contingencies.

Employing multinomial logistic regression, the analysis utilizes the National Sample Survey Office (NSSO) 77th round Situation Assessment Survey (SAS) data from the 2018 to 2019 period, specifically for the paddy Kharif season, to determine the factors determining the choice of marketing channels. The significant independent variables include minimum support price (MSP) awareness, access to and adoption of technical advice, input agency, social group, farm size of farmers, region, age and education of the household head.

Awareness of MSP and adoption of technical advice from experts can enhance the probability of selecting government channels for paddy. The reliance on government input agencies has a favourable impact on the choice of government channels. Government channels are more likely preferred by higher social groups and those with higher land-holdings. There has been a state-wise variation in access to regulated marketing channels for paddy.

Transaction cost associated with marketing channel choice is an important factor, not incorporated in this study due to the unavailability in the NSS data.

The research uses the latest unit-level data of the NSSO 77th round, published by the Ministry of Statistics and Programme Implementation (MoSPI), the Government of India.

This Friction stir welding study aims to weld thick AA8011 aluminium plates, and the interface joints created with a variety of tool pin profiles were examined for their effects on the welding process.

Scanning electron microscopy and optical microscopy and X-ray diffraction were used to examine the macro and micro-structural characteristics, as well as the fracture surfaces, of tensile specimens. The mechanical properties (tensile, hardness tests) of the base metal and the welded specimens under a variety of situations being tested. Additionally, a fracture toughness test was used to analyse the resilience of the base metal and the best weldments to crack formation. Using a response surface methodology with a Box–Behnken design, the optimum values for the three key parameters (rotational speed, welding speed and tool pin profile) positively affecting the weld quality were established.

The results demonstrate that a defect-free junction can be obtained by using a cylindrical tool pin profile, increasing the rotational speed while decreasing the welding speeds. The high temperature and compressive residual stress generated during welding leads to the increase in grain size. The grain size of the welded zone for optimal conditions is significantly smaller and the hardness of the stir zone is higher than the other experimental run parameters.

The work focuses on the careful examination of microstructures behaviour under various tool pin profile responsible for the change in mechanical properties. The mathematical model generated using Taguchi approach and parameters was optimized by using multi-objectives response surface methodology techniques.

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

Blockchain is a nascent technology that has the ability to revolutionize the workings of the educational landscape. However, there are several barriers to the adoption of blockchain technology (BCT). So, this paper aims to determine, rank and analyse the interdependent contextual relationship among the BCT adoption barriers within the education management system (EMS) of higher education institutes.

The present research principally uses the technology-organization-environment model for the classification of BCT adoption barriers in the EMS. An integrated dual phase best-worst method and interpretive structural modelling – cross-impact matrix multiplication applied to classification (BWM-ISM-MICMAC) analysis is used for the identification, prioritization and analysis of the contextual relationships among the BCT barriers.

The findings of the research show that the environmental barrier among the primary barriers and the lack of government initiatives among the sub-barriers are crucial barriers to BCT adoption in the EMS.

Certain barriers might not be selected during the literature review and expert opinions might be biased. Future studies should use structural equation modelling to validate the relationships between BCT barriers and conduct similar research across other business sectors to provide valuable insights for scholars and practitioners alike.

The study facilitates a better perspective of BCT barriers and explores possible solutions more comprehensively for policymakers and field managers. Consequently, it offers viable suggestions for the successful and effective implementation of BCT within the EMS.

The concept of using the blockchain in academics is a novel one. This study establishes a crucial research base for the smooth adoption of BCT in EMS.

Accurate 6D object pose estimation is essential for various robotic tasks. Uncertain pose estimates can lead to task failures; however, a certain degree of error in the pose estimates is often acceptable. This paper aims to enable the robots to make informed decisions by quantifying errors in the object pose estimate and acceptable errors for task success.

In this paper, the authors introduce a framework for evaluating robotic task success under object pose uncertainty, representing both the estimated error space of the object pose and the acceptable error space for task success using multi-modal non-parametric probability distributions. The proposed framework pre-computes the acceptable error space for task success using dynamic simulations and subsequently integrates the pre-computed acceptable error space over the estimated error space of the object pose to predict the likelihood of the task succes.

The authors evaluated the proposed framework on two mobile manipulation tasks. Their results show that by representing the estimated and the acceptable error space using multi-modal non-parametric distributions, the authors achieve higher task success rates and fewer failures.

Their proposed framework is generic and can be applied to a wide range of robotic tasks requiring object pose estimation. Hence, given the recent advancements in object pose uncertainty estimation and dynamic simulations, the proposed framework, in conjunction with these advancements, has the potential to enable robots to make reliable and informed decisions under pose uncertainty.

Unlike related works that model both acceptable error space and estimated error space using parametric uni-modal distributions, the authors model them as multi-modal distributions which is often the case in the real world.