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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.

By a thorough bibliometric examination of the area through time, this paper analyses the research landscape of metaverse in education. It is an effort that is focused on the metaverse research trends, academic production and conceptual focus of scientific publications.

The Web of Science (WoS) database was explored for information containing research articles and associated publications that met the requirements. For a thorough analysis of the trend, thematic focus and scientific output in the subject of metaverse in education, a bibliometric technique was used to analyse the data. The bibliometrix package of R software, specifically the biblioshiny interface of R-studio, was used to conduct the analysis.

The analysis of the metaverse in education spanning from 1995 to the beginning of 2023 reveals a dynamic and evolving landscape. Notably, the field has experienced robust annual growth, with a peak of publications in 2022. Citation analysis highlights seminal works, with Dionisio et al. (2013) leading discussions on the transition of virtual worlds into intricate digital cultures. Thematic mapping identifies dominant themes such as “system,” “augmented reality” and “information technology,” indicating a strong technological focus. Surprisingly, China emerges as a leading contributor with significant citation impact, emphasising the global nature of metaverse research. The thematic map suggests ongoing developments in performance and future aspects, emphasising the essential role of emerging technologies like artificial intelligence and virtual reality. Overall, the findings depict a vibrant and multidimensional metaverse in education, poised for continued exploration and innovation.

The study is among the pioneers that provide a comprehensive bibliometric analysis in the area of metaverse in education which will guide the novice researchers to identify the unexplored areas.

The purpose of this study is to develop the scale of the metaverse experience and examine the effect of the metaverse experience on consumer happiness in luxury brands.

A survey was distributed to metaverse users from general participants in the Republic of Korea. To reach this goal, the domain of the metaverse experience is defined, items are created through qualitative interviews, the initial scale is refined and then the scale is tested. A total of 262 valid responses were used for exploratory factor analysis (EFA), and 238 data were used for confirmatory factor analysis (CFA). The hypothesis was tested using structural equation modeling (SEM) and SmartPLS 3.0.

The results showed that the metaverse experience comprises three sub-constructs, namely fantasies, feelings and fun. Also, the metaverse experience affects consumer happiness positively in luxury brands.

This study investigates consumer experience in the metaverse environment. The authors examined the metaverse experience based on the experiential aspects of the consumption of luxury brands and develop the scale development of the metaverse experience. Furthermore, the relationship between metaverse experiences and consumer happiness provides a new perspective in studying metaverse marketing strategy and customer service creation.

This research paper aims to conceptually explain the dark side of the metaverse from customers’ perspective in the hospitality and tourism industry.

A comprehensive analysis of the existing academic and practice-based literature on the metaverse, including its related concepts such as social media and e-commerce, was undertaken to conceptualise the metaverse dark side.

This research posits a theoretical framework highlighting five pivotal dark sides of the metaverse that is physiological, psychological, legal, security and privacy and societal issues. Each identified concern is examined to unveil various potential consequences, providing a comprehensive understanding of the challenges posed by the metaverse for customers in tourism and hospitality.

To the best of the authors’ knowledge, this study stands out as the first of its kind to illuminate the adverse aspects of the metaverse from the viewpoint of tourism and hospitality customers. The arguments offered herein not only serve to raise awareness but also facilitate understanding of the darkverse among policymakers, government and metaverse business organisations. This awareness is crucial for the efficient and effective implementation of this novel innovative technology to enhance the customer experience in tourism and hospitality.

The paper aims to focus on underpinning the moderating role of work meaningfulness in alleviating the impact of general job demands on burnout directly and via work–family conflict by drawing on the conservation of resources theory.

Survey methodology was used for this study, using standardized instruments to assess general job demands, meaningfulness, work–family conflict and burnout. The survey was administered to school teachers (n = 800), and the data set was analyzed through SmartPLS 4.0.

This study ascertained that work meaningfulness moderated the relationship between general job demands and burnout. This study also found that general job demands under conditions of low work meaningfulness positively affected burnout through work–family conflict, thereby validating the moderated mediation model.

While several studies have established the relationship between general job demands, work–family conflict and burnout, to the best of the authors’ knowledge, this is the first study that examined the moderating role of work meaningfulness in the relationship, where work meaningfulness has emerged as a suitable moderator in lowering the impact of job demands on burnout via a work–family conflict. This study contributes to the extant literature on work meaningfulness and adds utility to practice.

The study examined the impact of two dimensions of curiosity: joyous exploration (JE) and deprivation sensitivity (DSv) on informal learning effort (ILE) and attitude toward knowledge sharing (ATKS). The authors further explored the mediating effect of learning culture (LC) in the organization on the relationship of the two curiosity dimensions with ILE and ATKS. Additionally, the authors investigated the moderating effect of group dynamics in the form of intragroup task conflict (ITC) and relationship conflict (IRC) on the relationship of curiosity variables with LC, ILE and ATKS.

Survey instrument was distributed to 790 knowledge workers in various organizations through their HR managers. 403 responses were returned and used in the study.

JE, the self-determined manifestation of curiosity, impacts all elements of ILE and ATKS, while DSv influences a few aspects of ILE. The effect of JE on the dependent variables is, however, more substantial at low levels of ITC. ITC and IRC independently impact ILE, but only ITC moderates the relationships involving JE (but not DSv). LC emerges from JE (but not from DSv) and partially mediates its association with ILE and ATKS.

Through this work, we demonstrate the differential relevance of the curiosity dimensions and the intragroup conflict types – and their interaction effect – on learning effort and attitude toward knowledge sharing. The findings of the study open new avenues for interventions within the workplace learning and knowledge sharing domain.

Induction heating applications aided by power electronic control have become very attractive in the recent past. For cooking applications, power electronics circuits are very suitable to feed power to multi loads with an appropriate control technique. The purpose of this paper is to develop a three leg inverter to feed power to three loads simultaneously and independently.

Pulse density modulation control technique is used to control the output power independently with constant switching frequency.

Multi-load handling converter with independent power control is achieved with reduced number of switching devices (two switches/per load) with simple control strategy.

The proposed system is simulated in MATLAB/Simulink, and the thermal analysis is carried out in COMSOL multi-physics software. The hardware realisation is performed for a 1 kW prototype with 20 kHz switching frequency and 10 kHz pulse density modulation frequency. PIC16F877A microcontroller is used to validate the experimental results for various values of control signals (D_PDM). The simulation and experimental results are in good agreement and validates the developed system.

Knowledge acquired by employees from co-workers through social networks may serve to reduce technostress during the use of a new and complex information system. The role of gender-based employee preferences in forming and acquiring system-related knowledge through friendship, advice, and expertise networks, and the impact of network-embedded expertise on performance outcomes are explored.

The research hypotheses were empirically tested through survey data collected from employees of a large organization that had implemented an enterprise system.

The advice networks of female employees were an extension of their friendship networks, whereas that of male employees were configured to include co-workers with system-related expertise. Exposure to high quality knowledge flows resulted in lowered technostress levels among male employees compared to their female counterparts. However, there was only a marginal difference in performance outcomes. The “expertise-deficit” in the advice network of female employees was apparently compensated through their dependence on the helpdesk.

Research on system-related knowledge support through social networks has focused on the structural features of interaction ties with little or no emphasis on networking employees and their individual preferences. Moving away from this structural orientation, this study validates the contention that gender-driven motivations impact employee networking preferences, determine network-embedded expertise levels, and influence employee technostress. This study can help configure implementation environments that maximize network acquisition of high-quality knowledge, reduce technostress, and enhance performance outcomes.

The purpose of this paper is to report a study in which creative design concepts have been applied to automotive brake rotor design.

The literature review on creative design concepts and braking system scenario has been carried out. By studying the existing brake rotors and applying creative design concepts, modified rotor designs have been developed.

The experience gained out of the study indicated that braking efficiency and durability of the braking system can be significantly improved by the adoption of proposed designs.

The research has been carried out for an automotive passenger car. The findings of this research work could be extended to similar models of buses and trucks.

The usage of the proposed designs reduces the driver’s effort in braking and adds significantly to the life of the rotors.

A case study has been reported to indicate the application of creative design concepts for enhancing the efficiency of automotive braking system in cars.

The purpose of this paper is to present research results in analyzing image contents to improve the accuracy of using an artificial neural network (ANN) to detect embedded data in a digital image.

A texture measure based on the MPEG‐7 texture descriptor is applied to assess the local texture amount. Those image blocks with high texture are masked out and the remaining blocks with low texture are used to derive features for an ANN to classify an image as embedded or clear. The high‐texture blocks are not discarded and can be tested independently for embedded data.

By masking out the high‐texture image blocks, an ANN has improved detection performance especially when the original embedding rate is low. Bypassing the low‐texture image blocks do not pay off for a steganographer because the effective embedding rate in the high‐texture blocks is driven higher.

Hidden data detectors should take the image content into account in order to improve detection performance.

The results can be integrated into a steganalytic system.

This paper presents evidence that image texture affects steganalytic performance and proposes a solution that incorporates texture that has improved detection performance.