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Federation analytics approaches are a present area of study that has already progressed beyond the analysis of metrics and counts. It is possible to acquire aggregated information about on-device data by training machine learning models using federated learning techniques without any of the raw data ever having to leave the devices in the issue. Web browser forensics research has been focused on individual Web browsers or architectural analysis of specific log files rather than on broad topics. This paper aims to propose major tools used for Web browser analysis.

Each kind of Web browser has its own unique set of features. This allows the user to choose their preferred browsers or to check out many browsers at once. If a forensic examiner has access to just one Web browser's log files, he/she makes it difficult to determine which sites a person has visited. The agent must thus be capable of analyzing all currently available Web browsers on a single workstation and doing an integrated study of various Web browsers.

Federated learning has emerged as a training paradigm in such settings. Web browser forensics research in general has focused on certain browsers or the computational modeling of specific log files. Internet users engage in a wide range of activities using an internet browser, such as searching for information and sending e-mails.

It is also essential that the investigator have access to user activity when conducting an inquiry. This data, which may be used to assess information retrieval activities, is very critical. In this paper, the authors purposed a major tool used for Web browser analysis. This study's proposed algorithm is capable of protecting data privacy effectively in real-world experiments.

The purpose of this study was to evaluate the impact of leadership development programme on enhancing leadership competencies of physicians in India. Assessment of leadership competencies of physicians is critical for designing suitable leadership development programmes. The previous studies of authors have revealed significant gaps in leadership competencies among physicians in India. Hence, authors have designed a programme incorporating various facets of health-care leadership and evaluated its impact on improvement of leadership competencies of top- and mid-career level professionals.

A six-day offsite residential programme incorporating a three-day component of leadership development was organized, in which 96 physicians participated. A mix of pedagogical approaches was used. A pre- and post-assessment of 30 medical leadership competencies was done using a self-administered questionnaire.

Majority of participants (69%) scored their competencies at Level 3 and Level 4 (Average to Good) with a mean score ranging from 3.20 ± 0.85 to 4.12 ± 0.71 in the pre-assessment group. In contrast, in post-assessment, this shifted to Level 4 and Level 5 (Good to Very good) in 72% with mean scores ranging from 3.8 to 4.24. Statistically significant differentiation was noted in pre- and post-assessment mean scores for all 30 competencies. The maximum improvement was noted in Competency 29 “Information management system planning and implementation”, whereas the least improvement was noted in Competency 12 “Holding self and others accountable and responsible for organizational goal attainment”.

The authors believe that this is the first study from India to assess effectiveness of leadership development programmes on enhancing medical leadership competencies demonstrating positive outcome. The findings of this study can provide a roadmap for designing of future medical leadership development programmes for physicians in India.

Leadership skills are vital for efficient delivery of health reforms. India, a low- and middle-income country, is transforming its public health care significantly. The health workforce, particularly doctors, however lacks leadership skills. This study aims to highlight the leadership skills gap and raise concerns about how India might achieve its ambitious health reforms in the lack of formal, prospective leadership training for its workforce.

This study conducted nine management development programmes between 2012 and 2020 and collected data from 416 (N = 444, 94% response rate) health-care professionals using a questionnaire. Participants were asked to inform leadership challenges that they perceived critical. A total of 47 unique challenges were identified, which were distributed across five domains of American College of Healthcare Executives Competency Assessment Tool (2020). Relevant information was also obtained from review of secondary sources including journal articles from scientific and grey literature and government websites.

Majority of participants (85.36%) had never attended any management training and were from public sector (56.1%). Mean total experience was 18 years. Top 5 challenges were lack of motivation (54.26%), communication (52.38%), contracts management (48.31%), leadership skills (47.26%) and retention of workforce (45.56%). Maximum challenges (29) were in domain of business skills and knowledge, followed by knowledge of health-care environment (9), leadership, professionalism, and communication and relationship management (3 each).

In absence of the leadership training, senior health professionals particularly doctors in India, suffer leadership challenges. Efforts should be made to strengthen leadership capacity in Indian health-care system to advance the country’s ongoing national health reforms.

In January 2021, India launched the world’s most extensive vaccination campaign against COVID-19. It is estimated that India would need to vaccinate over a billion people to achieve herd immunity. Even though the Indian Government focuses on improving and delivering its vaccination programme, significant challenges still exist. This paper aims to discuss current challenges to scale up India’s vaccination campaign and addresses strategies for achieving this.

The paper is based on a review of secondary sources, including journal articles from scholarly and grey literature and information available in the public domain. The search focused explicitly on the COVID-19 scenario, vaccination programme, public health management and systems leadership in the Indian health care system.

The analysis revealed that various factors have disrupted India’s vaccination campaign, including shortage of vaccine doses, mandatory prior online registration, lack of infrastructure, safety concerns for older people, untrained workforce and absence of a solid public health framework. Furthermore, India appears to have struggled to reduce tensions and instill trust in its ability to effectively manage the COVID-19 pandemic and vaccination programme due to a lack of cooperation between union government, state governments and other stakeholders, namely, policymakers, hospitals, industry and community.

The findings indicate that scaling up India’s anti-COVID vaccination programme would require system-level leadership strategies that work within the country’s limited resources. Deeper reforms in vaccine development, storage, delivery, training and regulatory frameworks are also needed to extend the world’s largest anti-COVID-19 vaccination campaign.

The young population of the globe is defined by individuals aged 15 to 24 years. Based on statistics from the Instituto Brasileiro de Geografia e Estatística (IBGE), the second largest women population among 15 years as well as 19 years was in 2017 only behind 35 and 39 years. At this time, the Brazilian male population was higher. The difficulties of the young generation affected the preceding generation and promoted social dynamism. The worldwide data shows that the generation of young and the digital world have been constantly sought, but in reality, approximately one-third of the population in 2017 had no access to the internet.

The worldwide movement around topics such as strategy on its threefold basis and Industry 4.0 enable a link to company duty towards society to be established. This present study was produced from 1 March 2020 to 2 September 2020 via resources of human and literature evaluation relating to the idea of strategic, Industry 4.0, the responsibility of society and the creation of youth. Its motive is the global creation of youth. Two recommendations should be made after studying the literature and information gathering that enabled “analyzing social responsibility of the company and industry 4.0 with a pivot on young creation: a strategic framework for resources of human management”.

The adoption of defensible practices and technology bring forth by the revolution in industrial is emphasized worldwide.

The focus on the usage of these ideas is essential, so that young people can absorb the workforce in the labour market. To achieve this, the CSR idea combines this theoretical triple-created recent study.

The purpose of this paper Computing is a recent emerging cloud model that affords clients limitless facilities, lowers the rate of customer storing and computation and progresses the ease of use, leading to a surge in the number of enterprises and individuals storing data in the cloud. Cloud services are used by various organizations (education, medical and commercial) to store their data. In the health-care industry, for example, patient medical data is outsourced to a cloud server. Instead of relying onmedical service providers, clients can access theirmedical data over the cloud.

This section explains the proposed cloud-based health-care system for secure data storage and access control called hash-based ciphertext policy attribute-based encryption with signature (hCP-ABES). It provides access control with finer granularity, security, authentication and user confidentiality of medical data. It enhances ciphertext-policy attribute-based encryption (CP-ABE) with hashing, encryption and signature. The proposed architecture includes protection mechanisms to guarantee that health-care and medical information can be securely exchanged between health systems via the cloud. Figure 2 depicts the proposed work's architectural design.

For health-care-related applications, safe contact with common documents hosted on a cloud server is becoming increasingly important. However, there are numerous constraints to designing an effective and safe data access method, including cloud server performance, a high number of data users and various security requirements. This work adds hashing and signature to the classic CP-ABE technique. It protects the confidentiality of health-care data while also allowing for fine-grained access control. According to an analysis of security needs, this work fulfills the privacy and integrity of health information using federated learning.

The Internet of Things (IoT) technology and smart diagnostic implants have enhanced health-care systems by allowing for remote access and screening of patients’ health issues at any time and from any location. Medical IoT devices monitor patients’ health status and combine this information into medical records, which are then transferred to the cloud and viewed by health providers for decision-making. However, when it comes to information transfer, the security and secrecy of electronic health records become a major concern. This work offers effective data storage and access control for a smart healthcare system to protect confidentiality. CP-ABE ensures data confidentiality and also allows control on data access at a finer level. Furthermore, it allows owners to set up a dynamic patients health data sharing policy under the cloud layer. hCP-ABES proposed fine-grained data access, security, authentication and user privacy of medical data. This paper enhances CP-ABE with hashing, encryption and signature. The proposed method has been evaluated, and the results signify that the proposed hCP-ABES is feasible compared to other access control schemes using federated learning.

“Machine learning (ML)” in business aids in increasing company scalability and boosting company operations for businesses all over the world. “Artificial intelligence (AI)” technologies and several “ML” algorithms have grown in prominence in the business analytics sector. In the era of a huge quantum of data being generated by the virtue of the integration of the various software with the business operations, the relevance of “ML” is continuously increasing. As a result, companies may now profit from knowing how companies may use “ML” and incorporating it into their own operations. “ML” derives useful results from the data to address very dynamic and difficult social and business problems. ML helps in establishing a system that learns automatically and produces results in less time and effort, allowing machines to discover. ML is developing at a breakneck pace, fuelled mostly by new computer technology to competitive advantages during the COVID pandemic.

For firms all around the world, “ML” in business aids in expanding scalability and boosting operations. In the field of business analytics, artificial intelligence (AI) and machine learning (ML) algorithms have become increasingly popular. The importance of “ML” is growing in an era when a massive amount of data is generated as a result of the integration of various applications with company activities. As a result, businesses can now benefit from understanding how other businesses are using “ML” and adopting it into their own operations. In order to handle very dynamic and demanding societal and business challenges, machine learning (ML) extracts valuable results from data. Machine learning (ML) aids in the development of a system that learns automatically and generates outcomes with less time and effort, allowing machines to discover. ML is progressing at a dizzying pace, fueled primarily by new computer technology and used to gain competitive advantages during the COVID pandemic.

According to a new study published by the Accenture Institute for High Performance, “AI” might double yearly economic growth rates in several wealthy nations by 2035. With broad AI deployment, the yearly growth rate in the USA increased from 2.6% to 4.6%, resulting in an extra $8.3tn. In the UK, AI may contribute $814bn to the economy, raising the yearly growth rate from 2.5% to 3.9%. The authors are already in a business period when huge technological development is assisting us in addressing a variety of difficulties to achieve maximum development. AI technology has enormous developmental consequences. In addition, big data analytics is helping to make AI more enterprise ready. Future developments in “ML” cannot be understated. Machines will very certainly eventually be smarter than humans in practically every way.

The introduction of AI into the market has enabled small businesses to use tried-and-true strategies for achieving greater business objectives. AI is continually offering a competitive advantage to start-ups, whilst large corporations provide a platform for building novel solutions. AI has become an integral component of reality, from functioning as a robot in a production unit to self-driving automobiles and voice activated resources in complex medical procedures. As a consequence, solving the difficulties highlighted below and finding out how to collaborate with robots will be a constant problem for the human species (Sujaya and Bhaskar, 2021).

In the field of cryptography, authentication, secrecy and identification can be accomplished by use of secret keys for any computer-based system. The need to acquire certificates endorsed through CA to substantiate users for the barter of encoded communications is one of the most significant constraints for the extensive recognition of PKC, as the technique takes too much time and susceptible to error. PKC’s certificate and key management operating costs are reduced with IBC. IBE is a crucial primeval in IBC. The thought behind presenting the IBE scheme was to diminish the complexity of certificate and key management, but it also gives rise to key escrow and key revocation problem, which provides access to unauthorised users for the encrypted information.

This paper aims to compare the result of IIBES with the existing system and to provide security analysis for the same and the proposed system can be used for the security in federated learning.

Furthermore, it can be implemented using other encryption/decryption algorithms like elliptic curve cryptography (ECC) to compare the execution efficiency. The proposed system can be used for the security in federated learning.

As a result, a novel enhanced IBE scheme: IIBES is suggested and implemented in JAVA programming language using RSA algorithm, which eradicates the key escrow problem through eliminating the need for a KGC and key revocation problem by sing sub-KGC (SKGC) and a shared secret with nonce. IIBES also provides authentication through IBS as well as it can be used for securing the data in federated learning.

The purpose of this paper is to secure health data collection and transmission (SHDCT). In this system, a native network consists of portable smart devices that interact with multiple gateways. It entails IoMT devices and wearables connecting to exchange sensitive data with a sensor node which performs the aggeration process and then communicates the data using a Fog server. If the aggregator sensor loses the connection from the Fog server, it will be unable to submit data directly to the Fog server. The node transmits encrypted information with a neighboring sensor and sends it to the Fog server integrated with federated learning, which encrypts data to the existing data. The fog server performs the operations on the measured data, and the values are stored in the local storage area and later it is updated to the cloud server.

SHDCT uses an Internet-of-things (IoT)-based monitoring network, making it possible for smart devices to connect and interact with each other. The main purpose of the monitoring network has been in the collection of biological data and additional information from mobile devices to the patients. The monitoring network is composed of three different types of smart devices that is at the heart of the IoT.

It has been addressed in this work how to design an architecture for safe data aggregation in heterogeneous IoT-federated learning-enabled wireless sensor networks (WSNs), which makes use of basic encoding and data aggregation methods to achieve this. The authors suggest that the small gateway node (SGN) captures all of the sensed data from the SD and uses a simple, lightweight encoding scheme and cryptographic techniques to convey the data to the gateway node (GWN). The GWN gets all of the medical data from SGN and ensures that the data is accurate and up to date. If the data obtained is trustworthy, then the medical data should be aggregated and sent to the Fog server for further processing. The Java programming language simulates and analyzes the proposed SHDCT model for deployment and message initiation. When comparing the SHDCT scheme to the SPPDA and electrohydrodynamic atomisation (EHDA) schemes, the results show that the SHDCT method performs significantly better. When compared with the SPPDA and EHDA schemes, the suggested SHDCT plan necessitates a lower communication cost. In comparison to EHDA and SPPDA, SHDCT achieves 4.72% and 13.59% less, respectively. When compared to other transmission techniques, SHDCT has a higher transmission ratio. When compared with EHDA and SPPDA, SHDCT achieves 8.47% and 24.41% higher transmission ratios, respectively. When compared with other ways it uses less electricity. When compared with EHDA and SPPDA, SHDCT achieves 5.85% and 18.86% greater residual energy, respectively.

In the health care sector, a series of interconnected medical devices collect data using IoT networks in the health care domain. Preventive, predictive, personalized and participatory care is becoming increasingly popular in the health care sector. Safe data collection and transfer to a centralized server is a challenging scenario. This study presents a mechanism for SHDCT. The mechanism consists of Smart healthcare IoT devices working on federated learning that link up with one another to exchange health data. Health data is sensitive and needs to be exchanged securely and efficiently. In the mechanism, the sensing devices send data to a SGN. This SGN uses a lightweight encoding scheme and performs cryptography techniques to communicate the data with the GWN. The GWN gets all the health data from the SGN and makes it possible to confirm that the data is validated. If the received data is reliable, then aggregate the medical data and transmit it to the Fog server for further process. The performance parameters are compared with the other systems in terms of communication costs, transmission ratio and energy use.

The COVID-19 virus outbreak began in December 2019 and rapidly spread to every continent on Earth. The analysts have predicted that COVID-19 and other similar pandemics will continue in the coming decade and badly affect offline businesses. As a result, the offline platform is also shifting to the online platform and online demands are increasing daily. The traditional two-dimensional E-Commerce websites are designed to provide simple, browser-based interfaces to allow users to access available products and services. Whilst virtual representations are an essential consideration in establishing trust, most virtual representation sites fall short in mimicking real-life human representation. This paper aims to focus on three-dimensional (3D) E-Commerce technology that presents how virtual reality (VR) and augmented reality (AR) can help deal with limitations and improve E-Commerce operations. It is built as an internet-only tool, a person-centred shopping assistant created following user-centred design principles to be used on various computing platforms, including desktop and mobile devices. The paper shows how VR and AR can offer more precise product information in 3D E-Commerce environments. The virtual store experience is also enhanced by an AR assistant that helps the users by giving them all the required information in audio form or using its avatar.

Implementation of VR and AR in E-Commerce will increase customer satisfaction. Sub hypothesis – to study the implementation of VR in E-Commerce. To study the implementation of AR in E-Commerce. To study the inclusion of E-Commerce sites in an open-world game. To study the customer satisfaction of users using VR stores.

The scope of work is concentrated on the urban Indian market especially targeting the country’s youth who are already or ready to indulge in VR such as video games, cinema and other activities (Mattsson and Barkman, 2019). This demography is more open to learning and using VR. The primary segment of E-Commerce that we are concentrating upon is fashion. Here, the regular user needs to have more immersed knowledge about the product rather than just the written information like how would they look in a dress or will the size available on the website fit me or not.

A perfect system does not exist in the world. A terrible disease has landed on the planet. Very soon, it will be impossible to escape from this current situation. The effects of this plague have been felt in every sector of the world. The researchers also claim that physical stores will continue to exist. There will never be anything that replaces the ability to hold and use products or have personal face-to-face interactions with retail professionals. For the time being, brick-and-mortar retail is having a difficult time, but immersive technology is starting to be used to enhance the in-store experience. The good news is that this should help retailers increase their chances of survival. However, the melody of 3D E-Commerce is it would help out the in-store experience.