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To increase protection level against transient faults, circuit designers usually take advantage of redundant structures like Triple Modular Redundancy (TMR). Since redundancy compel a significant power overhead, proposing a low power fault tolerant technique in digital circuits is the main objective of this research work.

In order to moderate power consumption, we use a dual to triple modular redundancy. In fact, we put one of the modules in a TMR system in sleep mode while the other two operating modules are producing the same outputs. Once a mismatch is detected, the third one exits the sleep mode and the dual modular redundancy (DMR) approach turns into a conventional TMR. Also a novel stoppable clock generator is proposed to handle the sleep mode of the third module. Finally, a new three-input majority voter, compatible with our proposed technique, is presented.

Power analysis of combinational circuit benchmarks, ISCAS85, and ISCAS89 as sequential circuit benchmarks are depicted. Simulation results show the power reduction of up to 30% in comparison with the conventional modular redundancy approach.

Since modular redundancy is the most effective and the most well-known fault tolerant approach which is widely used in reliable circuits designs, it is important to reduce its power consumption. In this paper configuring the sleep mode operation of a circuit and stoppable clock generator lead to a new TMR technique in which the power consumption is strongly reduced.

One of the main issues which microelectronics industry encounter is reliability as feature sizes scale down to nano-design level. The purpose of this paper is to provide a probabilistic transfer matrix based to find the accurate and efficient method of finding circuit’s reliability.

The proposed method provides a probabilistic description of faulty behavior and is well-suited to reliability and error susceptibility calculations. The proposed method offers accurate circuit reliability calculations in the presence of reconvergent fanout. Furthermore, a binary probability matrix is used to not only resolve signals correlation problem but also improve the accuracy of the obtained reliability in the presence of reconverging signals.

The results provide the accuracy and computation time of reliability evaluation for ISCAS85 benchmark schemes. Also, simulations have been conducted on some digital circuits involving LGSynth’91 circuits. Simulation results show that proposed solution is a fast method with less complexity and gives an accurate reliability value in comparison with other methods.

The proposed method is the only scheme giving the low calculation time with high accuracy compared to other schemes. The library-based method also is able to evaluate the reliability of every scheme independent from its circuit topology. The comparison exhibits that a designer can save its evaluation time in terms of performance and complexity.

Recent technological developments have encouraged the United Nations to promote the adoption of digital technologies to achieve the Sustainable Development Goals (SDGs). In addition to initiatives from businesses, an increasing number of studies indicate that public service agencies may gain benefits from adopting digital transformation. On a global scale, policymakers are examining the integration of digital technologies, specifically artificial intelligence (AI), into public service delivery (PSD), acknowledging the potential advantages and obstacles for the public sector. Therefore, the objective of this study is to investigate the impact of AI on PSD to support the SDGs initiative.

The research used a qualitative approach to explore the intersection of AI, SDGs and PSD. This approach involved scrutinising relevant publications and conducting an extensive literature review. The research also used bibliographic analysis to discern patterns within the field. Findings from the literature review and bibliographic analysis contributed to identifying research trends that explore the complex relationship among AI, PSD and the SDGs. The model derived from this comprehensive review and analysis elucidates the potential of AI to enhance PSD and contribute to the achievement of the SDGs.

The bibliographic study revealed significant research trends concerning AI, PSD and SDGs through an empirical investigation of an extensive array of peer-reviewed articles. This investigation focused on how the public sector can improve its delivery of services to citizens and all stakeholders to advance the SDGs. AI holds the promise of revolutionising PSD and bolstering the SDGs. By leveraging AI’s capabilities in data analysis, automation and customisation, governments can enhance the efficiency, effectiveness and accessibility of public services. This, in turn, enables public servants to tackle more complex tasks while providing citizens with personalised and relevant experiences. Additionally, the study advocates modelling the intersection of PSD and AI to achieve sustainable development.

The employed research methodologies, such as literature reviews and bibliographic analysis, enrich the context of AI, SDGs and PSD. They offer a comprehensive perspective, identify knowledge gaps and furnish policymakers, practitioners and academics with a conceptual framework for informed decision-making and sustainable development endeavours.

The study provides an agenda for AI and SDGs research on application in PSD. It emphasises varied research viewpoints, methods and gaps. This study helps researchers as well as practitioners identify subtopics, intersecting themes and new research pathways.

The implementation of digital twin in e-government services will become the future of public service delivery. It has a great promise for significantly optimizing e-government service delivery in public services because digital twin can be leveraged to achieve value co-creation, which can be turned for innovation and new knowledge creation. The purpose of this study is to fill a knowledge gap in the domain of e-government with digital twin enabled.

This study examined the concept of digital twins in the context of e-government for innovation management. This research applied exploratory research discussing a dynamic and interpretive model that examines the main factors to consider when developing digital twins for the Fourth Industrial Revolution’s integration of e-government services. This study begins with a thorough assessment and then evaluates the results to propose a model that would be used as a benchmark for future research. Secondary data was gathered from a variety of previously published primary research sources, including peer-reviewed journals, case studies, periodicals, newspapers and books.

E-government with digital twin platform will become increasingly integral to business or public value creation and can be managed individually as people and organizations expect much greater value for their well-being that is linked to a number of better outcomes. E-government with digital twin will no longer to be seen as a static web service but the next enabling platform to offer a comprehensive digital advisory for each and every user. The digital twin’s goal is to extract all of a user’s digital activity processes and thoroughly analyze them across all of e-services. When there are crucial issues or problems that need to be alerted to the (physical) user, the digital twin will present options, solutions and recommendations based on the entire gathered data continuum.

This study is conducted to provide a better understanding of the digital twin’s impact on public service delivery in the future. When it comes to e-government, a digital twin is a digital representation of an individual with the ability to integrate e-government services (such as e-citizenship, e-employment, e-participation, e-business, e-commerce, e-health, e-learning, e-regulation, e-entertainment and so on) with nearly real-time data and advanced analytics. Individuals will be able to improve, discover, foresee and make better and faster decisions as a result of the digital twin. The proposed model shows a future scenario for e-government services, in which the key principle of Industrial Revolution 4.0, Cyber Physical Systems, is accommodated by digital twins.

This study provides academics, policymakers and practitioners in the fields of technology, public and/or private service delivery and public policy, with the opportunity to define priorities, processes and outcomes of e-government services and thereby benefit more directly from the findings of the study. This study presents some novel insights into e-government services the use of digital twins to optimize public service delivery.

The adoption of knowledge management (KM) to steer new skills and capabilities among people provides evidence that KM not only offers competitive advantages but also provides a means for organisational survival, by improvising core capabilities or generate new ones that can drive people in the Fourth Industrial Revolution (4IR) era. This paperaim to identify critical new skills and capabilities among people within an organisation to stay competitive, innovative and relevant.

The paper presents the findings on new skills assessment for Fourth Industrial Revolution. The study was carried out through an interview with a focus group discussion technique to gather data on the role of KM in creating new set of skills or capabilities in Fourth Industrial Revolution’s landscape. The study also reports a bibliographic study of critical skills based on more than a decade of related academic and industry publications to portray research trends and future directions.

There is a demand in “must-have” skills related to Industry 4.0 such as capability for complex decision-making, complex problem-solving, collaborative innovation, project management, creativity and critical thinking, social skill and social responsibility. While these skills are critical enablers to aiding individuals in the scenarios of plausible 4IR futures, several important new research trends that emerge have also not been adequately explored including KM and Industry 4.0 skill gap, skill evolution, machine knowledge, intuitive decision-making, rational decision-making, technostress, digital fluency, collaborative innovation, industrial policies, human–machine interaction and societal systems.

This research provides a roadmap for the next research trends and topics in the area of Fourth Industrial Revolution and new skills requirements. The study discusses some of the essential issues and challenges with upskilling required for Industry 4.0. It also focuses on how upskilling learning initiatives influence new knowledge creation. This primarily contributes to the educational field in deciding how and when to adopt appropriate strategies and identify which initiatives to best meet the needs of its community.

KM enables individuals to utilise their existing core capabilities or generate new ones for immediate investment in upskilling to meet current and future skills needs required by an organisation. Simply put, KM will improve the organisation’s talent-driven learning strategy and increase individuals’ ability to learn faster and attain sustainable competitive advantage in a fast-paced ever changing environment.

This paper is useful to academics, practitioners and policymakers in the fields of KM. The research provides initial insight into new skills mapping in the context of Fourth Industrial Revolution and the needs for researchers to understand the recent research trends in KM.

The malfunction variables of power stations are related to the areas of weather, physical structure, control and load behaviour. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behaviour into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms are used to perform the Short-term estimation. The environment, the operation and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a data set. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, for any future power grid, there is a testbed ready to estimate the future failures.

The breakout of the COVID-19 pandemic has forced governments all over the globe to bring radical changes to all walks of life. Strict lockdowns are not only adversely affecting the social, economic, and psychological wellbeing of individuals but also questioning the sustainability of most businesses. In wake of the current scenario, this study is aimed at exploring how the COVID-19 pandemic is influencing the sustainability of entrepreneurship particularly from a female perspective and further providing insights into the role of Islamic financial institutions in the sustainability of businesses during COVID-19.

This is a qualitative study that takes social constructivism approach to study the underlying phenomenon. Semi-structured interviews are conducted to collect primary data. Secondary data are also utilized in this study to theoretically define various concepts relating to entrepreneurial sustainability. The application of thematic analysis revealed various risks associated with sustainability. The interviews reveal the ground realities and tell us about the hardships being faced by the entrepreneurs due to ongoing crises. The participants of the study also shed light on the role of Islamic financial institutions during the pandemic.

The study results revealed that it may look impossible for women entrepreneurs to halt or avoid the adverse consequences of the pandemic; however, a few female entrepreneurs strived to guard their existing portfolios with the help of Islamic microfinance institutions. Whereas, several women, especially those running home-based businesses, lost their income streams. Despite these rapid challenges, most female entrepreneurs are working on inventive online systems to sustain their business activities during the crisis. Finally, guidelines are suggested which can help achieve sustainability of the entrepreneurial startups.

The outcomes of this study are expedient for funding agencies, government authorities and Islamic financial institutions as well as for non-government institutions to establish sustainable and broader policies for women to become successful entrepreneurs during severe disasters like COVID-19. Moreover, the study is a helpful tool for women entrepreneurs to avert the worst impact of the pandemic with the help of Islamic microfinance institutions. The themes of this study help generate realistic information to appraise the strategies to create facilitating business environments that drive the women to carry out the entrepreneurial activity during any crisis like the COVID-19.

The results of this study provide evidence that crisis can be anticipated up to some extent if entrepreneurs become able to take proactive decisions in case of expected or identifiable threats. The study may also help the women entrepreneurs to comprehend the serious consequences of the pandemic by shifting their mode of financing to Islamic finance. Although this pandemic is a cause of physical discomfort instead this research may encourage the female entrepreneurs not to lose heart, just find the potential opportunities for their home-based and small businesses and manage funding from the Islamic microfinance institutions.

The study adds to the existing literature on entrepreneurial sustainability with a particular focus on the role of Islamic microfinance institutions for women entrepreneurs' sustainability in Pakistan. Secondly, the study employs the entrepreneurial sustainability model (ESM) that, according to the best of our knowledge, has not been used by the researchers earlier to study the given research phenomenon. Thirdly, the study findings are expedient for funding agencies, government authorities and financial institutions as well as for non-government institutions to establish sustainable and broader policies for women to become successful entrepreneurs during disasters like COVID-19.

The Asian crisis, which exploded in Thailand in July 1997 initially, spilled to the other ASEAN countries (Indonesia, Malaysia, and Philippines) and later it spreads to Korea and even crossing the continent to Russia and Brazil. The chronological pattern seems to indicate the contagious behaviour of the crisis. However, the sequential economic down‐turns that occurred in the Asia Pacific do look like a contagion effect. The idea that currency speculators contributed to the depth of the crisis is agreeable but to conclude that they are the roots of the problem would be misleading. This paper argued that the roots of the problems lie in current account deficit and loss of competitiveness, and moral hazard and over‐investment This paper also argued that the currency crisis is a symptom and not the cause of the Asian crisis.

The study aims to explore the factors that influence Emirati women's career choice in the UAE. This study contributes to the influence of context in career choices by investigating how Emirati women chose information technology (IT) as a profession through the lens of the social cognitive career theory.

This study undertook in-depth interviews with 21 Emirati women working in technology in the UAE. The study considers women's career choices at three levels, i.e. from an individual, organisational and national context perspective.

The key findings include identifying the importance of national context in influencing career choices among other factors such as family centrality, desire to be seen as a role model, company reputation and government policy.

The study has wider implications for women's career choices in other contexts. The findings highlight the challenges women face, such as a lack of role models and family centrality, which need to be considered in recruitment policies and practices in other national contexts.

The originality of the study is its contribution to the literature developing understanding of the influences on women's career choices in the Emirates. While previous studies have identified the role of patriarchal influence on women's careers, we have less understanding of the importance attributed to individual factors such as being perceived as a role model within their family and to society. Similarly, the literature provides limited evidence of the influence of factors such as government sponsorship and company reputation.