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Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.

Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lightning prediction.

The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.

The research is limited to the data collected in support of weather prediction work through the 45th Weather Squadron of the United States Air Force.

These methods are important due to the increasing reliance on sensor systems. These systems often provide incomplete and chaotic data, which must be used despite collection limitations. This work establishes a viable data imputation methodology.

Improved lightning prediction, as with any improved prediction methods for natural weather events, can save lives and resources due to timely, cautious behaviors as a result of the predictions.

Based on the authors’ knowledge, this is a novel application of these imputation methods and the forecasting methods.

Even though extant research highlights the crucial role some stakeholders play in helping corporations understand, manage and mitigate the occurrence of modern slavery in their supply chains and operations, there is a fundamental lack of understanding of all the relevant stakeholder groups and the specific roles they play. By adopting a stakeholder theory approach, this study aims to identify all the key stakeholders and their associated roles towards supporting corporations’ modern slavery monitoring, detection and disclosure activities.

A systematic literature review was conducted by following the PRISMA guidelines. Relevant literature included scholarly work focusing on the identification of key stakeholders and the roles they play in enabling corporations’ modern slavery monitoring, detection and disclosure activities.

Nine stakeholder groups and their roles were identified, such as governments, workers, IGOs, NGOs and suppliers. Examples of performed activities include conducting audits, providing training, monitoring occurrences of modern slavery, enforcing regulations, reporting on labour issues and evaluating corporations’ modern slavery reports.

A comprehensive understanding of key stakeholders and their roles enables better collaboration towards achieving transparency within corporations’ supply chains and operations. Other stakeholders can leverage these findings to enhance modern slavery reporting activities.

Clarity regarding key stakeholders and their roles may improve quality and quantity of reported modern slavery information, enhancing corporations’ public accountability.

This study adopts a stakeholder theory approach to provide a comprehensive understanding of key stakeholders and their roles in enhancing corporations’ modern slavery reporting activities.

The purpse of this study is to examine sustainable technology development (STD) during the “Valley of Death” phase encountered by university startups undertaking intellectual property rights (IPR) commercialisation.

A comprehensive literature review was conducted after searching for relevant documents across multiple databases. Semi-structured interviews with university startup founders were also conducted as part of a qualitative case study.

This study resulted in two significant findings. First, the Valley of Death has been redefined in the specific context of IPR commercialisation by university startups. Second, the sustainable technology development framework (STDF) has been conceptualised to enhance the success rate of IPR commercialisation by university startups. The authors also identified three essential components of STD in the context of university startups: market development, technical efficiency and business sustainability.

This exploratory research involved a thorough literature analysis. Given that only one qualitative case study was conducted, data saturation was not achieved. Further empirical research is needed to validate the conceptualised STDF.

The validated STDF will be a useful tool for enhancing the success of IPR commercialisation by university startups.

While others have focused on innovating business models, this study focused on an underexplored area: the sustainability of technology development during the commercialisation of IPR by university startups during the Valley of Death phase.

This study aims to explore the key challenges and drawbacks of smart contracts (SCs) and how they impact digital resilience within small and medium enterprises (SMEs). Whilst this type of technology is seen as a step forward in terms of traceability, transparency and immutability to increase digital resilience, we argue that it should be approached with trepidation.

In developing this paper, the authors conduct a systematic literature search using the Scopus database. Through this, we identified 931 relevant articles, of which 30 were used as the focus of this article. Thematic analysis was used as the analytical approach to develop themes and meaning from the data.

In this paper, there is an emphasis on the importance of understanding the potential risks associated with SC implementation, as well as identifying appropriate strategies for mitigating any negative impact. In our findings, we puts forward three key themes, namely legality, security and human error, which we argue are key smart contract challenges that impact SME digital resilience.

In this paper, we propose the notion of “centralised control in decentralised solutions”. This comes from the research highlighting SC weaknesses in digital resilience for SMEs. We argue that there is a need for standards, regulations and legislation to address these issues, advocating, ironically, a centralised approach to decentralised technology.

This chapter focuses on two aspects of the achievement gap – underachievement and low achievement among Black males in urban school contexts. More specifically, the authors explain several problems/issues confronting Black male students in P-12 gifted and talented, advanced placement, and special education programs, along with the school-to-prison pipeline – inequitable discipline in the form of suspensions and expulsions. We parse underrepresentation and overrepresentation for this student group. A central part of this discussion is grounded in the achievement gap literature on Black students in general with implications for Black males in particular. Another fundamental aspect of this discussion is the need for educators to adopt an anti-racist (social justice or civil rights) and cultural competence approach to their work, which means being equity-based and culturally responsive in philosophy and action. Suggestions for closing the achievement gap and otherwise improving the achievement of Black males are provided for educators. We also compel educators to go beyond talking about equity by setting quantifiable equity goals for minimum and maximum percentages (and numbers).

The new disruption in the form of ChatGPT can be a valuable tool for organizations to enhance their knowledge management and decision-making capabilities. This article explores how ChatGPT can enhance organizations' KM capability for improved decision-making and identifies potential risks and opportunities.

Using existing literature and a small-scale case study, we develop a conceptual framework for implementing artificial intelligence on the internal organizational knowledge base of big data and its integration with a larger knowledge base of ChatGPT.

This viewpoint conceptualizes integrating knowledge management and ChatGPT for improved organizational decision-making. By facilitating efficient information retrieval, personalized learning, collaborative knowledge sharing, real-time decision support, and continuous improvement, ChatGPT can help organizations stay competitive and achieve business success.

This is one of the first studies on the integration of organizational knowledge management systems with ChatGPT. This research work proposes a conceptual model on integration of knowledge management with generative AI which can be further tested in actual work settings to check it's applicability and make further modifications.

The study provided insights to managers and executives who, in collaboration with IT professionals, can devise a mechanism for integrating existing knowledge management systems in organizations with ChatGPT.

This is one of the first studies exploring the linkage between ChatGPT and knowledge management for informed decision-making.