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Secure communication is very important for computer networks. Thereby, authentication is one of the most eminent preconditions. In ad hoc networks, common authentication schemes are not applicable since public key infrastructures with a centralized certification authority are hard to deploy in ad hoc networking environments. This paper aims to investigate these issues.

In order to overcome these issues, the paper proposes and evaluates a security concept based on a distributed certification facility. Thereby, a network is divided into clusters with one special head node each. These cluster head nodes perform administrative functions and hold shares of a network key used for certification. New nodes start to participate in the network as guests; they can only become full members with a network‐signed certificate after their authenticity has been warranted by some other members. Access to resources and services within the ad hoc network is controlled using authorization certificates.

The feasibility of this concept was verified by simulations. Three different models for node mobility were used in order to include realistic scenarios as well as to make the results comparable to other work. The simulation results include an evaluation of the log‐on times, availability, and communication overhead.

The paper introduces a cluster‐based architecture to realize a distributed public key infrastructure that is highly adapted to the characteristics of ad hoc networks.

The purpose of this paper is to compare the transformational leadership style of women business owners and those women in the top position of organizations with women executives who are not in the top leadership position of organizations.

A quantitative approach using a population and business owners and executives from the private sector of the American Management Association.

The findings support the relationship between a woman owning a business or being in the top position and the increased use of transformational leadership behaviors.

The paper analyzes data collected in 1997 and the changes to the demographics may in fact be a limitation of the study.

The study focuses on the importance of contextual considerations in the study of women and their use of transformational leadership.

This paper proposes an algorithm for the extraction of reduced order models of MEMS switches, based on using a physics aware simplification technique.

The reduced model is built progressively by increasing the complexity of the physical model. The approach starts with static analyses and continues with dynamic ones. Physical phenomena are introduced sequentially in the reduced model whose order is increased until accuracy, computed by assessing forces that are kept in the reduced model, is acceptable.

The technique is exemplified for RF-MEMS switches, but it can be extended for any device where physical phenomena can be included one by one, in a hierarchy of models. The extraction technique is based on analogies that are carried out for both the multiphysics and the full-wave electromagnetic phenomena and their couplings. In the final model, the multiphysics electromechanical phenomena is reduced to a system with lumped components with nonlinear elastic and damping forces, coupled with a system with distributed and lumped components which represents the reduced model of the RF electromagnetic phenomena.

Contrary to the order reduction by projection methods, this approach has the advantage that the simplified model can be easily understood, the equations and variables have significance for the user and the algorithm starts with a model of minimal order, which is increased until the approximation error is acceptable. The novelty of the proposed method is that, being tailored to a specific application, it is able to keep physical interpretation inside the reduced model. This is the reason why, the obtained model has an extremely low order, much lower than the one achievable with general state-of-the-art procedures.

This study aims to identify and explain a possible gender pay gap in the creative industry. By using the salary information of Hollywood actors, this paper restricts the analysis to a relatively homogenous group of workers. In addition, actors' human capital endowments and past performance can be measured precisely. The factors that impact the salaries of movie stars are likely to influence the pay of other high-wage employees, such as athletes and executives.

This paper uses a rich panel data set including 178 female and male actors in 973 movies released between 1980 and 2019. Using a random-effects model and the Blinder–Oaxaca decomposition approach, this paper distinguishes between a fraction of the gender pay gap that can be explained and another fraction that cannot be explained. Hence, only the unexplained residual typically obtained by estimating two standard Mincer-type earnings functions is due to discriminatory pay practices.

This study reveals a pay difference between female and male actors. Gender-specific representation in leading roles and systematic differences in performance measures can explain this pay difference. While female actors' underrepresentation in leading roles reflects consumer tastes and, therefore, reflects discriminatory attitudes, no evidence can be found for direct pay discrimination in Hollywood's movie business.

To the best of the authors’ knowledge, this is the first Hollywood study to relying on a rich panel data set that includes various measures of the human capital characteristics of the different individual actors. This paper's theoretical contribution lies in applying classic labor economics reasoning to explain pay determination in Hollywood's movie business.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.

Pancho’s Burritos is a high-end fast-food restaurant located in Charlottesville, Virginia. Due to a recent surge in customers, the lines at the restaurant during peak hours are becoming very long and causing excessive customer waiting. To improve current customer wait times and plan for future growth requirements, Francisco “Pancho” Escoba, the proprietor, wants to get a better understanding of the current operational capacity. The key decision Escoba must make is how to redesign his burrito-making process to increase the capacity and reduce customer wait time.

Suitable for an undergraduate or MBA course, the case can be used in an introductory operations course to teach capacity analysis and queuing. The case provides a relatable and understandable setting for students without an operations background to gain a better grasp of basic course concepts and illustrates how interactions between capacity and queuing affect one another. As an exam or review case it works well because it contains standard process calculations that all students should know how to perform.

The purpose of this case study is to describe the Costa Rican coffee roaster and retail company Grupo Britt and provides sufficient information for readers to discuss the company's growth options in the US and Latin American markets. It has been prepared to facilitate discussion and learning about appropriate growth strategies and the building, positioning and branding of companies from emerging economies within the internationalization processes.

The case study is based on primary research conducted in conjunction with the company, including interviews with senior management and an ample review of documents. Secondary research was also conducted into the relevant environmental, industry and competitor trends and characteristics.

The case presents the ways in which Grupo Britt has been successful in developing a new business model based on the concept of a “sense of place.” This translates as meaning that the company generates products and services that highlight the particular characteristics of the place(s) in which it operates.

This is a complex, in‐depth case study suitable for use with advanced MBA students and practitioners. Depending on the aims of the instructor, different aspects of the case can be highlighted and it can be used in a course or module focussing on strategies for growth or internationalization, international business or marketing, or brand management

This paper examines the impact of extreme rainfall shocks on the performance in test scores of students living near at-risk urban areas in Brazil.

To identify the causal effect, we consider the exogenous variation of rainfall at the municipal level conditioned on the distance from the school to risk areas and the rainfall intensity in the school months.

The results suggest that extreme precipitation shocks, defined as a shock of at least three months of high-intensity rainfall, have an adverse impact on both math and language performance. Through a heterogeneous effects analysis, we find that the impact varies by student gender, with girls being more affected. In addition, among students who study near at-risk areas, those with better previous school performance and higher socioeconomic status are more negatively affected.

Our results suggest that extreme weather events can increase the differences in human capital accumulation between the population living near risk areas and those living more distant from these areas.

The purpose of this paper is to analyze volatility transmission between the Japanese stock and foreign exchange markets.

In contrast to the existing literature, industry‐level stock data are applied to a trivariate Baba, Engle, Kraft and Kroner‐generalised autoregressive conditional heteroscedasticity (BEKK‐GARCH) model that also includes comparable US industrial stocks returns as a control variable.

Using daily data over the study period 1994‐2007, it was found that news shocks in the Japanese currency market account for volatility transmission in eight of the ten industrial sectors considered. Evidence was also found of significant asymmetric effects in five of these industries.

While the BEKK‐GARCH model enables analysis of volatility transmission between the stock and foreign markets against a background of conditional correlation and asymmetries, the model requires the estimation of a large number of parameters, which can be problematic for a limited dataset.

The paper's findings have important implications for understanding international volatility transmission involving the stock and foreign exchange markets. This in turn can provide insight into investor behaviour.