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To operate with high efficiency and minimise the risks of power failures, power systems require careful monitoring. The availability of real-time data is crucial for assessing the performance of the grid and assisting operators in gauging the present security of the grid. Traditional supervisory control and data acquisition (SCADA)-based systems actually employed provides steady-state measurement values which are the calculation premise of State Estimation. More often, however, the power grid operates under dynamic state and SCADA measurements can lead to erroneous and inaccurate calculation results. The introduction of the phasor measurement unit (PMU) which provides real-time synchronised voltage and current phasors with very high accuracy is universally recognised as an important aspect of delivering a secure and sustainable power system. PMUs are a relatively new technology and because of their high procurement and installation costs, it is imperative to develop appropriate methodologies to determine the minimum number of PMUs as well as their strategic placements to guarantee full observability of a power system. Thus, the problem of the optimal PMU placement (OPP) is formulated as an optimisation problem subject to various constraints to minimise the number of PMUs while ensuring complete observability of the grid. In this chapter, integer linear programming (ILP), genetic algorithm (GA) and non-linear programming (NLP) constrained models of the OPP problem are presented. A new methodology is proposed to incorporate several constraints using the NLP. The optimisation methods have been written in Matlab software and verified on the standard Institute of Electrical and Electronics Engineers (IEEE) 14-bus test system to authenticate their effectiveness. This chapter targets United Nations Sustainable Development Goal 7.

Presents a robust and unconditionally stable return‐mapping algorithm based on the discrete counterpart of the principle of maximum plastic dissipation. Develops the explicit expression for the consistent elasto‐plastic tangent modulus. All expressions are derived via tensor formulation showing the advantage over the classical matrix notation. The integration algorithm is implemented in the formulation of the four‐node isoparametric assumed‐strain finite‐rotation shell element employing the Mindlin‐Reissner‐type shell model. By applying the layered model, plastic zones can be displayed through the shell thickness. Material non‐linearity described by the von Mises yield criterion and isotropic hardening is combined with a geometrically non‐linear response assuming finite rotations. Numerical examples illustrate the efficiency of the present formulation in conjunction with the standard Newton iteration approach, in which no line search procedures are required. Demonstrates the excellent performance of the algorithm for large time respective load steps.

This study distinctively explores the firm-level and national-level determinants of audit committee effectiveness (ACE) in the Libyan banking sector (LBS).

A mixed-methods approach has been employed to enhance the quality of the collected data and reduce the risk of bias. Five groups of actors in the Libyan banking sector were surveyed, including board members, AC members, executive managers, internal auditors and external auditors, further to interviewing a representative sample of these groups. In total, 218 survey responses were gathered, and 20 semi-structured interviews were conducted.

The study results show that AC authority, financial expertise and diligence are positively and significantly attributed to ACE, although AC independence and resources are not significantly related to ACE. The authors find that the legal and regulatory environment, government intervention, and the accounting and auditing environment are perceived as important and associated with ACE regarding national-level factors. These findings are strongly supported by semi-structured interviews and suggest that both firm-level and national-level factors are essential in understanding ACE in Libya's banking sector.

The study’s evidence reiterates the vital need for more concentrated work to integrate governance, legislative and regulatory reforms to ensure the effectiveness of ACs as a key corporate governance (CG) mechanism in developing economies.

This study extends the literature relating measures of AC inputs and outputs by examining the perception of stakeholders to understand both the firm-level and national-level factors that affect ACE in a single institutional setting. Additionally, this work adds to the limited number of recent studies examining the role of ACs in the banking sector in developing economies.

The Subject‐Object Relationship Interface model (SORI) described in this paper is a novel approach that displays many of the structures necessary to map between the conceptual level and the external level in a database management system, which is an information‐oriented view of data. The model embodies a semantic synthesiser, which is based on an algorithm that maps the syntactic representation of a tuple or a record onto a semantic representation. This is based on table‐driven semantics which are embedded in the database model. The paper introduces a technique for translating tuples into natural language sentences, and discusses a system that has been fully implemented in PROLOG.

This study aims to test empirically the differences between Islamic and conventional banks in terms of impacts of the audit committees' quality on financial performance between Subprime and Corona crises.

The variables are articulated in four hypotheses tested by the GLS analysis. The data were collected via DATASTREAM and from banks' annual reports. The collected data covered four continents: America, Asia, Africa and Europe. The financial performance measures and audit committee's determinants of the conventional and Islamic banks concerned 112 banks of each type after the Subprime crisis and before the Corona crisis (2010–2019).

Results showed that the audit committee reduced the profitability of two bank types. Moreover, it harmed the conventional banks' efficiency, but reported an unclear effect within Islamic banks. Even so, the authors noticed that the audit committee had a positive impact for the conventional banks' liquidity, while the same effect was apparently ambiguous on the Islamic banks' liquidity. For solvency, the audit committee positively influenced conventional banks, while it affected that of Islamic banks.

Empirically, the authors’ results can serve as a reference for decision-makers allowing to clarify the data on the financial competitiveness of two bank types to facilitate the planning of strategic performance programs based on the audit committee quality. Theoretically, researchers found that the differences between the results are due to the audit committee quality of each bank type or to the financial performance evaluation method. However, there are further factors that are related to the research peculiarities, the methodology, the data and the interpretation.

Based on the comparative literature review between conventional and Islamic banks, this study is the first conditional and comparative research between the audit committee quality and the financial performance of conventional and Islamic banks in a specific period (after Subprime and before Corona crises).

Performing tasks in public spaces can be demanding due to task complexity. Systems that can keep track of the current task state may help their users to successfully fulfill a task. These systems, however, require major implementation effort. The purpose of this paper is to investigate if and how a mobile information assistant which has only basic task-tracking capabilities can support users by employing a least effort approach. This means, we are interested in whether such a system is able to have an impact on the way a workflow in public space is perceived.

The authors implement and test AIRBOT, a mobile chatbot application that can assist air passengers in successfully boarding a plane. The authors apply a three-tier approach and, first, conduct expert and passenger interviews to understand the workflow and the information needs occurring therein; second, the authors implement a mobile chatbot application providing minimum task-tracking capabilities to support travelers by providing boarding-relevant information in a proactive manner. Finally, the authors evaluate this application by means of an in situ study (n = 101 passengers) at a major European airport.

The authors provide evidence that basic task-tracking capabilities are sufficient to affect the users’ task perception. AIRBOT is able to decrease the perceived workload airport services impose on users. It has a negative impact on satisfaction with non-personalized information offered by the airport, though.

The study shows that the number of features is not the most important means to successfully provide assistance in public space workflows. The study can, moreover, serve as a blueprint to design task-based assistants for other contexts.

Security is one of the major challenges in the design and implementation of protocols for mobile ad hoc networks (MANETs). In such systems, the cooperation between nodes is one of the important principles being followed in the current research works to formulate various security protocols. Many existing works assume that mobile nodes will follow prescribed protocols without deviation. However, this is not always the case, because these networks are subjected to a variety of malicious attacks. Since there are various models of attack, trust routing scheme can guarantee security and trust of the network. The purpose of this paper is to propose a novel trusted routing model for mitigating attacks in MANETs.

The proposed model incorporates the concept of trust into the MANETs and applies grey relational analysis theory combined with fuzzy sets to calculate a node’s trust level based on observations from neighbour nodes’ trust level, these trust levels are then used in the routing decision-making process.

In order to prove the applicability of the proposed solution, extensive experiments were conducted to evaluate the efficiency of the proposed model, aiming at improving the network interaction quality, malicious node mitigation and enhancements of the system’s security.

The proposed solution in this paper is a new approach combining the fundamental basics of fuzzy sets with the grey theory, where establishment of trust relationships among participating nodes is critical in order to enable collaborative optimisation of system metrics. Experimental results indicate that the proposed method is useful for reducing the effects of malicious nodes and for the enhancements of system’s security.

This chapter aims to evaluate the relationship between the representation of women on corporate boards of directors and its impact on firm financial performance.

This study utilized both a systematic review and a meta-analysis, using a sample of 40 published studies, which gleaned financial indicator and observation data from 28 different countries.

As indicated in previous studies, while positive, there was no significant correlation found between the number of women serving on the boards of directors and firm financial performance.

The heterogeneity between the various studies analyzed may present difficulties in making general conclusions. The chapter could also be subject to publication bias, as the selection criteria included may indicate a need for further peer review. Future meta-analyses should include data associated with other financial indicators.

This study shows how composition ratios of men/women serving on corporate boards should be addressed in terms of proving for a greater diversity of leadership perspectives.

Previous systematic reviews and meta-analyses have analyzed country environments as moderators for the relationship between the representation of women on corporate boards and firm financial performance. The present study evaluates possible differences between the impact of the number of women serving on the board of directors on a variety of financial indicators (ROA, ROE, and Tobin’s Q).

Prior studies have demonstrated that simple linear discriminant models can be highly successful in identifying financially distressed companies, and therefore useful in predicting corporate failures. Such models have been shown to be both industry and country specific even though their variable selection has been narrow. These models have remained incredibly robust over time despite variations in the definition of the ‘distressed’ state employed for modelling purposes. This paper extends such analysis to the main and second boards of the Kuala Lumpur Stock Exchange (KLSE) in Malaysia, with particular reference to their designation of PN4 companies (those classified as ‘distressed’ in accordance with Practice Note No. 4 introduced in February 2001). The findings of the study show that a single discriminant model has high classificatory power for both boards of the KLSE, and that the optimum model comprises financial ratio variables common to other published models. Previous findings are therefore shown to be substantially generalisable to a new environment and to a different definition of distress.

Dynamic predictions of financial distress of the firms have received less attention in finance literature rather than static prediction, specifically in Malaysia. This study, therefore, investigates dynamic symptoms of the financial distress event a few years before it happened to the firms by using neural network method. Cox Proportional Hazard regression models are used to estimate the survival probabilities of Malaysian PN17 and GN3 listed firms. Forecast accuracy is evaluated using receiver operating characteristics curve. From the findings, it shown that the independent directors’ ownership has negative association with the financial distress likelihood. In addition, this study modeled a mix of corporate financial distress predictors for Malaysian firms. The combination of financial and non-financial ratios which pressure-sensitive institutional ownership, independent director ownership, and Earnings Before Interest and Taxes to Total Asset shown a negative relationship with financial distress likelihood specifically one year before the firms being listed in PN 17 and GN 3 status. However, Retained Earnings to Total Asset, Interest Coverage, and Market Value of Debt have positive relationship with firm financial distress likelihood. These research findings also contribute to the policy implications to the Securities Commission and specifically to Bursa Malaysia. Furthermore, one of the initial goals in introducing the PN17 and GN3 status is to alleviate the information asymmetry between distressed firms, the regulators, and investors. Therefore, the regulator would be able to monitor effectively distressed firms, and investors can protect from imprudent investment.