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Influence Diagrams in Cyber Security: Conceptualization and Potential Applications
Get PDFOver the last years, cyber-attacks are increasing in organizations especially due to the use of emerging technologies and transformation in terms of how we work. Informed decision-making in cyber security is critical to prevent, detect, respond, and recover from cyber-attacks effectively and efficiently. In cyber security, Decision Support System (DSS) plays a crucial role especially in supporting security analysts, managers, and operators in making informed decisions. Artificial Intelligence (AI)-based techniques like Bayesian Networks, Decision Trees are used as an underlying approach in such DSSs. Furthermore, Influence Diagrams (IDs) possess the capability to support informed decision-making based on its existing applications in other domains like medical. However, the complete capability and potential of IDs are not utilised in cyber security especially in terms of its explainable nature for different stakeholders and existing applications in other domains. Therefore, this research tackles the following research question: “What are potential applications of Influence Diagrams (IDs) in cyber security?”. We identified applications of IDs in different domains and then translated it to design potential applications for cyber security issues. In the future, this will help both researchers and practitioners to develop and implement IDs for cyber security-related problems, which in turn will enhance decision-making especially due to its explainable nature for different stakeholders.publishedVersio
Study of the magnetostructural transition in critical-element free Mn1−xNi1−xFe2xSi0.95Al0.05
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MRDPGA: a multiple restart dynamic population genetic algorithm for scheduling road traffic
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Optical interference coatings for coloured building integrated photovoltaic modules: Predicting and optimising visual properties and efficiency
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Smart energy approaches for carbon abatement: Scenario designs for Chile's energy transition
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Profitability of battery storage in hybrid hydropower–solar photovoltaic plants
Get PDFIncreased energy demand and rapid environmental changes triggered by global greenhouse gas emissions have forced numerous countries to consider renewable energy sources (RES) as possible alternatives to conventional fossil-fuel energy sources. Due to the inherent uncertainty, intermittency, and generally uncontrollable power generation by single-source renewable power plants, hybrid power plants (HPPs) incorporating several mutually complementary RES have lately gained much interest. Integrating battery storage systems with such HPPs has the potential to run them more similarly to conventional fossil-fueled power plants, providing controllable power generation, and reducing its variability. Given such a future scenario and the lack of existing detailed studies, this paper investigates the profitability potential for a viable business case for battery storage integration with utility-scale hybrid hydropower–solar photovoltaic (PV) plants. The study presented here is based on a hypothetical, two-reservoir cascaded hydropower plant in Sub-Saharan Africa. The role of the battery is assessed by considering the overall profitability of the HPP when participating in capacity markets, ancillary services, and energy arbitrage. The relationship between the value stacking of battery services and its impact on battery life has been critically examined. This study provides estimates on increased profitability, cost-optimal battery capacities, battery degradation estimates, and the HPP-battery interoperability aspects under various hydropower and electricity market operating scenarios. Batteries will likely increase cost-effectiveness by co-optimization with PV-system as well as power market contracts. In this case, adding a battery increased the profitability by about 2% when combining revenues from capacity markets and ancillary services.Profitability of battery storage in hybrid hydropower–solar photovoltaic plantspublishedVersio
Security Aspects of Social Robots in Public Spaces: A Systematic Mapping Study
Get PDFBackground: As social robots increasingly integrate into public spaces, comprehending their security implications becomes paramount. This study is conducted amidst the growing use of social robots in public spaces (SRPS), emphasising the necessity for tailored security standards for these unique robotic systems. Methods: In this systematic mapping study (SMS), we meticulously review and analyse existing literature from the Web of Science database, following guidelines by Petersen et al. We employ a structured approach to categorise and synthesise literature on SRPS security aspects, including physical safety, data privacy, cybersecurity, and legal/ethical considerations. Results: Our analysis reveals a significant gap in existing safety standards, originally designed for industrial robots, that need to be revised for SRPS. We propose a thematic framework consolidating essential security guidelines for SRPS, substantiated by evidence from a considerable percentage of the primary studies analysed. Conclusions: The study underscores the urgent need for comprehensive, bespoke security standards and frameworks for SRPS. These standards ensure that SRPS operate securely and ethically, respecting individual rights and public safety, while fostering seamless integration into diverse human-centric environments. This work is poised to enhance public trust and acceptance of these robots, offering significant value to developers, policymakers, and the general public.Security Aspects of Social Robots in Public Spaces: A Systematic Mapping StudypublishedVersio
Probabilistic Planning of Distribution Networks with Optimal DG Placement Under Uncertainties
Get PDFThis research paper presents an efficient methodology for distribution network planning under an uncertain environment. As an extension of our previous work presented at the ECCE Asia 2021 conference, here optimal placement and sizing of Renewable Energy Sources (RES)-based Distributed Generations (DGs) are determined considering the generation and load uncertainties. In addition, the optimal tap settings of off-load tap changing transformers present in a network are also determined. Probabilistic non-linear optimization is solved with a sensitivity-based technique to minimize the distribution network losses and improve its voltage stability. The proposed methodology is implemented on standard test systems like the IEEE 69 bus and the Indian 85 bus networks. Further, to determine its real-world functionality, the methodology is tested on a practical radial distribution network of 88 buses present in a remote Froan island of Norway. When compared with existing techniques, the proposed methodology provides much more efficient network planning solutions with lesser power losses. Developed on free and open-source software platforms, it also provides a reliable and cost-effective alternative to network operators to determine their network robustness.Probabilistic Planning of Distribution Networks with Optimal DG Placement Under UncertaintiesacceptedVersio