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- PublicationEfficient Voltage Regulation: An RW-ARO Optimized Cascaded Controller Approach(2024)This work introduces novel advancements in automatic voltage regulator (AVR) control, addressing key challenges and delivering innovative contributions. The primary motivation lies in enhancing AVR performance to ensure stable and reliable voltage output. A crucial innovation in this work is the introduction of the random walk aided artificial rabbits optimizer (RW-ARO). This novel optimization strategy incorporates a random walk approach, enhancing the efficiency of AVR control schemes. The proposed cascaded RPIDD2-PI controller, fine-tuned using the RW-ARO, stands out as a pioneering approach in the AVR domain. It demonstrates superior stability, faster response times, enhanced robustness, and improved efficiency compared to existing methods. Comparative analyses with established controller approaches reaffirm the exceptional performance of the proposed method. The new approach results in shorter rise times, quicker settling times, and minimal overshoot, highlighting its effectiveness and speed in achieving desired system responses. Moreover, the novel approach attains higher phase and gain margins, showcasing its superior performance in the frequency domain. The disturbance rejection and harmonic analysis are performed in order to demonstrate the efficacy of the proposed approach for potential real-world applications. The latter analyses further cement the superior capability of the proposed approach for the automatic voltage regulation.
7 1 - PublicationGIJA:Enhanced geyser‐inspired Jaya algorithm for task scheduling optimization in cloud computing(2024)Task scheduling optimization plays a pivotal role in enhancing the efficiency and performance of cloud computing systems. In this article, we introduce GIJA (Geyser‐inspired Jaya Algorithm), a novel optimization approach tailored for task scheduling in cloud computing environments. GIJA integrates the principles of the Geyser‐inspired algorithm with the Jaya algorithm, augmented by a Levy Flight mechanism, to address the complexities of task scheduling optimization. The motivation for this research stems from the increasing demand for efficient resource utilization and task management in cloud computing, driven by the proliferation of Internet of Things (IoT) devices and the growing reliance on cloud‐based services. Traditional task scheduling algorithms often face challenges in handling dynamic workloads, heterogeneous resources, and varying performance objectives, necessitating innovative optimization techniques. GIJA leverages the eruptive dynamics of geysers, inspired by nature's efficiency in channeling resources, to guide task scheduling decisions. By combining this Geyser‐inspired approach with the simplicity and effectiveness of the Jaya algorithm, GIJA offers a robust optimization framework capable of adapting to diverse cloud computing environments. Additionally, the integration of the Levy Flight mechanism introduces stochasticity into the optimization process, enabling the exploration of solution spaces and accelerating convergence. To evaluate the efficacy of GIJA, extensive experiments are conducted using synthetic and real‐world datasets representative of cloud computing workloads. Comparative analyses against existing task scheduling algorithms, including AOA, RSA, DMOA, PDOA, LPO, SCO, GIA, and GIAA, demonstrate the superior performance of GIJA in terms of solution quality, convergence rate, diversity, and robustness. The findings of GIJA provide a promising solution quality for addressing the complexities of task scheduling in cloud environments (95%), with implications for enhancing system performance, scalability, and resource utilization.
6 - PublicationDeploying model obfuscation: towards the privacy of decision-making models on shared platforms(2024)The automation of the industrial paradigms characterizes the era of Industry 4.0. The implementation nuances involve data and model sharing among allies and partners working on the same domain. Privacy and security of data and models are fundamental necessities that must be satisfied for this protocol's proper functioning. To this end, we propose a conceptual and algorithmic framework of a model obfuscation scheme. It is built upon the extant data obfuscation paradigm. The future work lies with the implementation and establishment of its viability. This research is expected to develop into deployable model obfuscation technique which practitioners from the industrial domain can adopt.
1 3 - PublicationKnowing the class distinguishing abilities of the features, to build better decision-making models(2024)Explainability allows end-users to have a transparent and humane reckoning of an ML scheme's capability and utility. ML model's modus opernadi can be explained via the features which trained it. To this end, we found no work explaining the features' importance based on their class-distinguishing abilities. In a given dataset, a feature is not equally good at distinguishing between the data points' possible categorizations (or classes). This work explains the features based on their class or category-distinguishing capabilities. We estimate the variables' class-distinguishing capabilities (scores) for pair-wise class combinations, utilize them in a missing feature context, and propose a novel decision-making protocol. A key novelty of this work lies in the refusal to render a decision option when the missing feature (of the test point) has a high class-distinguishing potential for the likely classes. Two real-world datasets are used empirically to validate the explainability of our scheme.
9 1 - PublicationWhen geoscience meets generative AI and large language models: Foundations, trends, and future challenges(2024)Generative Artificial Intelligence (GAI) represents an emerging field that promises the creation of synthetic data and outputs in different modalities. GAI has recently shown impressive results across a large spectrum of applications ranging from biology, medicine, education, legislation, computer science, and finance. As one strives for enhanced safety, efficiency, and sustainability, generative AI indeed emerges as a key differentiator and promises a paradigm shift in the field. This article explores the potential applications of generative AI and large language models in geoscience. The recent developments in the field of machine learning and deep learning have enabled the generative model's utility for tackling diverse prediction problems, simulation, and multi‐criteria decision‐making challenges related to geoscience and Earth system dynamics. This survey discusses several GAI models that have been used in geoscience comprising generative adversarial networks (GANs), physics‐informed neural networks (PINNs), and generative pre‐trained transformer (GPT)‐based structures. These tools have helped the geoscience community in several applications, including (but not limited to) data generation/augmentation, super‐resolution, panchromatic sharpening, haze removal, restoration, and land surface changing. Some challenges still remain, such as ensuring physical interpretation, nefarious use cases, and trustworthiness. Beyond that, GAI models show promises to the geoscience community, especially with the support to climate change, urban science, atmospheric science, marine science, and planetary science through their extraordinary ability to data‐driven modelling and uncertainty quantification.
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1138 - PublicationThe Late Holocene evolution of the Black Sea – a critical view on the so-called Phanagorian regression(2012)Throughout its geologic history, the Black Sea experienced major sea level changes accompanied by severe environmental modifications, including geomorphologic reshaping. The most spectacular changes were driven by the Quaternary glaciations and deglaciations that reflect responses to Milankovitch cycles of 100 and 20 ky periodicity. Major sea level changes were also considered for a shorter and more recent cyclicity. The concept of the Phanagorian re- and transgression cycle, supposedly with a minimum sea level stand of 5-6 m below its present position in the middle of the 1 st millennium BC, was established in 1963 by Fedorov for the Black Sea region. It was based on archaeological and palaeogeographical research conducted around the ancient Greek colonies of the Cimmerian Bosporus, in particular at the name giving site of Phanagoria, where underwater prospection had revealed the presence of a large number of submerged relics of the Classical Greek era. Analyses of sediment cores as well as 14C-dated fossil coastal bars in the western and southern parts of Taman Peninsula show that contemporary coastal bars are related to different sea levels. The dissymmetry can reach up to 6 m around 500 BC. This and more evidence from drill cores confirms that on Taman Peninsula many of the apparent sea level changes are tectonically induced. The subsidence may have been initiated by the release of gas from mud volcanoes inherited along anticline axes. Other observations around the Black Sea confirm that submerged archaeological sites correspond to areas where subsidence has taken places, while the so-called Holocene highstand - said to have been located above the present-day sea level - is associated with uplift areas (triggered by the ongoing Caucasus orogeny). Recent oceanographic research carried out in the Black Sea area shows that since the Black Sea was reconnected with the Mediterranean Sea (i.e., 7500 14C BP at the latest), both marine water bodies have been in equilibrium. This fact and arguments from archaeology, history, hydrodynamics etc. lead us to question the existence of the Phanagorian regression. It is important to note that none of the sea level curves established for the (eastern) Mediterranean shows a comparable regression/transgression cycle of several metres during the 1 st millennium BC.
Scopus© Citations 41 1058 76 - PublicationNon-linear relationship between real commodity price volatility and real effective exchange rate: The case of commodity-exporting countries(2019)The aim of this paper is to contribute to the existing literature by exploring the relationship between the real commodity price volatilities and the real effective exchange rate (REER) of commodity-exporting countries, taking into account the transition variable of financial market integration. To this end, we consider a sample of 42 commodity-exporting countries subdivided into 4 panels: food and beverages, energy, metals, and raw materials. Our results highlight that the relationship between real commodity price volatility and REER is non-linear and depends on the degree of financialization of the commodity market. Specifically, when a country is poorly integrated financially, the volatility of the real commodity price has a strong and negative impact on the variation in REER. However, for periods when a country is better integrated financially, we observe a decrease in the impact of real commodity price volatility on REER, especially for the two panels of food and beverages as well as energy. Our findings also highlight the growth of financialization of commodities post-2000, particularly in the case of the energy sector.
Scopus© Citations 25 855 - PublicationCoral Reefs of Abu Dhabi, United Arab Emirates: Analysis of Management Approaches in Light of International Best Practices and a Changing Climate(2020)The coasts and islands that flank Abu Dhabi, the United Arab Emirates (UAE)’s largest emirate, host the country’s most significant coastal and marine habitats including coral reefs. These reefs, although subject to a variety of pressures from urban and industrial encroachment and climate change, exhibit the highest thresholds for coral bleaching and mortality in the world. By reviewing and benchmarking global, regional and local coral reef conservation efforts, this study highlights the ecological importance and economic uniqueness of the UAE corals in light of the changing climate. The analysis provides a set of recommendations for coral reef management that includes an adapted institutional framework bringing together stakeholders, scientists, and managers. These recommendations are provided to guide coral reef conservation efforts regionally and in jurisdictions with comparable environmental challenges.
Scopus© Citations 7 804 88 - PublicationThe globalization of social sciences? Evidence from a quantitative analysis of 30 years of production, collaboration and citations in the social sciences (1980-2009)(SAGE Publications Ltd, 2014)This article addresses the issue of internationalization of social sciences by studying the evolution of production (of academic articles), collaboration and citations patterns among main world regions over the period 1980-2009 using the SSCI. The results confirm the centre-periphery model and indicate that the centrality of the two major regions that are North America and Europe is largely unchallenged, Europe having become more important and despite the growing development of Asian social sciences. The authors' quantitative approach shows that the growing production in the social sciences but also the rise of international collaborations between regions have not led to a more homogeneous circulation of the knowledge produced by different regions, or to a substantial increase in the visibility of the contributions produced by peripheral regions. Social scientists from peripheral regions, while producing more papers in the core journals compiled by the SSCI, have a stronger tendency to cite journals from the two central regions, thus losing at least partially their more locally embedded references, and to collaborate more with western social scientists. In other words, the dynamic of internationalization of social science research may also lead to a phagocytosis of the periphery into the two major centers, which brings with it the danger of losing interest in the local objects specific to those peripheral regions. © The Author(s) 2013.
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