Abhishek Gupta

This book examines the convergence of Islamic legal principles and modern financial systems, covering the fundamental principles of Islamic finance and banking, and how they are practically applied within the banking sector. Using real-world examples to discuss the operation of contracts, partnerships, and risk-sharing arrangements while adhering to Islamic law, the book details Sharia-compliant banking and finance both in theory and practice. With an international perspective, the book analyses Islamic Banking law in countries such as the UK, Malaysia and India, covering their respective legal framework and regulations in detail. It also delves into the history of banking law in each country, alongside topics such as taxation, corporate governance and regulatory practice. The book will be of interest to students and scholars in the field of Islamic law, banking and finance law.

En termes de progr s technologique, les DG jouent un r le crucial dans la minimisation des pertes de puissance dans le syst me de distribution afin de r pondre aux exigences de la charge. L'augmentation de la production d' lectricit a permis de r pondre la demande croissante du r seau de distribution dans les stations de chargement. L'un des moyens de r pondre la demande de charge essentielle dans le r seau de distribution est de r duire les pertes de puissance globales. En r duisant les pertes de puissance r active du syst me, la puissance r elle peut tre augment e travers le r seau. Par cons quent, en r partissant de mani re optimale les unit s de production d centralis e dans le syst me de distribution, nous pouvons minimiser les pertes de puissance.L'objectif principal de ce livre est de d terminer le meilleur emplacement possible et la taille des unit s DG afin de minimiser les pertes totales de puissance r active et de r duire ainsi les pertes de puissance r elle tout en conservant un meilleur profil de tension dans le syst me de distribution radial. Ce livre propose une m thode analytique ainsi qu'une nouvelle constante PVSF (Power Voltage Sensitivity Factor) qui permet d'identifier la taille et l'emplacement optimaux des unit s de production d centralis es.

Em termos de avan o tecnol gico, as GDs desempenham um papel crucial na minimiza o das perdas de energia no sistema de distribui o, de modo a atingir os requisitos de carga. O aumento da produ o de energia tem sido capaz de satisfazer a procura crescente do sistema de distribui o nas esta es de carga. Uma forma de satisfazer a procura de carga essencial no sistema de distribui o reduzir as perdas globais de energia. Ao reduzir as perdas de pot ncia reactiva do sistema, a pot ncia real pode ser aumentada em toda a rede. Por conseguinte, atrav s da atribui o optimizada das unidades de GD no sistema de distribui o, podemos minimizar as perdas de energia.O principal objetivo deste livro determinar a melhor localiza o poss vel e a dimens o das unidades GD para minimizar as perdas totais de pot ncia reactiva e, assim, reduzir as perdas de pot ncia real, mantendo um melhor perfil de tens o no sistema de distribui o radial. Este livro sugere um m todo anal tico e tamb m uma nova constante PVSF (Power Voltage Sensitivity Fator) que identifica a melhor dimens o e localiza o das GDs.

Jeśli chodzi o postęp technologiczny, DG odgrywają kluczową rolę w minimalizowaniu strat mocy w systemie dystrybucyjnym, aby spelnic wymagania dotyczące obciążenia. Wzrost produkcji energii jest w stanie zaspokoic rosnące zapotrzebowanie na system dystrybucji w stacjach ladowania. Jednym ze sposob w zaspokojenia podstawowego zapotrzebowania na moc w systemie dystrybucyjnym jest zmniejszenie calkowitych strat mocy. Obniżając straty mocy biernej w systemie, można zwiększyc moc rzeczywistą w calej sieci. Dlatego też, optymalnie rozmieszczając jednostki DG w systemie dystrybucyjnym, możemy zminimalizowac straty mocy.Gl wnym celem tej książki jest określenie najlepszej możliwej lokalizacji i wielkości jednostek DG w celu zminimalizowania calkowitych strat mocy biernej, a tym samym zmniejszenia rzeczywistych strat mocy przy jednoczesnym utrzymaniu lepszego profilu napięcia w promieniowym systemie dystrybucyjnym. W książce zaproponowano metodę analityczną, a także nową stalą PVSF (Power Voltage Sensitivity Factor), kt ra identyfikuje najlepszy optymalny rozmiar i lokalizację DG.

In termini di progresso tecnologico, i DG svolgono un ruolo cruciale nel ridurre al minimo le perdite di potenza nel sistema di distribuzione, in modo da raggiungere i requisiti di carico. L'aumento della produzione di energia stato in grado di soddisfare la crescente domanda del sistema di distribuzione nelle stazioni di carico. Un modo per soddisfare la domanda di carico essenziale nel sistema di distribuzione quello di ridurre le perdite di potenza complessive. Riducendo le perdite di potenza reattiva del sistema, possibile aumentare la potenza reale sulla rete. Pertanto, allocando in modo ottimale le unit DG nel sistema di distribuzione, possibile ridurre al minimo le perdite di potenza.L'obiettivo principale di questo libro quello di determinare la migliore posizione e dimensione possibile delle unit DG per minimizzare le perdite totali di potenza reattiva e quindi ridurre le perdite di potenza reale, mantenendo un migliore profilo di tensione in un sistema di distribuzione radiale. Questo libro propone un metodo analitico e una nuova costante PVSF (Power Voltage Sensitivity Factor) che identifica la dimensione e la posizione ottimale dei DG.

Im Rahmen des technologischen Fortschritts spielen die DGs eine entscheidende Rolle bei der Minimierung der Leistungsverluste im Verteilungssystem, um die Lastanforderungen zu erf llen. Eine Steigerung der Stromerzeugung ist in der Lage, den wachsenden Bedarf des Verteilungssystems an den Ladestationen zu decken. Eine M glichkeit, den wesentlichen Lastbedarf im Verteilernetz zu decken, ist die Verringerung der Gesamtleistungsverluste. Durch die Verringerung der Blindleistungsverluste des Systems kann die Wirkleistung im gesamten Netz erh ht werden. Daher k nnen wir durch eine optimale Zuweisung der DG-Einheiten im Verteilungssystem die Leistungsverluste minimieren.Das Hauptziel dieses Buches ist es, den bestm glichen Standort und die Gr e von DG-Einheiten zu bestimmen, um die Gesamtblindleistungsverluste zu minimieren und dadurch die Wirkleistungsverluste zu reduzieren, w hrend gleichzeitig ein besseres Spannungsprofil in einem radialen Verteilungssystem erhalten bleibt. In diesem Buch werden eine analytische Methode und eine neue Konstante PVSF (Power Voltage Sensitivity Factor) vorgeschlagen, mit der die optimale Gr e und der beste Standort von DGs ermittelt werden k nnen.

In terms of technological advancement, DGs play a crucial role in minimizing power losses in the distribution system so as to achieve load requirements. An increase in power production has been capable of meeting growing demands for the distribution system at the loading stations. One way to meet the essential load demand in distribution system is to reduce overall power losses. By lowering the reactive power losses of the system, real power can be increased across the network. Therefore, by optimally allocating the DG units in distribution system we can minimize the power losses. The main aim of this book is to determine the best possible location and size of DG units to minimize the total reactive power losses and thereby reducing real power losses while keeping a better voltage profile in radial distribution system. This book suggested an analytical method and also a new constant PVSF (Power Voltage Sensitivity Factor) that identify the best optimally size and location of DGs.

A remarkable facet of the human brain is its ability to manage multiple tasks with apparent simultaneity. Knowledge learned from one task can then be used to enhance problem-solving in other related tasks. In machine learning, the idea of leveraging relevant information across related tasks as inductive biases to enhance learning performance has attracted significant interest. In contrast, attempts to emulate the human brain’s ability to generalize in optimization – particularly in population-based evolutionary algorithms – have received little attention to date. Recently, a novel evolutionary search paradigm, Evolutionary Multi-Task (EMT) optimization, has been proposed in the realm of evolutionary computation. In contrast to traditional evolutionary searches, which solve a single task in a single run, evolutionary multi-tasking algorithm conducts searches concurrently on multiple search spaces corresponding to different tasks or optimization problems,each possessing a unique function landscape. By exploiting the latent synergies among distinct problems, the superior search performance of EMT optimization in terms of solution quality and convergence speed has been demonstrated in a variety of continuous, discrete, and hybrid (mixture of continuous and discrete) tasks. This book discusses the foundations and methodologies of developing evolutionary multi-tasking algorithms for complex optimization, including in domains characterized by factors such as multiple objectives of interest, high-dimensional search spaces and NP-hardness.

Electricity is a key energy source today, with rising household use of heavy loads like ACs and washing machines. Unlike industrial loads, which are balanced and follow fixed patterns, household loads are increasingly non-linear due to electronic devices and inverter technology. This leads to harmonic disturbances in the power system. The proposed system aims to implement a Shunt Active Power Filter using the PI technique to mitigate harmonics and noise from non-linear, unbalanced, and mixed loads.

It also discusses the regulators approach to curb financial crimes and how syndication among financial institutions can create a robust ecosystem for monitoring and managing financial crimes. It opens with an introduction to financial crimes for a financial institution, the context of financial crimes, and its various participants.

This book discusses all aspects of money laundering, starting from traditional approach to financial crimes to artificial intelligence-enabled solutions. It also discusses the regulators approach to curb financial crimes and how syndication among financial institutions can create a robust ecosystem for monitoring and managing financial crimes. It opens with an introduction to financial crimes for a financial institution, the context of financial crimes, and its various participants. Various types of money laundering, terrorist financing, and dealing with watch list entities are also part of the discussion. Through its twelve chapters, the book provides an overview of ways in which financial institutions deal with financial crimes; various IT solutions for monitoring and managing financial crimes; data organization and governance in the financial crimes context; machine learning and artificial intelligence (AI) in financial crimes; customer-level transaction monitoring system; machine learning-driven alert optimization; AML investigation; bias and ethical pitfalls in machine learning; and enterprise-level AI-driven Financial Crime Investigation (FCI) unit. There is also an Appendix which contains a detailed review of various data sciences approaches that are popular among practitioners.The book discusses each topic through real-life experiences. It also leverages the experience of Chief Compliance Officers of some large organizations to showcase real challenges that heads of large organizations face while dealing with this sensitive topic. It thus delivers a hands-on guide for setting up, managing, and transforming into a best-in-class financial crimes management unit. It is thus an invaluable resource for researchers, students, corporates, and industry watchers alike.

A remarkable facet of the human brain is its ability to manage multiple tasks with apparent simultaneity. Knowledge learned from one task can then be used to enhance problem-solving in other related tasks. In machine learning, the idea of leveraging relevant information across related tasks as inductive biases to enhance learning performance has attracted significant interest. In contrast, attempts to emulate the human brain’s ability to generalize in optimization – particularly in population-based evolutionary algorithms – have received little attention to date. Recently, a novel evolutionary search paradigm, Evolutionary Multi-Task (EMT) optimization, has been proposed in the realm of evolutionary computation. In contrast to traditional evolutionary searches, which solve a single task in a single run, evolutionary multi-tasking algorithm conducts searches concurrently on multiple search spaces corresponding to different tasks or optimization problems,each possessing a unique function landscape. By exploiting the latent synergies among distinct problems, the superior search performance of EMT optimization in terms of solution quality and convergence speed has been demonstrated in a variety of continuous, discrete, and hybrid (mixture of continuous and discrete) tasks. This book discusses the foundations and methodologies of developing evolutionary multi-tasking algorithms for complex optimization, including in domains characterized by factors such as multiple objectives of interest, high-dimensional search spaces and NP-hardness.