As renewable energy penetration continues to grow, grid-connected inverters are increasingly required to operate reliably under weak-grid conditions, where low short-circuit ratios, changing grid impedances, and rapid disturbances reveal the limitations of conventional fixed-gain PI current controllers. Reinforcement l...
Jabala Nur Fahima, Kayes Hasan, Md. Rifat Hazari et al.· Electric Power Systems Resea...· 0 citations
The vast expansion of Internet of Things (IoT) ecosystems has posed significant challenges regarding security, scalability, latency, and user privacy, which are not properly handled by the conventional architectures. To solve these issues, the authors of this paper suggest an integrated IoT management framework that em...
Thirusubramanian Ganesan, Mohanarangan Veerapperumal Devarajan, Akhil Raj Gaius Yallamelli et al.· Communications in Statistics...· 0 citations
Learning from Snapshots Is Not Enough: An Even-Driven Continuous-Time Reinforcement Learning Framework Revenue management systems evolve continuously, but reinforcement learning often requires dividing time into a fixed grid. Fine grids improve accuracy but increase computation; coarse grids can sacrifice performance....
This study systematically investigates the turbulence characteristics and drag-reduction mechanisms of steady wall-normal blowing control on a three-dimensional square cylinder at Re = 22000 using a large-eddy simulation (LES) with the Smagorinsky subgrid-scale model. Four jet positions at the cylinder corners—the wind...
Xin Guan, Liang Zhong, Jinyang Liu et al.· Applied Ocean Research· 0 citations
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The real-time simulation of highly deformable slender structures interacting with complex, irregular boundaries remains a computationally demanding challenge in computational mechanics. A prominent motivating application for this fundamental problem is the navigation of continuum surgical robots within narrow anatomica...
H. S. Chen, Jian Chen, Shuai Wang et al.· Computer Methods in Applied...· 0 citations
Malaysia's low ranking in TIMSS and PISA exposes students' weaknesses in mastering Higher Order Thinking Skills (KBAT) due to a curriculum that overemphasizes rote learning. This scenario contributes to disciplinary issues and moral conflicts among Tamil Vernacular Primary School (SJKT) students because of their inabil...
Suresh Kumar Manikam, Nadarajan Thambu Ph.D, Susan Fitriasari· Muallim Journal of Social Sc...· 0 citations
The interest in Machine Learning (ML) has spread to safety systems due to its ability to solve tasks that cannot be explicitly programmed, including pattern recognition, object detection, and autonomous control. To ensure the safe integration of ML in avionics, the European Union Aviation Safety Agency (EASA) proposed...
Ángel-Grover Pérez-Muñoz, Hernán García-Quijano, G. López-García et al.· Machine Learning with Applic...· 0 citations
Security in Wireless Sensor Network-based Internet of Things (WSN-IoT) systems is becoming increasingly important in the face of many cyber-attacks. This paper presents a smart framework, Swin-Yoked Neural Approach to Predictive Security (SYNAPSE) with a Parrot-CatchFish Integrated Q-Learning (PaCFIQ) optimizer to addr...
Nithya R, K. Vinoth Kumar· Journal of the Chinese Insti...· 0 citations
Trajectory planning for Unmanned Aerial Vehicles (UAVs) in complex three-dimensional (3D) environments is a critical challenge in UAV-assisted task planning systems, particularly in dynamic scenarios such as rescue operations where UAVs serve as mobile wireless communication hubs. This paper addresses this challenge by...
In this opening chapter, we set the stage for the book by describing both the opportunities and risks that artificial intelligence (AI) presents as it becomes increasingly embedded in critical domains such as healthcare, education, transportation, energy, conservation, and security. We argue that researchers and practi...
Ayan Mukhopadhyay, Yevgeniy Vorobeychik· River Publishers eBooks· 0 citations
As renewable energy sources and electric vehicles proliferate, managing energy efficiently under uncertainty has become critical. This chapter focuses on optimization challenges in electric vehicle (EV) charging and vehicle-tobuilding (V2B) integration, formalizing them as sequential decision-making problems under unce...
Fangqi Liu, Rishav Sen, Abhishek Dubey et al.· River Publishers eBooks· 0 citations
In the Quantum Approximate Optimization Algorithm (QAOA), the entanglement topology, where qubit pairs are connected by two-qubit gates, is conventionally set equal to the edge set of the problem graph. This coupling ties circuit design to explicit problem knowledge and may not yield the most trainable circuit under li...
Tobias Rohe, Federico Harjes Ruiloba, Markus Baumann et al.· Frontiers in Quantum Science...· 0 citations
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.