reinforcement learning

Edukasi Anti-Bullying melalui Program "Detektif Teman Baik" untuk Membangun Pertemanan Positif Siswa SDN 006 Sambutan

Peer conflict and bullying behavior, manifested in verbal mocking and physical aggression, present significant challenges in elementary education environments, including at SDN 006 Sambutan. This study aimed to examine the implementation and effectiveness of the "Detektif Teman Baik" anti-bullying education program in...

Automatic Generation of Deep Learning Models Based on Heterogeneous Pre-Trained Model Stitching

Findings support the feasibility of MPMS-AG for automatic generation of customized deep learning models from heterogeneous pre-trained model libraries within the evaluated setting.

The Role of Parents in Developing Phonological Awareness in 4–5-Year-Old Children: A Case Study at Cahaya Hati Kindergarten

Phonological awareness is a fundamental skill that supports early literacy development in young children. This study aimed to: (1) analyze the role of parents in developing children's phonological awareness at home; (2) identify the factors that support parents' involvement in fostering children's phonological awarenes...

Constraint-guided multi-agent deep reinforcement learning for multi-microgrid energy management with mobile electric vehicles

Quantum Cryptography and AI Integration: Quantum-Resistant Defenses for Future Communication Systems Against Emerging Cyber Threats

Quantum cryptography, like QKD, leverages quantum mechanics for unbreakable encryption against quantum computers, but faces deployment hurdles in key management, scalability, and noise. AI integration revolutionizes this by optimizing protocols, minimizing errors, and enabling real-time monitoring. Deep and reinforceme...

A Study of Myopic, Predictive, and Reinforcement Learning Energy Management Strategies for Isolated Microgrids

The increasing penetration of renewable energy sources in isolated microgrids has intensified the need for Energy Management Systems (EMS) capable of reducing diesel dependence while ensuring reliable operation. This study compares three EMS strategies for a photovoltaic–diesel–battery microgrid representative of remot...

Urban electric vehicle fast charging load forecasting: an LGRL approach

Test results show that the proposed hybrid forecasting method outperforms traditional algorithms in forecasting accuracy, convergence speed, and robustness under extreme conditions such as data missing, and it can effectively quantify the impact of load fluctuations on the voltage of distribution networks.

Well-log depth alignment: a critical review and field-based comparison of classical and machine-learning methods

Abstract Accurate well-log depth matching is important because even small depth errors can affect fluid-contact interpretation, net-pay estimates, well-to-well correlation, and reservoir modelling. In practice, electric wireline logging (EWL) and logging-while-drilling (LWD) logs often differ in depth because of cable...

Graph neural network-based tail-risk pricing for cyber insurance against cyber-physical attacks in power systems

Abstract Cyber insurance transfers the residual cyber risk that remains after technical controls are installed, yet conventional pricing models rarely condition losses on grid topology, operating state, communication dependencies, and physical consequences. We develop a graph neural network (GNN) framework for pricing...

IoT-ML for Smart City Traffic Management and Dynamic Routing

Urban areas face severe traffic congestion, pollution, and economic losses from rising populations and vehicle density. Traditional fixed-timing controls fail under dynamic conditions. IoT-ML integration enables smart city dynamic routing. IoT sensors, GPS, and connected vehicles provide real-time traffic data. ML tech...

Choice-selective sequences dominate in cortical relative to thalamic inputs to NAc to support reinforcement learning

Knowledge graph-enhanced pre-trained language model for organizational resilience assessment and dynamic capability reconstruction path mining

Abstract Organizational resilience now shapes which firms survive prolonged uncertainty, yet most assessment instruments remain fragmented across indicators and keep structured domain knowledge apart from semantic understanding. This study develops a domain-specific framework in which knowledge graph reasoning and pre-...