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With the constant advancement of the smart grid, zero-day attack processes in Advanced Metering Infrastructure (AMI) and Supervisory Control and Data Acquisition (SCADA) networks are also continually evolving. This study...

Abstract Federated Learning (FL) has been widely used in Internet of Things (IoT) environments as a promising decentralized framework capable of collaborative model training without exposing local data. Despite its advan...

Abstract Cloud computing is quite popular because of its scalability and flexibility merits. However, faces significant security risks from malware, which exploits infrastructure weaknesses to cause unauthorized access, ...

The identification of exoplanets within habitable zones remains a central objective in modern astrophysics, particularly with the availability of large-scale photometric datasets from space-based missions such as the Tra...

This study aims to examine the influence of family factors on the learning independence of students at Tiara School Elementary School Jakarta. Family factors analyzed include parental support and attention, grade level, ...

Abstract Multimodal industrial documents–such as operation manuals, circuit diagrams, and parameter tables–contain domain knowledge distributed across text, images, and document layout. However, most existing retriev...

he orchestration of microservices in distributed cloud environments poses significant challenges due to the heterogeneous nature of cluster nodes and dynamic workload patterns. Traditional scheduling strategies in Kubern...

Effective leadership is vital for the high-quality early childhood education and care (ECEC) that positively impacts children’s development. Despite the recognised importance of leadership, there is limited understandi...

Attacks on network components and devices pose a significant threat to service continuity, necessitating robust detection mechanisms. This paper presents a Distributed Denial of Service (DDoS) attack detection framework ...

Abstract With the rapid adoption of multi-cloud platforms, dynamic orchestration of service function chains faces coupled challenges. This study proposes a hierarchical service chain orchestration for multi-cloud environ...

Abstract In rural areas, unreasonable access of distributed photovoltaic (DPV) may pose a significant challenge to the safe operation of the power network. To address this, determining the maximum hosting capacity of net...

Federated Learning (FL) has emerged as a privacy-preserving distributed learning paradigm that enables collaborative model training without sharing raw data. Despite its advantages, ensuring trustworthy FL deployment rem...

Inborn errors of immunity (IEI) are increasing in number, and prompt recognition and diagnosis remain a challenge for clinicians. Use of machine learning (ML) for clinical pattern recognition is promising but has been li...

Abstract Nanofluids have emerged as promising heat transfer media due to their superior thermal performance associated to conventional fluids, yet their behavior under mutual impacts of radiation, heat source/sink, and m...

Even with the introduction of additional security features, the progression toward 6G and Open Radio Access Network (O-RAN) architectures expands security risks, increasing both the scale and complexity of mobile network...

Digital health increasingly relies on artificial intelligence for clinical decision-making, patient management, and distributed learning, yet two persistent challenges remain: the computational complexity of optimization...

Heart disease is rapidly increasing. For early and accurate prediction, advanced machine learning (ML) models are needed. However, the sensitive nature of clinical data, along with strict regulatory constraints, creates ...

IntroductionA research gap exists regarding the association between non-optimal ambient temperature (NOAT) and early childhood development (ECD) in low- and middle-income countries (LMICs). This study investigates the as...

This research describes a deep learning-based artificial neural network (ANN) approach for the detection, classification, and localization of series faults (open conductor faults) in power distribution networks. The ANN ...

The power system event detection process must accelerate and become more precise with increasing penetration of renewable energy systems into the grid. The authors discuss a federated learning LSTM (FL-LSTM) that serves ...

In response to issues in regional landslide risk evaluation (LRE), such as the over-reliance on administrative unit statistics for vulnerability characterization and the difficulty in capturing the fine-scale spatial het...

Abstract Accurate tumor targeting is vital in prostate cancer (PCa) radiotherapy for precise dose delivery and minimizing healthy tissue exposure. Currently, no artificial intelligence (AI) tool exists to predict setup d...

Mining activities in the Kenyan Marble Quarries (KMQ) are a potential source of atmospheric pollution, raising health concerns for the local population. This study aims to examine the extent to which marble mining contri...

Abstract High-density, long-term stable decoding of whole-brain function is crucial for advancing basic neuroscience research and developing neural disorder therapies. However, two major challenges remain: the lack of sc...