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IEEE Open Journal of the Computer Society
Scopus
ISSN 2644-1268 · IEEE · 447 artikel di indeks
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Artikel Jurnal
AG-CLIP: Attribute-Guided CLIP for Zero-Shot Fine-Grained Recognition
Zero-shot fine-grained recognition is challenging due to high visual similarities between classes and the inferior encoding of fine-grained features in embedding models. In this work, we present an attribute-guided Contrastive Language-Image Pre-training (AG-CLIP) model with an additional attribute…
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EMO-CARE: EEG Multi-Scale Temporal Modeling With Channel-Aware Feature Attention for Robust Subject-Independent Emotion Recognition
Electroencephalography (EEG)-based emotion recognition holds promise for real-time mental health monitoring, adaptive interfaces, and affective computing. However, accurate prediction across individuals remains challenging due to inter-subject variability and the non-stationary nature of EEG…
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MM-3DAttNet: Multi-Modal 3D Attention Network for MGMT Methylation Prediction
The methylation status of the $O^{6}$-methylguanine-DNA methyltransferase (MGMT) promoter is an established prognostic and predictive biomarker in glioma, particularly for estimating response to alkylating chemotherapy such as temozolomide. However, many existing radiogenomic methods remain…
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Redefining Elderly Care With Agentic AI: Challenges and Opportunities
The global ageing population necessitates new and emerging strategies for caring for older adults. In this article, we explore the potential for transformation in elderly care through Agentic Artificial Intelligence (AI), powered by Large Language Models (LLMs). We discuss how Agentic AI…
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Towards Secure Air Traffic Surveillance: A Survey on ADS-B Threats, Existing Solutions, and Future Research
Automatic Dependent Surveillance-Broadcast (ADS-B) has transformed air traffic surveillance systems by improving flight efficiency, reducing operational costs, and enhancing situational awareness. Despite the protocol's advantages, its unencrypted and open nature makes it vulnerable to significant…
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Machine Learning for Parkinson’s Disease Detection: Analyzing Hybrid Voice Data With Spectral, Topological, and Random Matrix Methods
Parkinson’s disease (PD) is a progressive neurodegenerative disorder that affects both motor and speech functions. Advances in machine learning and signal processing have enabled non-invasive PD detection through voice analysis. This study proposes a comprehensive mathematical framework for PD…
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On the Fuzzy Entropy and the Rankability of Data
Rankability measures how strongly a dataset supports a unique and stable ordering, complementing ranking algorithms that always output an order even when the data are ambiguous. We propose EnRank, a lightweight rankability score for pairwise-comparison data that combines (i) entrywise fuzzy entropy…
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Advancing Autism Spectrum Disorder Diagnosis With Multimodal Data: A Survey
Autism Spectrum Disorder (ASD) is a complicated neurodevelopmental condition characterised by a variety of behavioural and communication challenges, marking timely and accurate diagnosis and intervention essential. Despite their widespread occurrence, conventional diagnostic methods like clinical…
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Reinforcing CBDC Integrity: A Novel Anti Money Laundering Solution by Integrating Blockchain, Machine Learning, and Taint Analysis
As the central bank digital currency (CBDC) is rapidly becoming operational, there are both opportunities for financial inclusion and efficiency, as well as problems of security threats and anti-money laundering (AML), particularly due to concerns about user anonymity. In order to address the risks…
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Human-in-the-Loop Feature Selection Using Interpretable Kolmogorov-Arnold Network-Based Double Deep Q-Network
Feature selection is critical for improving the performance and interpretability of machine learning models, particularly in high-dimensional spaces where complex feature interactions can reduce accuracy and increase computational demands. Existing approaches often rely on static feature subsets or…
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Validating AI-Driven Nudge Recommendations: A/B Testing Two-Tower and Bandit Models in Simulated Digital Banking Environment
While radical moves towards personalization characterize increasingly ambitious digital banking campaigns, recommender systems are typically based on either collaborative filtering or content-based filtering, and they often prove ineffective due to a lack of behavioral awareness, as well as issues…
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zk-REAL: A Zero-Knowledge-Based Protocol for Repeated Image Edit Authenticity Proof With Lattice Hashing
The rapid advancement of deepfake technology poses risks, including financial fraud and political misinformation, demanding robust methods for verifying image content authenticity. While C2PA and ZK-based methods provide mechanisms for authenticity, existing solutions struggle to efficiently…
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ECommVis: Supporting E-Commerce Marketplace Advertising Outcomes Through a Visual Analytics System
E-commerce marketplace platforms rely increasingly on digital advertising to drive merchant sales, yet existing analytics tools often fail to provide contextual insights that connect advertising performance with actionable business strategies. This paper introduces ECommVis, a visual analytics…
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Risk Model for Choosing Signature Thresholds for Software Updates
The timely installation of software updates has become an accepted best practice for protecting connected systems from persistent threats. Modern software update frameworks and trust anchor management protocols allow for the use of multiple digital signatures on update messages to protect against…
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Integrating AI and Large Language Models for Automated Data Quality Enhancement in Data Integration Systems
This article introduces an AI and LLM-based framework to automate data quality improvement in complex data systems. Traditional methods struggle with semantic inconsistencies and evolving schemas, degrading quality as data scales. The framework incorporates Real-Time Semantic Annotation (RTSA)…
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A Vision-Based Framework for Safe Landing Zone Mapping of UAVs in Dynamic Environments
Identification safe landing zones (SLZ) for Uncrewed Aerial Vehicles (UAVs) is important to ensure reliable and safe navigation, especially when they are operated in complex and safety-critical environments. However, this is a challenging task due to obstacles and UAV motion. This paper proposes a…
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MCP-Secure: A Runtime Access Control Layer for Privilege-Aware LLM Agent Tooling
Tool-enabled language-model agents introduce new security risks because their behavior evolves over multi-step workflows, yet existing defenses primarily rely on static allowlists or infrastructure isolation. This article presents MCP-Secure, a lightweight, host-side enforcement layer for the Model…
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Scalability and Sustainability of Linear WSNs Using Erasure Coding-Based TDMA Scheduling
Linear multi-hop wireless sensor networks (LWSNs) are commonly used for infrastructure monitoring and event detection where single-hop communication and wired links are impractical. Despite their cost-effectiveness and ease of deployment, these networks often suffer packet loss due to link…
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METS: Metadata-Embedded Steganography for Digital Rights Tracking in LLM-Generated Text
Large language models (LLMs) have enabled unprecedented advances in text generation but also pose significant challenges for authorship verification and copyright protection. Existing zero-bit watermarking schemes merely indicate the presence of a watermark without conveying specific metadata such…
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Artikel Jurnal
Temporal and Relational Graph Neural Networks for Fraud Detection in Transaction Networks
Financial fraud in credit card and bank transactions remains a significant challenge, as traditional detection systems often struggle to keep pace with evolving fraudulent strategies. This paper addresses the problem by formulating fraud detection as a supervised link prediction task in transaction…