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Human-Centric Intelligent Systems
Scopus
ISSN 2667-1336 · Springer Nature · 157 artikel di indeks
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Artikel Jurnal
Psychological Anxiety Risk Analysis Model Based on Large Language Model Interaction
Abstract In recent years, psychological anxiety has emerged as a pervasive mental health issue impacting socioeconomic development and individual well-being, making scientific assessment of anxiety crucial. While traditional manual evaluation methods and machine learning-based automated assessment…
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YOLOv11-HBDY: A Unified Hybrid Model Integrating NAM-R, CBH-R, and Ghost Convolutions for Multi-task Mpox Lesion Analysis
Abstract Recent mpox (monkeypox) outbreaks have intensified global public health concerns and underscored the urgent demand for accurate, scalable, and accessible diagnostic systems. Correctly distinguishing the five clinical stages of cutaneous lesions—macules, papules, vesicles, pustules, and…
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Artikel Jurnal
Seeing the Threat: Vulnerabilities in Vision-Language Models to Adversarial Attack
Abstract Large Vision-Language Models (LVLMs) have shown remarkable capabilities across a wide range of multimodal tasks. However, their integration of visual inputs introduces expanded attack surfaces, thereby exposing them to novel security vulnerabilities. In this work, we conduct a systematic…
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Artikel Jurnal
iTrace: Click‑Based Gaze Visualization on the Apple Vision Pro
Abstract The Apple Vision Pro is equipped with accurate eye-tracking capabilities; however, its privacy restrictions prevent direct access to continuous user gaze data. This study introduces iTrace, a novel application that overcomes these limitations through click-based gaze extraction techniques…
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Research on the Construction and Reasoning of Educational Knowledge Graph Based on Pre-trained Language Model
Abstract In this paper, we propose a comprehensive framework for educational knowledge graph construction and reasoning that integrates pre-trained language models with structured knowledge representation to address complex educational knowledge organization and inference challenges. Our approach…
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Artikel Jurnal
Floor Plan Semantic Segmentation Network with Gated Channel-Spatial Fusion and Explicit Boundary Constraint
Abstract To address challenges in floor plan segmentation, specifically structural disconnection caused by insufficient long-range dependency capture, and semantic region overflow resulting from inadequate geometric-semantic fusion, an Explicit-boundary Dual-stream Attention Network (EDANet) is…
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Trust-Aware Federated User Representation Learning for Privacy-Preserving and Carbon-Optimized Personalized Recommendation in Large-Scale Social Platforms
Abstract Personalized recommendation in large-scale social platforms faces challenges of privacy preservation, trustworthiness of user contributions, and high carbon footprint due to computationally intensive training. Traditional centralized and federated approaches often overlook user…
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Mitigating Class Imbalance in Human Resources Attrition Prediction using Hybrid Generative and Cluster-Driven Ensemble Modeling
Abstract Modern organizations continue to have a major problem with employee attrition, which has an impact on long-term strategic planning, operational effectiveness, and workforce stability. For data-driven human resource (HR) management, it is important to be able to accurately estimate…
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Feature-Importance-Weighted Distance Metrics for Enhanced k-Nearest Neighbors Classification in Medical Diagnosis
Abstract Traditional k-Nearest Neighbors (KNN) classification assumes equal feature importance, which limits its effectiveness in domains where features exhibit inherently different levels of relevance. This study introduces a systematic feature importance weighted distance framework that…
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Towards a Human-Centric Intelligent Lighting System in Expressway Tunnels: A Deep Learning Based Framework for Luminance Demand Prediction
Abstract Traditional expressway tunnel lighting systems usually lack sufficient consideration of the dynamic luminance demand arising from real-time traffic conditions and smooth luminance transitions between different tunnel lighting sections. These shortcomings may impede the effective…
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Leveraging Graph Transformers for Knowledge Editing in Large Language Models
Abstract Large Language Models (LLMs) have transformed natural language processing, yet their static knowledge bases present significant challenges, such as temporal obsolescence and factual inconsistencies, limiting their effectiveness in real-world applications. Knowledge editing offers an…
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Artikel Jurnal
LE-HRNet: A Lightweight High-Resolution Network for Efficient Human Pose Estimation
Abstract Human pose estimation is a core task in computer vision, aiming to accurately locate keypoints of the human body in images. While current deep learning-based networks (such as HRNet) can preserve fine spatial details, their high computational complexity and parameter count hinder their…
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Artikel Jurnal
Dynamic Reward-Guided with Multi-Head Attention for Actor-Critic Policy Learning Optimization
Abstract In offline reinforcement learning, model-based approaches have demonstrated superior data efficiency by leveraging learned dynamics models to generate additional training samples. However, due to inevitable model inaccuracies, directly deriving policies from such models often leads to…
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Advancing Holonic Systems in the Era of Artificial Intelligence and Digital Twins for Trustworthy and Effective Human-Centric Intelligent Systems
Abstract Holonic systems provide a powerful paradigm for modeling complex, distributed, and autonomous systems. However, their deployment in large-scale, heterogeneous environments raises challenges related to coordination, semantic alignment, bias migration, ethical reasoning, and real-time…
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ML-Based Threat Severity Detection in Cyber-Physical Systems for Smart Environments Using Behavioral Analysis
Abstract The extensive adoption of cyber-physical systems (CPS) in daily life has led to an increase in cybersecurity vulnerabilities in both physical and digital domains. Traditional rule-based and signature defenses are inadequate for safeguarding against emerging technologies and zero-day…
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Human-Centered Intelligent Systems for Railroad Energy Management: A Behavioral Analysis Framework using Machine Learning for Technology Assessment and Social Impact
Abstract The shift toward sustainable railroad energy systems calls for intelligent, human-centered solutions that consider not only technical performance but also behavioral dynamics and social impact. This study proposes a behavioral analysis framework powered by machine learning to assess…
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Artikel Jurnal
Algorithmic Governance: Gender Bias in AI-Generated Policymaking?
Abstract Artificial Intelligence (AI) tools are becoming deeply embedded in everyday life and increasingly influence or automate decision-making processes that could shape not only public opinion but also policies. As their potential impact grows, it is essential to assess the inclusivity of the…
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Artikel Jurnal
Moral Attribute Elicitation for Automated Vehicles: Does Scenario Presentation Method Matter?
Abstract The development of automated vehicles (AVs) presents significant ethical challenges, particularly in eliciting moral attributes from humans to guide AV decision-making in high-risk situations. This study explores whether two different elicitation methods—specifically, 3D animations and 2D…