cs papers | Gist.Science

Measurement-guided, training-free Fourier correction: a cost-efficient alternative to generative adaptation for cold-start construction-scene segmentation

This paper introduces a cost-efficient, training-free Fourier correction protocol that quantifies and adjusts specific low-frequency amplitude mismatches between synthetic and real construction images to significantly improve cold-start segmentation performance for rare safety-critical classes without requiring extensive unlabeled target data or generative models.

Jonghun Gim, Jeongik Min2026-07-21✓ Author reviewed ⓘ

💻 computer science

CB-SentiLex: An Auditable Weak-Supervision Framework for Central Bank Stance Detection with a Bangladesh Bank Benchmark

This paper introduces CB-SentiLex, an auditable weak-supervision framework and the first reproducible NLP benchmark for a South Asian central bank, which successfully generates stance labels for a Bangladesh Bank corpus and demonstrates strong model performance alongside significant correlations with monetary policy directions, despite challenges from temporal concept drift.

Ann Naser Nabil, Umme Hafsa2026-07-21

💻 computer science

Recursive Cascade Instability and Targeted Stabilization in Multi-Agent AI Systems: Large-Scale Network Simulations Using an Ethical Field Theory Framework

This study introduces the Ethical Field Theory framework to demonstrate through large-scale simulations that adaptive targeted stabilization is significantly more effective than uniform regulation or no intervention in preventing recursive cascade instabilities across diverse multi-agent AI network topologies.

Ali Moslemi Tabrizi2026-07-21

💻 computer science

Co-identification of Vibration, Structural Looseness, and Surface Damage in Industrial Equipment Operation Videos

This paper presents a joint discrimination algorithm that synergistically identifies vibration states, structural looseness, and surface defects in industrial equipment videos by integrating spatiotemporal features from a Video Swin Transformer, micro-displacement features from RAFT optical flow, and multi-task appearance analysis, thereby significantly reducing missed detections in composite anomaly scenarios compared to single-task models.

Yukun Du, Zhihuang Chen, Quanle Liu, Yuang Dong2026-07-21

💻 computer science

Zero Trust for IT Governance and Risk Management: A Systematic Review and Conceptual Framework

This study employs a PRISMA 2020 systematic review of 73 peer-reviewed articles to bridge the gap between technical Zero Trust implementations and organizational governance, proposing a conceptual framework that links continuous verification and identity-centric controls to enhanced risk management and strategic IT objectives while highlighting critical gaps in SME adoption and AI-driven automation.

‪nabil almotawkel‬‏, Mohammed Alkohali, Sadeg Manaa, Osamah AL-Maamari, Ashraf Al-Godami, Shaima Alqahoom2026-07-21

💻 computer science

A Hybrid VGG16–PCA–Fuzzy Based Framework for the Classification of Morphologically Similar Maize Pests

This study proposes a hybrid VGG16–PCA–Fuzzy framework that integrates Gaussian membership-based uncertainty modeling to significantly improve the classification accuracy of morphologically similar maize pests, achieving a 97.17% accuracy rate that outperforms standalone VGG16 baselines.

Bonga G Baleni, Ayinde M Usman, Clement Nyirenda2026-07-21

💻 computer science

Chain-Hash Audit Framework with Trusted Anchoring for Tamper-Evident Evidence Lifecycle Management

This paper proposes the Chain-Hash Audit Framework (CHAF), a novel architecture that enhances traditional hash-chain logging by integrating authorization status, timestamps, and lifecycle properties with signed checkpoints and external anchoring to create a tamper-evident, verifiable evidence chain that significantly reduces audit reconstruction time for digital asset systems.

Jinyuan Li, Yulun Zhang, Yicheng Gu2026-07-21

💻 computer science

The Influence of Artificial Intelligence on Project Risk Identification and Mitigation

This study demonstrates that Artificial Intelligence significantly enhances project risk identification and mitigation through improved accuracy and data processing, while highlighting the critical need for human-AI collaboration frameworks to address challenges like information overload, algorithmic bias, and over-reliance.

Praise Adeleke2026-07-21

💻 computer science

An AI–BIM Integrated Framework for Rapid Early-Stage Energy Performance Prediction in Algerian Residential Buildings: A Machine Learning Approach Using Random Forest and XGBoost

This research presents an AI-BIM integrated framework utilizing Random Forest and XGBoost models to enable rapid, real-time energy performance prediction for Algerian residential buildings, thereby overcoming the limitations of traditional simulation tools during early-stage design.

BESSAI Hadjer2026-07-21

💻 computer science

Algorithmic Topological Resonance Theory: Realizing a Quantum Stateless AI Data Center Architecture via Zero-Payload I/O and Permanent O(1) Complexity

This paper proposes the Quantum Stateless AI Data Center (QS-AIDC) architecture, which utilizes Algorithmic Topological Resonance theory, Zero-Payload I/O, and Proof of Resonance consensus to achieve permanent O(1) complexity, eliminate data storage, and drastically reduce energy consumption by replacing traditional stateful computing with non-local, deterministic reconstruction.

Min Ho Jung2026-07-21

← Previous Next →