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Discover Computing
Scopus
ISSN 2948-2992 · Springer · 906 artikel di indeks
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Artikel Jurnal
Information retrieval framework using knowledge graph embeddings and uncertainty modelling using probabilistic soft logic
Abstract The growing complexity and uncertainty inherent in modern information retrieval tasks necessitate systems that can reason probabilistically while leveraging rich semantic structures. This research explores the core question: How can uncertainty-aware retrieval be enhanced through the…
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Artikel Jurnal
A data analytics based federated biometrics for deepfake fraud detection in financial multimedia systems
Abstract Detecting deepfake-based fraud in financial Video Know Your Customer (V-KYC) systems is increasingly critical due to sophisticated AI-generated manipulations and stringent privacy regulations. This study proposes FMM-MMF (Federated Micro-Expression Mining and Multi-Modal Metadata Fusion)…
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Artikel Jurnal
Cybersecurity challenges and solutions in 5G-enabled internet of things
Abstract Due to the growing interconnection and sensitive nature of IoT applications, this article provides a comprehensive overview of cybersecurity in 5G-enabled Internet of Things (IoT) networks. The review highlights the significant potential of 5G technology while also emphasizing the need for…
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Artikel Jurnal
Legal text summarization with optimized hybrid models and fine-tuned LLaMA-2
Abstract Legal document summarization presents a critical challenge due to the dense, complex nature and extreme length of legal texts. This paper proposes and evaluates two distinct methods for this task. The first is an optimized hybrid model that combines TextRank for extractive summarization…
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Artikel Jurnal
Hybrid ensemble model for automated assessment of delinquency levels in adolescents via random subspace learning
Abstract Timely intervention and behavioral correction are contingent upon the early detection of juvenile delinquency. With the use of several decision-based classifiers and the random subspace technique, this study suggests a strong ensemble learning framework for automated assessment of…
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Artikel Jurnal
A multivocal grey literature review on fake news and risk management
Abstract The proliferation of fake news presents an emerging and complex cybersecurity challenge in the realm of information systems, with significant implications for security. This study investigates the intersection of fake news and risk management through a Multivocal Literature Review, drawing…
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Artikel Jurnal
The role of Industry 5.0 Internet of Things adoption on sustainable performance of manufacturing SMEs through the integration of supply chain
Abstract Organisations today face an increasingly complex and rapidly changing business environment, driving them towards adopting advanced technological innovations to achieve sustainable success. This study focuses on the impact of adopting Internet of Things (IoT) technologies within Industry…
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Artikel Jurnal
AI-driven anonymization for secure and privacy-preserving business intelligence cloud migration
Abstract Sensitive data protection is a key issue in the context of Business Intelligence (BI), especially considering the increasing emergence of outsourcing computing over cloud. This paper presents an AI-driven automated solution designed to conceal sensitive data while maintaining its integrity…
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Artikel Jurnal
Crop disease detection using EfficientNetB0 deep learning approach for precision agriculture
Abstract Crop disease detection plays a crucial role in modern agriculture by enabling timely interventions to address diseases that directly impact crop yields and global food security. This research aims to explore a novel deep-learning approach for detecting crop diseases. We utilize the…
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Artikel Jurnal
A causal inference for digital infrastructure construction and green innovation using double machine learning
Abstract During global digital transformation, advancing digital infrastructure has emerged as a catalyst for green development in China. Leveraging the Broadband China Pilot policy as a quasi-natural experiment for digital infrastructure construction, this study employs double machine learning…
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Artikel Jurnal
Predictive modelling of Australian school principals’ turnover intentions using machine learning with random effects
Abstract This study identifies key predictors of Australian school principals’ turnover intention, using a machine learning approach—extreme gradient boosting (XGBoost) with random effects. Drawing on data from 1630 Australian principals across two years, the prediction model includes 89…
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Artikel Jurnal
Design and performance evaluation of a green LED OFDM LiFi system for an electromagnetic interference sensitive hospital network
Abstract Light Fidelity (LiFi) is an alternative technology to Wireless Fidelity (WiFi) for secure, high-speed hospital communication. The main objective of this study is to design a Four-Quadrature Amplitude Modulation-Orthogonal Frequency Division Multiplexing (4QAM-OFDM) LiFi system that…
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Artikel Jurnal
Evaluating the performance of generative artificial intelligence models in multidimensional data analysis tasks: a comparative study with large language models
Abstract This study presents a comparative performance evaluation of state-of-the-art generative artificial intelligence models in the context of data analysis. Eight large language models (Claude, Gemini, ChatGPT, Qwen, Grok, DeepSeek, LLaMA, and Mistral) were tested on 13 distinct analytical…
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Artikel Jurnal
Adaptive teaching mode optimization using reward-shaped deep reinforcement learning and big data mining
Abstract Teaching mode refers to the method used to deliver educational content, including lectures, demonstrations, and hands-on activities, designed to meet students’ diverse needs and engagement. Teaching mode innovation is transforming education by utilizing advanced technologies to create…
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Artikel Jurnal
Operation control of visualization VR teaching platform for mechanical manufacturing professional course under iterative learning PID algorithm
Abstract To address the issue of operational instability in the VR visualization teaching platform for mechanical manufacturing courses—caused by significant errors in system variables during complex tasks such as virtual environment rendering, interactive operations, and data…
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Artikel Jurnal
Modified YOLOv8x model for coronary stenosis detection and troponin risk stratification
Abstract Detection of coronary artery stenosis and risk stratification of troponin plays a pivotal role in offering early diagnosis and treatment of cardiovascular diseases. In this paper, an improved deep learning framework that allows using both spatial and frequency-based attention mechanisms…
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Artikel Jurnal
Optimized deep learning-based multi-stage Alzheimer’s disease characterization with temporal modeling and soft-NMS for neuroimaging
Abstract Alzheimer’s disease (AD) represents an important and growing global health challenge, characterized by progressive neurodegeneration and cognitive decline. Early and accurate diagnosis, especially distinguishing between different stages such as cognitively normal (CN), mild cognitive…
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Artikel Jurnal
An ensemble deep learning model based on graph neural networks for intelligent caching in next generation data centers
Abstract Repeated user requests to edge servers increase traffic load and content-delivery latency. Although recommender-driven caching is promising, it still faces challenges of scalability, sparsity, cold-start, and limited generalization. We subsequently develop an error-aware ensemble method…
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Artikel Jurnal
Multiattention network with HFA-UNet for remote sensing semantic segmentation of Wular Lake in India
Abstract Semantic segmentation is crucial to remote sensing imaging (RSI) analysis of varied landscapes and objects. The Hybrid Feature Adaptive UNet (HFA-UNet) improves RSI semantic segmentation by combining spatial and channel attention modules into a convolutional network. This work intends to…
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Artikel Jurnal
Cluster head based dual level node authentication model with node pattern analysis for intrusion detection in wireless sensor networks using machine learning
Abstract The application of Wireless Sensor Networks (WSNs) in military and civilian scenarios is on the rise but since they are operated in the open and unsecured world, they are extremely susceptible to routing attacks like wormhole, sinkhole, sybil, and black hole attacks. A WSN consists of a…