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Big Data and Cognitive Computing
Scopus
ISSN 2504-2289 · MDPI AG · 1.406 artikel di indeks
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Artikel Jurnal Teks lengkap
Thinking Machines: Mathematical Reasoning in the Age of LLMs
Large Language Models (LLMs) have demonstrated impressive capabilities in structured reasoning and symbolic tasks, with coding emerging as a particularly successful application. This progress has naturally motivated efforts to extend these models to mathematics, both in its traditional form…
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Unifying Aesthetic Evaluation via Multimodal Annotation and Fine-Grained Sentiment Analysis
With the rapid growth of visual content, automated aesthetic evaluation has become increasingly important. However, existing research faces three key challenges: (1) the absence of datasets combining Image Aesthetic Assessment (IAA) scores and Image Aesthetic Captioning (IAC) descriptions; (2)…
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A Systematic Review and Bibliometric Analysis of Automated Multiple-Choice Question Generation
The aim of this study is to systematically capture, synthesize, and evaluate current research trends related to Automated Multiple-Choice Question Generation as they emerge within the broader landscape of natural language processing (NLP) and large language model (LLM)-based educational and…
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Large Model in Low-Altitude Economy: Applications and Challenges
The integration of large models and multimodal foundation models into the low-altitude economy is driving a transformative shift, enabling intelligent, autonomous, and efficient operations for low-altitude vehicles (LAVs). This article provides a comprehensive analysis of the role these large…
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Extracting Metasystem: A Novel Paradigm to Perceive Complex Systems
Abundant evidence shows that there is a core component within a complex system, referred to as the metasystem, that fundamentally shapes the structural and dynamical characteristics of a complex system. The limitations of existing techniques for analyzing complex systems have made it increasingly…
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Data-Driven Life-Cycle Assessment of Household Air Conditioners: Identifying Low-Carbon Operation Patterns Based on Big Data Analysis
Air conditioners are a critical adaptation measure against heat- and cold-related risks under climate change. However, their electricity use and refrigerant leakage increase greenhouse gas (GHG) emissions. This study developed a data-driven life-cycle assessment (LCA) framework for residential room…
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Using Large Language Models to Detect and Debunk Climate Change Misinformation
The rapid spread of climate change misinformation across digital platforms undermines scientific literacy, public trust, and evidence-based policy action. Advances in Natural Language Processing (NLP) and Large Language Models (LLMs) create new opportunities for automating the detection and…
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Delay-Driven Information Diffusion in Telegram: Modeling, Empirical Analysis, and the Limits of Competition
Information diffusion models developed for Twitter, Reddit, and Facebook assume network contagion and competition for shared attention. Telegram operates differently. It is built around channels rather than social graphs, and users receive posts directly from subscribed channels without algorithmic…
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TRACE: Topical Reasoning with Adaptive Contextual Experts
Retrieval-Augmented Generation (RAG) is widely used for long-text summarization due to its efficiency and scalability. However, standard RAG methods flatten documents into independent chunks, disrupting sequential flow and thematic structure, resulting in significant loss of contextual information…
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Improving Flat Maxima with Natural Gradient for Better Adversarial Transferability
Deep neural networks are vulnerable and susceptible to adversarial examples, which can induce erroneous predictions by injecting imperceptible perturbations. Transferability is a crucial property of adversarial examples, enabling effective attacks under black-box settings. Adversarial examples at…
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Big Data and Cognitive Computing: Five New Journal Sections Established
The journal Big Data and Cognitive Computing (BDCC) is a scholarly online journal which provides a platform for big data theories with emerging technologies on smart clouds and exploring supercomputers with new cognitive applications [...]
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Adaptive Data Prefetching for File Storage Systems Using Online Machine Learning
Data prefetching is essential for modern file storage systems operating in large-scale cloud and data-intensive environments, where high performance increasingly depends on intelligent, adaptive mechanisms. Traditional rule-based methods and recently proposed machine learning-based techniques often…
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Machine Learning-Based Prediction of Operability for Friction Pendulum Isolators Under Seismic Design Levels
Within the scope of the study, the parameters of friction pendulum-type (FPS) isolators used or planned to be used in different projects were evaluated specifically for the project and its location. The evaluations were conducted within a performance-based seismic design framework using…
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Data-Driven Insights: Leveraging Sentiment Analysis and Latent Profile Analysis for Financial Market Forecasting
Background: This study explores an innovative integration of big data analytics techniques aimed at enhancing predictive modeling in financial markets. It investigates how combining sentiment analysis with latent profile analysis (LPA) can accurately forecast stock prices. This research aligns with…
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A Review on Fuzzy Cognitive Mapping: Recent Advances and Algorithms
Fuzzy Cognitive Maps (FCMs) are a type of recurrent neural network with built-in meaning in their architecture, originally devoted to modeling and scenario simulation tasks. These knowledge-based neural systems support feedback loops that handle static and temporal data. Over the last decade, there…
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Image–Text Multimodal Sentiment Analysis Algorithm Based on Curriculum Learning and Attention Mechanisms
With the rapid development of mobile internet technology, the explosive growth of image–text multimodal data generated by social networking platforms has provided rich practical scenarios and theoretical research value for multimodal sentiment analysis. However, existing methods generally suffer…
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Driving Simulator Performance After Acquired Brain Injury: A Comparative Study of Neuropsychological Predictors
Acquired brain injury (ABI) often results in cognitive and motor impairments that can compromise driving ability, an essential aspect of independence and social participation. This study utilized a custom-designed driving simulator to compare driving performance between individuals with ABI and…
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FakeVoiceFinder: An Open-Source Framework for Synthetic and Deepfake Audio Detection
AI-based audio generation has advanced rapidly, enabling deepfake audio to reach levels of naturalness that closely resemble real recordings and complicate the distinction between authentic and synthetic signals. While numerous CNN- and Transformer-based detection approaches have been proposed…
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Phenomenological Semantic Factor Method for Risk Management of Complex Systems in Drifting
Managing risk in drifting complex systems is hindered by the weak integration of unstructured incident narratives into quantitative, decision-ready models. We present a phenomena-centric semantic factor framework that closes the data–model–decision gap by transforming free-text incident reports…
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Applications of Artificial Intelligence in Fisheries: From Data to Decisions
AI enhances aquatic resource management by automating species detection, optimizing feed, forecasting water quality, protecting species interactions, and strengthening the detection of illegal, unreported, and unregulated fishing activities. However, these advancements are inconsistently employed…
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