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Connection Science
Scopus
ISSN 0954-0091 · Taylor & Francis Group · 439 articles in the index
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Journal Article
A novel hybrid deep learning framework with volatility-weighted loss for high-fidelity stock price prediction
Historical stock price data and technical indicators, such as close, volume, and open interest, are widely applied to improve forecasting and market understanding. These indicators capture essential information on trends, volatility, and potential reversals, offering actionable insights for traders…
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Journal Article
Enhanced conditional diffusion network for facial animation generation
With the increasing demand for realistic facial animation in applications such as virtual reality, film, and video conferencing, existing methods face challenges in preserving high-fidelity details and accurate motion dynamics. Traditional GAN-based approaches often introduce artifacts and lack the…
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Journal Article
Triangulating research discourse on tiktok: integrating bibliometrics, sentiment analysis and topic modeling
This paper investigates the academic discourse surrounding TikTok, the globally influential short-video social media platform, with a particular focus on its relationship with politics (accounting for 24.7% of the total papers). It aims to uncover trends, entities and links within TikTok-related…
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Journal Article
DAMS-Mamba: integrating dynamic attention and multi-scale modelling for cerebral vessel segmentation
Recent developments in the fields of deep learning and computer vision have significantly impacted the segmentation of medical images, especially in the challenging task of cerebral vessel segmentation. The complexity of vascular structures and the need for high clinical accuracy present unique…
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Journal Article
Enhanced CAD patient length of stay prediction using the Graph Neuro Boost model
Coronary Artery Disease (CAD) remains one of the leading causes of mortality worldwide and accounts for a great number of prolonged hospital stays, which increase the cost of healthcare and its resource consumption. This research presents Graph Neuro Boost, a new method of predicting hospital LOS…
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Journal Article
Subcluster: towards scalable and efficient KPIs clustering for cybersecurity operation via representative subsequence extraction
Modern cybersecurity infrastructure management is facing the challenge of an explosion in the number of machines and Key Performance Indicators(KPIs). As a fundamental data-mining technique, clustering can not only group data with similar characteristics but also provide informative insights that…
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Journal Article
Object-zoomed training of convolutional neural networks inspired by toddler development improves shape bias
Convolutional Neural Networks (CNNs) surpass human-level performance on visual object recognition, yet their behavior differs from humans in important ways. One prominent example is that CNNs trained on ImageNet exhibit a texture bias, while humans show a strong shape bias. Although CNN shape bias…
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Journal Article
RBC-AD: conformal anomaly detection with explicit false-alarm control for the Tennessee Eastman Process
Fault detection in the Tennessee Eastman Process (TEP) is challenged by transient dynamics, post-injection regime transitions, and score drift that destabilize fixed-threshold detectors and increase false alarms. In the proposed Risk-Budgeted Conformal Anomaly Detection (RBC-AD) framework, a…
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Journal Article
A deep learning framework for tonal trajectory, segment dynamics, and speaker influence in political talk shows
This study introduces a computational framework for analyzing the tonal structure and interactional dynamics of political discussion programs broadcast on Turkish television. Using a self-constructed dataset of televised debates featuring journalists, politicians, and commentators, we trained a CNN…
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Journal Article
Multi-modal affective computing framework for real-time monitoring of children's learning engagement
Children's attention monitoring is crucial in education for improving learning outcomes. However, existing methods often rely on single-modality inputs, making it difficult to address the complexity of children's emotional expressions and attention fluctuations. This paper presents CSW-FocusNet, a…
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Journal Article
Fuzzy spiking neural network-based neuroadaptive cooperative control for nonlinear UAV systems
Achieving reliable cooperative control in multi-agent systems is often impeded by complex environmental disturbances, such as wind fields, which simultaneously affect the entire swarm. To address this, we propose a resource-efficient cooperative control framework that enables agents to…
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Journal Article
Enhancing location accuracy in urban logistics using hybrid machine learning and deep learning models on large-scale global positioning system data
As technology advances, analyzing Global Positioning System (GPS) data is critical to improving location accuracy in product distribution. In this study, the geolocation accuracy of a distribution company in Istanbul was evaluated using 4,784,003 GPS records and prediction models, including machine…
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Journal Article
Analysing student learning pathways in educational systems using CRNN-based multichannel temporal modelling
With the rapid growth of educational data, analysing students’ learning pathways has become increasingly challenging. Traditional learning behaviour analysis methods struggle to handle multi-channel and heterogeneous data, and they often fail to capture complex relationships among student…
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Journal Article
Variational spatiotemporal enhanced transformer encoder-decoder for robust EEG signal recognition
Electroencephalogram (EEG)-based brain–computer interfaces (BCIs) decode neural intent but remain vulnerable to non-stationarity, low signal-to-noise ratios, complex spatiotemporal dynamics, and inter-trial variability. Existing deterministic deep models often fail to capture global temporal…
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Journal Article
SMLIE: a SHA-512 seeded multi-layer image encryption algorithm for medical image security
Protection of medical images during transmission and storage is critical for ensuring patient confidentiality. To provide secure encryption for healthcare applications, this study proposes the SHA-512 Seeded Multi-Layer Image Encryption (SMLIE) algorithm. It generates a session-specific key by…
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Journal Article
A near CXL memory processing architecture for distributed graph neural network inference and training
Distributed Graph Neural Networks (GNNs) require efficient handling of both fine-grained memory accesses and cross memory-device communication, particularly when scaling to large graphs. However, existing acceleration solutions fail to adequately address low bandwidth utilization and scalability…
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Journal Article
CADRNet: geometric figure recognition in architectural drawings via dynamic feature pyramid and cross-architecture adapter
Automatic recognition of symbols in computer-aided design (CAD) drawings is a key bottleneck in achieving digital transformation of engineering design. The main challenge is the multi-scale variability of engineering symbols and their complex contextual dependencies. In this study, CADRNet, a…
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Journal Article
Uncertainty-aware traffic prediction and routing for emergency vehicles: a multi-objective risk-aware framework
Efficient emergency vehicle routing in urban environments is critical for timely medical response, yet existing approaches often decouple traffic prediction from routing, overlook heterogeneous uncertainty, and lack causal reasoning under routing interventions. We propose an end-to-end…
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Journal Article
L2G-transT: a local-to-global multi-scale attention framework for robust vehicle tracking
Vehicle tracking in complex traffic environments remains a challenging task due to frequent target occlusion, high visual similarity among vehicles, and cluttered backgrounds. These factors often result in tracking drift and target misidentification, undermining the reliability of tracking systems…
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Journal Article
RMF: one-step radio map reconstruction via mean flow matching
Accurate radio map construction is essential for 6 G wireless network optimization, yet faces significant challenges due to sparse real-world measurements and dynamic environmental obstacles. This paper presents RMF, a novel one-step generative model based on mean flow matching that enables direct…