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PeerJ Computer Science
Scopus
ISSN 2376-5992 · PeerJ Inc. · 3.939 artikel di indeks
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PETRoberta: a novel method for charging station site selection evaluation
With the rapid adoption of electric vehicles, rational planning for charging station locations has become increasingly important. This study proposes a data-driven prompt learning–based approach for evaluating the suitability of charging station placement. By transforming regional features into…
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Enhanced fire detection: a weighted bounding box fusion approach based on Dempster–Shafer theory
In this study, we present an advanced fire detection approach using an improved weighted bounding box fusion technique based on Dempster–Shafer theory. A key challenge in fire detection is the inherent uncertainty in distinguishing true fire events from false positives (e.g., fire-like objects or…
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G-Pro bot: a GraphRAG-powered GIS (Geographical information system) chatbot
Generative artificial intelligence (GAI) is gaining increasing popularity, but its applications in the Geographical Information System (GIS) domain remain limited. Consequently, answers to domain-specific questions often lack depth and specialization. GraphRAG presents a promising solution by…
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Digital twin-enabled AI for sustainable traffic management: real-time urban mobility optimization in smart cities
An intelligent and agile traffic signal system has emerged as a vital sustainable component of urban mobility. The centralised traffic control systems currently in use are not capable of providing the required responsiveness or scalability to facilitate real-time traffic management. In this…
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Design of packaging style recommendation system based on user behavior analysis and emotional feature extraction
With the rapid growth of e-commerce, consumer demand for personalized packaging solutions has grown significantly. To address this issue, this article constructs an intelligent recommendation model that combines user behavior data and sentiment analysis techniques. Firstly, a user behavior…
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Analysis of deep convolutional GAN-based data augmentation for early detection of Alzheimer’s disease
Early and accurate detection of Alzheimer’s disease (AD), particularly at the very mild and mild cognitive impairment stages, remains a significant clinical challenge due to subtle anatomical changes and overlapping imaging features between classes. This study evaluates the effectiveness of…
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Nocturnal non-speech sound classification with multi-spectrogram feature fusion and an attention-based stacked hybrid convolutional bidirectional long short-term memory–vision transformer architecture
Nocturnal non-speech sounds encapsulate critical physiological and behavioral information, making them a valuable modality for non-invasive assessment of sleep quality. Despite this potential, existing approaches predominantly rely on single-view spectral features or shallow learning architectures…
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Brain disease diagnosis using federated deep learning
Brain tumors often require treatment and multiple biopsies. They are the third most common cancer among young adults in both incidence and mortality. The expression of the O6-methylguanine-DNA methyltransferase (MGMT) gene plays an important role in predicting tumor behavior. It affects how…
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Design of an intelligent optimization framework for corporate financial management based on GA-FL-transformer
This article addresses lenges in enterprise financial management, including difficulties in processing multi-source data, limited adaptability to dynamic environments, and a lack of systematic integration in the decision-making process. To tackle these issues, a new intelligent optimization…
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DC-TSCM: an interpretable dual-channel traditional Chinese medicine syndrome classification model via semantic-structural fusion
Background With the widespread adoption of electronic medical records, massive prescription data can be digitized and systematically stored. This provides a solid foundation for intelligent traditional Chinese medicine (TCM) diagnosis systems. TCM syndrome classification is the core of syndrome…
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Effects of parameters of particle swarm optimization algorithms on the path planning for flexible needles
Background Percutaneous puncture has wide applications in various clinical tasks. Path planning is crucial but challenging. Particle swarm optimization (PSO) algorithms are proper candidates to solve this problem and have been introduced. However, path planning errors exist and the effects of PSO…
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Risk-aware diffusion model for generating extreme weather scenarios and safety evaluation in autonomous driving
Extreme weather scenarios, are likely to cause safety hazards such as perception failures and decision-making anomalies. These scenarios are indispensable for the safety assessment and robustness testing of autonomous driving systems. Most existing scenario generation methods focus on manually…
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Masked timesteps in spiking neural networks for efficient time series classification
Spiking neural networks (SNN) accurately emulate the neurodynamics of biological neurons, theoretically enhancing the processing capabilities for time series data by using spike trains. Existing research, however, has largely remained in an exploratory stage, focusing primarily on the potential of…
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Topic-aware transformer with hierarchical prompting learning for multi-label image classification
While existing multi-label classification methods primarily focus on capturing label co-occurrence patterns, they often fail to explore the global contextual information and the semantic hierarchy inherent in multi-label datasets, especially in large-scale label spaces, leading to suboptimal…
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Detecting differentiated services code point values and packet length mismatch in internet protocol packet headers
The Differentiated Services Code Point (DSCP) field in Internet Protocol (IP) headers lets you set Quality of Service (QoS) priorities. If the DSCP values and packet lengths mismatch, it could mean that the network is not set up correctly, that policies are being broken, or that traffic is being…
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Anomaly synthesis and detection in accounting data via a generative adversarial network
To address the challenge of anomaly detection in high-dimensional, heterogeneous accounting data, we propose multimodal fusion generative adversarial network (MF-GAN), a multimodal fusion framework that integrates synthesis and detection within a unified architecture. MF-GAN employs a dual-branch…
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TGMF-pose: text-guided multi-view 3D pose estimation and fusion network for online sports instruction
Background Posture estimation technology has been widely applied in online sports instruction to provide precise motion recognition and real-time correction, which significantly improves teaching quality and learning outcomes. However, existing methods often struggle to capture subtle differences…
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Moth-flame optimized UNet++ with self-attention for early-stage Alzheimer’s disease prediction using multimodal input
Early-stage identification of Alzheimer’s Disease (AD) is a sizeable challenge to health care globally due to its progressive nature and the fact that there is no available effective treatment. It becomes strategic for practices using interventions meant to halt or reverse cognitive decline if…
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Artificial intelligence-enhanced CSI-based Wi-Fi sensing for non-contact vital sign monitoring: a systematic review
Background In the recent era, non-invasive health monitoring has gained attention as a crucial component of healthcare. Especially with the advancements in artificial intelligence (AI) and Wi-Fi-based sensing technologies offering promising solutions. These technologies can detect vital signs and…
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Automatic medical report generation: a comprehensive review of methodologies and applications
The increasing demand for medical imaging has significantly challenged healthcare systems, emphasizing the need for efficient and accurate diagnostic support tools. Recent advancements in computer vision (CV) and natural language processing (NLP) have demonstrated great promise in addressing these…
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