Results 221 to 230 of about 215,342 (268)

Assessing Capability Complexity Using Enterprise Architecture Framework

Systems Engineering, EarlyView.
ABSTRACT This study proposes a structured and quantitative methodology to evaluate the holistic complexity of system‐of‐systems (SoSs), employing the Zachman Architecture Framework (ZAF) as its foundational analytical tool. A five‐phase analytical procedure is developed and empirically validated, encompassing: (1) refinement of complexity measures, (2)
Javad Bakhshi, Mahmoud Efatmaneshnik
wiley   +1 more source

Factors influencing the nature of client complaint behaviour in the aftermath of adverse events

Veterinary Record, Volume 196, Issue 6, 15/22 March 2025.
Abstract Background Negative veterinary client complaint behaviour poses wellbeing and reputational risks. Adverse events are one source of complaint. Identifying factors that influence adverse event‐related complaint behaviour is key to mitigating detrimental consequences and harnessing information that can be used to improve service quality, patient ...
Julie Gibson, Kate White, Liz Mossop, Marnie L. Brennan   +3 more
wiley   +1 more source

Pickin' up good vibrations: a systematic review of footfall detection and analysis in the realm of wildlife surveying

Wildlife Biology, EarlyView.
Exploration of new wildlife surveying methodologies that leverage advances in sensor technology and machine learning has led to tentative research into the application of seismology techniques. This, most commonly, involves the deployment of a footfall trap – a seismic sensor and data logger customised for wildlife footfall.
Benjamin J. Blackledge, Luigi La Spada, Robert A. Briers, Niamh M. McHugh, Patrick J. C. White   +4 more
wiley   +1 more source

Pixel Lens: A Granular Assessment of Saliency Explanations

Artificial Intelligence for Engineering, EarlyView.
We propose a pipeline that detects shortcut‐dominated classifiers by comparing predictions on clean and shortcut‐perturbed images and checking dominance via a Shapley‐based ground‐truth explainer. The workflow quantifies the explanation quality of different explainable artificial intelligence (XAI) methods.
Kanglong Fan, Chen Ma, Yifan Peng, Jinglong Yang, Qilin Sun, Yuming Fang   +5 more
wiley   +1 more source

Review on enhancing clinical decision support system using machine learning

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood, Usman Naseem, Junaid Rashid, Jungeun Kim, Imran Razzak   +4 more
wiley   +1 more source

Deviation‐Guided Attention for Semi‐Supervised Anomaly Detection With Contrastive Regularisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Anomaly detection (AD) aims to identify abnormal patterns that deviate from normal behaviour, playing a critical role in applications such as industrial inspection, medical imaging and autonomous driving. However, AD often faces a scarcity of labelled data. To address this challenge, we propose a novel semi‐supervised anomaly detection method,
Guanglei Xie, Xiaochang Hu, Yi Sun, Wenzhuo Zhang, Yafeng Bu, Hao Fu, Xin Xu   +6 more
wiley   +1 more source

Tibetan Data Augmentation via GAN‐Based Handwritten Text Generation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Increased awareness of Tibetan cultural preservation, along with technological advancements, has led to significant efforts in academic research on Tibetan. However, the structural complexity of the Tibetan language and limited labeled handwriting data impede advancements in Optical Character Recognition (OCR) and other applications.
Dorje Tashi, Bingtian Chen, Tianying Sheng, Yongbin Yu, Xiangxiang Wang, Jin Zhang, Lobsang Yeshi, Rinchen Dongrub, Thupten Tsering, Nyima Tashi   +9 more
wiley   +1 more source

Multi‐Scale Transformer for Image Restoration

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Although Transformer‐based image restoration methods have demonstrated impressive performance, existing Transformers still insufficiently exploit multiscale information. Previous non‐Transformer‐based studies have shown that incorporating multiscale features is crucial for improving restoration results.
Wuzhen Shi, Youwei Pan, Chun Zhao, Yuqing Liu, Shaobo Zhang, Heng Zhang, Yang Wen   +6 more
wiley   +1 more source

Adversarial robust EEG-based brain-computer interfaces using a hierarchical convolutional neural network. [PDF]

Sci Rep
Samuel J, Murugan TK, Govindaraj L, Balaji M, SenthilKumar V, Sundararajan S.   +5 more
europepmc   +1 more source