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关键词： Measurement   Generators   Network analyzers   Image edge detection   Generative adversarial networks   Computer science   Stability analysis   Centroid node   clustering   multiple local community detection (MLC)   network analysis   seed set expansion  

摘要： In recent years, the research of local community detection has attracted much attention. Most existing local community detection methods aim to find a single community of closely related nodes for a given query node, but in general, nodes are possible to belong to several communities, and detecting all the potential communities for a given query node is much more challenging. In this work, we propose a novel approach called the centroid-based multiple local community detection (C-MLC) to find all the communities for a query node. Differing from the existing local community detection methods that directly find a community from the query node, we assume that every community contains a "centroid " node, which locates in the core of the community and can be used to identify the community. Then, a query node corresponds to several centroid nodes if the query node belongs to multiple communities. The key ideas of C-MLC are that C-MLC automatically determines the number of communities containing the query node by finding the related centroid nodes and uses each query node together with the centroid node to uncover the corresponding community based on a set of high-quality seeds. Through extensive evaluations on real-world networks and synthetic networks, C-MLC outperforms the state-of-the-art methods significantly, demonstrating that finding the centroid nodes is a better approach to uncover the multiple local communities.

关键词： narrative inquiry   decoloniality   praxis   justice   sport  

摘要： Stories are always grounded in personal, collective, and ancestral experiences and come in a variety of visual, performance, textile, and text-based forms. Physical culture participation and politics can be better understood by engaging with the stories of people facing ongoing colonial and epistemic injustices, intersectional oppressions, as well as structural and cultural racism. In contrast to dominant trends in the cultural politics of sport, this article offers an ontological, epistemological, and methodological alternative. Following Black and decolonial scholars, we must honor non-Western storytelling modalities to listen to, tell, show, and center multiple experiences to resist Western colonial culture's binary structures and hierarchies, introduce alternate theorizations, and inject other ways of knowing and being into the (study of) sport and physical cultures. This article highlights several areas of Black and decolonial studies that will be essential to efforts at transformative justice in sport and sports scholarship: interdisciplinarity, counter-storytelling, and creation stories.

ISBN: (纸本)9783959773102

关键词： Graph neural networks   Motion pictures   Electronic mail   Computer science   Collaborative filtering   Behavioral sciences   Software   Collaborative filtering (CF)   disentangled representation learning   graph neural network (GNN)  

摘要： Collaborative filtering (CF) is dedicated to learning the representations of users and items based on interactive data. Regrettably, the lack of fine-grained modeling of interactive motivation makes the model less interpretable. A feasible solution is to combine the disentangling idea with the graph neural network (GNN) and capture different types of interaction relationships by using a message propagation mechanism on the graph of user-item interaction. However, this process typically relies on the disentangling of users' hidden intents, ignoring the significance of item features to user engagement. This fact leads to the inadequate interpretability of existing models. To make up for the deficiency, this article proposes a new feature-aware disentangled GNN (FDGNN) for the recommendation. By learning the relationship between user behavior and important features of items, the model aims to achieve better recommendation performance and model interpretability. In the end, we first realize the feature partition based on mutual information and then design an attention-based graph disentangling model to realize the fine-grained disentangling of user intents. In addition, to further ensure the independence of the disentangled intents, we augment the model with disagreement regularization. Through multilayer embedding propagation, FDGNN can display a capture CF effect in feature semantics. The interpretability and efficiency of our proposed approach are demonstrated by numerous pertinent experiments.

摘要： First-job readiness versus long-term career preparation.

关键词： Electrical and electronic engineering   Computer science  

摘要： Human-machine interfaces for capturing, conveying, and sharing tactile information across time and space hold immense potential for healthcare, augmented and virtual reality, human-robot collaboration, and skill development. To realize this potential, such interfaces should be wearable, unobtrusive, and scalable regarding both resolution and body coverage. Taking a step towards this vision, we present a textile-based wearable human-machine interface with integrated tactile sensors and vibrotactile haptic actuators that are digitally designed and rapidly fabricated. We leverage a digital embroidery machine to seamlessly embed piezoresistive force sensors and arrays of vibrotactile actuators into textiles in a customizable, scalable, and modular manner. We use this process to create gloves that can record, reproduce, and transfer tactile interactions. User studies investigate how people perceive the sensations reproduced by our gloves with integrated vibrotactile haptic actuators. To improve the effectiveness of tactile interaction transfer, we develop a machine-learning pipeline that adaptively models how each individual user reacts to haptic sensations and then optimizes haptic feedback parameters. Our interface showcases adaptive tactile interaction transfer through the implementation of three end-to-end systems: alleviating tactile occlusion, guiding people to perform physical skills, and enabling responsive robot teleoperation. Adaptive tactile interactions transfer across users, space, and time, via embroidered smart gloves is reported by the authors. The scalable fabrication and adaptive computation pipeline enable tactile occlusion alleviation, human skills transfer, and interactive teleoperation.

关键词： Engineering   Computer science  

摘要： Autonomous robots used in infrastructure inspection, space exploration and other critical missions operate in highly dynamic environments. As such, they must continually verify their ability to complete the tasks associated with these missions safely and effectively. Here we present a Bayesian learning framework that enables this runtime verification of autonomous robots. The framework uses prior knowledge and observations of the verified robot to learn expected ranges for the occurrence rates of regular and singular (e.g., catastrophic failure) events. Interval continuous-time Markov models defined using these ranges are then analysed to obtain expected intervals of variation for system properties such as mission duration and success probability. We apply the framework to an autonomous robotic mission for underwater infrastructure inspection and repair. The formal proofs and experiments presented in the paper show that our framework produces results that reflect the uncertainty intrinsic to many real-world systems, enabling the robust verification of their quantitative properties under parametric uncertainty.

关键词： Artificial intelligence   AI-generated output   Computer science   Medical documentation  

摘要： Purpose Chat generative pre-trained transformer (GPT) is a novel large pre-trained natural language processing software that can enable scientific writing amongst a litany of other features. Given this, there is a growing interest in exploring the use of ChatGPT models as a modality to facilitate/assist in the provision of clinical care. Methods We investigated the time taken for the composition of neurosurgical discharge summaries and operative reports at a major University hospital. In so doing, we compared currently employed speech recognition software (i.e., SpeaKING) vs novel ChatGPT for three distinct neurosurgical diseases: chronic subdural hematoma, spinal decompression, and craniotomy. Furthermore, factual correctness was analyzed for the abovementioned diseases. Results The composition of neurosurgical discharge summaries and operative reports with the assistance of ChatGPT leads to a statistically significant time reduction across all three diseases/report types: p < 0.001 for chronic subdural hematoma, p < 0.001 for decompression of spinal stenosis, and p < 0.001 for craniotomy and tumor resection. However, despite a high degree of factual correctness, the preparation of a surgical report for craniotomy proved to be significantly lower (p = 0.002). Conclusion ChatGPT assisted in the writing of discharge summaries and operative reports as evidenced by an impressive reduction in time spent as compared to standard speech recognition software. While promising, the optimal use cases and ethics of AI-generated medical writing remain to be fully elucidated and must be further explored in future studies.

关键词： Computer science   Information technology   Machine learning   Mathematics and computing  

摘要： A tragic scandal at the UK Post Office highlights the need for legal change, especially as organizations embrace artificial intelligence to enhance decision-making.

关键词： Machine learning   Computer science   Medical research   Society  

摘要： The chatbot, which is based on a large language model (LLM) developed by Google, was more accurate than board-certified primary-care physicians in diagnosing respiratory and cardiovascular conditions, among others. "To our knowledge, this is the first time that a conversational AI system has ever been designed optimallyfordiagnosticdialogueand taking theclinical history," says Alan Karthikesalingam, a clinical research scientist at Google Health in London and a co-author of the study, which was published this month in the arXiv preprint repository (T. Tu etal. To test the system, researchers enlisted 20 people who had been trained to impersonate patients, and got them to have online text-based consultations - both with AMIE and with one of 20 board-certified clinicians.