A5100682481- Context-Aware Activity Recognition Systems
- IoT and Edge/Fog Computing
- Anomaly Detection Techniques and Applications
- Human Pose and Action Recognition
- Energy Efficient Wireless Sensor Networks
- Human Mobility and Location-Based Analysis
- Data Management and Algorithms
- Time Series Analysis and Forecasting
- Mobile Crowdsensing and Crowdsourcing
- Privacy-Preserving Technologies in Data
- Modular Robots and Swarm Intelligence
- Neural dynamics and brain function
- Semantic Web and Ontologies
- Service-Oriented Architecture and Web Services
- Domain Adaptation and Few-Shot Learning
- Retinal Imaging and Analysis
- Opportunistic and Delay-Tolerant Networks
- Personal Information Management and User Behavior
- Gaze Tracking and Assistive Technology
- Speech and Audio Processing
- Computational Physics and Python Applications
- Mobile Agent-Based Network Management
- Privacy, Security, and Data Protection
- High Temperature Alloys and Creep
- Hand Gesture Recognition Systems
University of St Andrews
2014-2024
Second Affiliated Hospital of Zhejiang University
2018-2024
Lanzhou University
2023-2024
State Key Laboratory of Applied Organic Chemistry
2023
Center for Cancer Research
2022-2023
Zhejiang University
2023
Guangdong University of Technology
2022-2023
Northwestern Polytechnical University
2020
Hefei General Machinery Research Institute (China)
2012-2019
University of California, Irvine
2018
Abstract Pervasive computing is by its nature open and extensible, must integrate the information from a diverse range of sources. This leads to problem exchange, so sub-systems agree on shared representations. Ontologies potentially provide well-founded mechanism for representation exchange such structured information. A number ontologies have been developed specifically use in pervasive computing, none which appears cover adequately space concerns applicable application designers. We...
Social networks represent a sophisticated tool for accessing the preferences and properties of individuals groups. Thus, they potentially allow up-to-date, richly annotated contextual data to be acquired as side effect users' everyday use services. In this paper, we explore how such "social sensing" could integrated into pervasive systems. We frame survey possible approaches an integration, discuss open issues challenges facing researchers.
Autism is a lifelong developmental condition that affects how people perceive the world and interact with others.Challenges typical social engagement, common in autism experience, can have significant negative impact on quality of life individuals families living autism.Recent advances sensing, intelligent, interactive technologies enable new forms assistive augmentative to support interactions.However, researchers not yet demonstrated effectiveness these long-term real-world use.This paper...
The ability to identify the behavior of people in a home is at core Smart Home functionality. Such environments are equipped with sensors that unobtrusively capture information about occupants. Reasoning mechanisms transform technical,
Here we present the overall objectives and approach of SAPERE ("Self-aware Pervasive Service Ecosystems") project, focussed on development a highly-innovative nature-inspired framework, suited for decentralized deployment, execution, management, self-aware adaptive pervasive services in future network scenarios.
Recognising high-level human activities from low-level sensor data is a crucial driver for pervasive systems that wish to provide seamless and distraction-free support users engaged in normal activities. Research this area has grown alongside advances sensing communications, experiments have yielded traces coupled with ground truth annotations about the underlying environmental conditions user actions. Traditional machine learning had some success recognising activities; but need large...
Sensor-based human activity recognition (HAR) is having a significant impact in wide range of applications smart city, home, and personal healthcare. Such deployment HAR systems often faces the annotation-scarcity challenge; that is, most techniques, especially deep learning require large number training data while annotating sensor very time- effort-consuming. Unsupervised domain adaptation has been successfully applied to tackle this challenge, where knowledge from well-annotated can be...
Mobile gaze tracking involves inferring a user's point or direction on mobile device's screen from facial images captured by the front camera. While this technology inspires an increasing number of gaze-interaction applications, achieving consistent accuracy remains challenging due to dynamic user-device spatial relationships and varied motion conditions inherent in contexts. This paper provides empirical evidence how user mobility behaviour affect accuracy. We conduct two studies collecting...
Abstract Subretinal injection is a complicated task for retinal surgeons to operate manually. In this paper we demonstrate robust framework needle detection and localisation in robot‐assisted subretinal using microscope‐integrated Optical Coherence Tomography with deep learning. Five convolutional neural networks different architectures were evaluated. The main differences between the are amount of information they receive at input layer. When evaluated on ex‐vivo pig eyes, top performing...
Pervasive computing is typically highly sensor-driven, but sensors provide only evidence of fact rather than facts themselves.The uncertainty sensor data will affect each component in a pervasive system, which may decrease the quality its provided services.We general model to represent semantics different levels (e.g., sensor, lower-level context and higherlevel context).Within our model, fine-grained approaches are applied evaluate propagate uncertainties.They help resolve process...
Location is a core concept in most pervasive systems-and one that's surprisingly hard to deal with flexibly. Using location model supporting range of expressive representations for spaces, spatial relationships, and positioning systems, the authors constructed LOC8, programming framework exploring data's multifaceted uses. With developers can construct complex queries by combining basic additional contextual information.
Speech emotion recognition (SER) is an important part of affective computing and signal processing research areas. A number approaches, especially deep learning techniques, have achieved promising results on SER. However, there are still challenges in translating temporal dynamic changes emotions through speech. Spiking Neural Networks (SNN) demonstrated as a approach machine pattern tasks such handwriting facial expression recognition. In this paper, we investigate the use SNNs for SER more...