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Article
Federated few-shot learning for cough classification with edge devices
Automatically classifying cough sounds is one of the most critical tasks for the diagnosis and treatment of respiratory diseases. However, collecting a huge amount of labeled cough dataset is challenging mainl...
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Chapter and Conference Paper
Towards a New Multi-tasking Learning Approach for Human Fall Detection
Many fall detection systems are being used to provide real-time responses to fall occurrences. Automated fall detection is challenging because it requires near perfect accuracy to be clinically acceptable. Rec...
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Chapter
Multi-layered Monitoring for Virtual Machines
This chapter describes monitoring methods to achieve both security and reliability in virtualized computer systems. We show how to perform continuous monitoring and leverage information across different layers...
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Article
Masked face recognition with convolutional neural networks and local binary patterns
Face recognition is one of the most common biometric authentication methods as its feasibility while convenient use. Recently, the COVID-19 pandemic is dramatically spreading throughout the world, which seriou...
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Chapter and Conference Paper
Combined Local and Global Features for Action Recognition from Motion Sensors
Hand gestures are becoming one of the most convenient means of communication between human and machine. In this paper, we propose a method for hand gesture recognition using wearable motion sensors. The method...
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Article
Open AccessSelf-controlling photonic-on-chip networks with deep reinforcement learning
We present a novel photonic chip design for high bandwidth four-degree optical switches that support high-dimensional switching mechanisms with low insertion loss and low crosstalk in a low power consumption l...
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Article
Combining skeleton and accelerometer data for human fine-grained activity recognition and abnormal behaviour detection with deep temporal convolutional networks
Single sensing modality is widely adopted for human activity recognition (HAR) for decades and it has made a significant stride. However, it often suffers from challenges such as noises, obstacles, or dropped ...
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Article
Open AccessAstrocytes respond to a neurotoxic Aβ fragment with state-dependent Ca2+ alteration and multiphasic transmitter release
Excessive amounts of amyloid β (Aβ) peptide have been suggested to dysregulate synaptic transmission in Alzheimer’s disease (AD). As a major type of glial cell in the mammalian brain, astrocytes regulate neuro...
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Article
Incremental Learning for Autonomous Navigation of Mobile Robots based on Deep Reinforcement Learning
This paper presents an incremental learning method and system for autonomous robot navigation. The range finder laser sensor and online deep reinforcement learning are utilized for generating the navigation po...
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Article
Health-related quality of life and recovery patterns among hospitalised injury patients in Vietnam
To measure post-injury health-related quality of life (HRQoL) among hospitalised injury patients following discharge and to identify factor associated with lower HRQoL over time.
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Chapter and Conference Paper
Traffic Incident Recognition Using Empirical Deep Convolutional Neural Networks Model
Traffic incident detection plays an important role for a broad range of intelligent transport systems and applications such as driver- assistant, accident warning, and traffic data analysis. The primary goal o...
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Chapter and Conference Paper
An Orientation Histogram Based Approach for Fall Detection Using Wearable Sensors
Histogram features are extracted by calculating the distribution of orientations of small fragments or quanta of sliding windows on the sensors continuously acceleration data stream. Bins of the histogram is a...
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Chapter and Conference Paper
MobiCough: Real-Time Cough Detection and Monitoring Using Low-Cost Mobile Devices
In this paper we present MobiCough, a method and system for cough detection and monitoring on low-cost mobile devices in real-time. MobiCough utilizes the acoustic data stream captured from a wirelessly low-co...
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Chapter and Conference Paper
Motion Primitive Forests for Human Activity Recognition Using Wearable Sensors
Human activity recognition is important in many applications such as fitness logging, pervasive healthcare, near-emergency warning, and social networking. Using body-worn sensors, these applications detect act...
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Chapter and Conference Paper
SigVer3D: Accelerometer Based Verification of 3-D Signatures on Mobile Devices
We present SigVer3D – a convenient authentication method for users of mobile devices with built-in accelerometers. The method works by analyzing streams of signals returned by a mobile device’s accelerometer w...
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Chapter and Conference Paper
Real-Time Fall Detection and Activity Recognition Using Low-Cost Wearable Sensors
We present a real-time fall detection and activity recognition system (FDAR) that can be easily deployed using Wii Remotes worn on human body. Features extracted from continuous accelerometer data streams are ...
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Chapter
Activity Recognition and Healthier Food Preparation
Obesity is an increasing problem for modern societies, which implies enormous financial burdens for public health-care systems. There is growing evidence that a lack of cooking and food preparation skills is a...
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Chapter and Conference Paper
A Dynamic Time War** Approach to Real-Time Activity Recognition for Food Preparation
We present a dynamic time war** based activity recognition system for the analysis of low-level food preparation activities. Accelerometers embedded into kitchen utensils provide continuous sensor data strea...
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Chapter and Conference Paper
Slice&Dice: Recognizing Food Preparation Activities Using Embedded Accelerometers
Within the context of an endeavor to provide situated support for people with cognitive impairments in the kitchen, we developed and evaluated classifiers for recognizing 11 actions involved in food preparatio...
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Chapter and Conference Paper
PUB-2-SUB: A Content-Based Publish/Subscribe Framework for Cooperative P2P Networks
This paper is focused on the content-based publish/subscribe service and our problem is to devise an efficient mechanism that enables this service in any given P2P network of cooperative nodes. Most techniques...
