Real-Time Indoor Movement Animation System In 3D Environment

In the era of smart homes, activities of daily living (ADLs) gains more and more attentions, ADLs can be used to present an individual’s living status, gauge an individual’s level of functioning and estimate his/her health condition. With smart devices, our daily motions can be captured and mapped into digital data, these raw data can be analyzed so that activities can be recognized. Although activities can be determined, they’re still represented as digital data, it would be boring, hard and time-consuming to read and understand such data. A system that could provide real-time monitoring and visualizing of an individual’s activities without privacy issue will be an urgent requirement for the non-technical, especially for nurses, doctors and family members, in order to observe people in need and in turn provide better nursing services. For this project, I present a real-time animation system for human movements in an 3D indoor environment with simultaneous tracking of an individual. This system collects and recognizes activities only through a smart phone and animates these movement behaviors in a 3D environment. The indoor activities are recognized by processing the data combination of magnetic field, acceleration and Wi-Fi signals. With this system, people can easily see the daily movement information of an individual and where that individual is located at a specific time. The purpose of this system is to provide a cost-effective and convenient healthcare service for people in need

Multi-labeled Relation Extraction with Attentive Capsule Network

To disclose overlapped multiple relations from a sentence still keeps challenging. Most current works in terms of neural models inconveniently assuming that each sentence is explicitly mapped to a relation label, cannot handle multiple relations properly as the overlapped features of the relations are either ignored or very difficult to identify. To tackle with the new issue, we propose a novel approach for multi-labeled relation extraction with capsule network which acts considerably better than current convolutional or recurrent net in identifying the highly overlapped relations within an individual sentence. To better cluster the features and precisely extract the relations, we further devise attention-based routing algorithm and sliding-margin loss function, and embed them into our capsule network. The experimental results show that the proposed approach can indeed extract the highly overlapped features and achieve significant performance improvement for relation extraction comparing to the state-of-the-art works.Comment: To be published in AAAI 201

Long term testing and analysis of dielectric samples under DC excitation

This paper details testing conducted under DC conditions on a dielectric sample containing internal voids. The DC testing was conducted using a ramp method to vary the voltage applied to the dielectric sample. The dielectric sample was de-energised for a week prior to two separate identical ramp tests and the results are presented showing the variability of PD activity. After the second ramp test an additional ramp test was performed in quick succession and PD activity was reduced, emphasizing the importance of de-energising the sample between tests. A major challenge associated with void type dielectric samples is ensuring that repeatable results are generated and possible approaches are discussed

PD activity in void type dielectric samples for varied DC polarity

This paper discusses the DC testing of a dielectric sample (with voids) under DC conditions. The ramp test method was employed to assess whether the tests were repeatable. Three DC ramp tests were performed in quick succession. The polarity of the first/third tests was positive and the polarity of the second test was negative. The resultant partial discharge activity was analyzed for each series of tests and compared for positive and negative conditions. The results show that the inclusion of a negative ramp between two positive ramps enabled similar PD activity to be recorded in the first and second positive ramp tests. The negative cycle was used to re-initialise the test sample and allows trapped charge to migrate enabling similar PD activity in the subsequent positive ramp test. Changes in PD behavior were observed in the distribution of PD data between the tests

Metabolome response to temperature-induced virulence gene expression in two genotypes of pathogenic Vibrio parahaemolyticus

Relative concentration of metabolites identified in Vibrio parahaemolyticus ATCC17802. (XLSX 113 kb)