Search

Detecting change points sequentially in a streaming setting, especially when both the mean and the variance of the signal can change, is often a challenging task. A key difficulty in this context often involves setting an appropriate detection threshold, which for many standard change statistics may need to be tuned depending on the prechange and postchange distributions. This presents a challenge in a sequential change detection setting when a signal switches between multiple distributions. Unfortunately, change point detection schemes that use the log-likelihood ratio, such as cumulative sum (CUSUM) and the generalized log-likelihood ratio (GLR), are quick to react to changes but are not symmetric when both the mean and the variance of the signal change. This makes it difficult to set a single threshold to detect multiple change points sequentially in a streaming setting. We propose a modified version of CUSUM that we call data-adaptive symmetric CUSUM (DAS-CUSUM). The DAS-CUSUM procedure is symmetric for changes between distributions, making it suitable to set a single threshold to detect multiple change points sequentially in a streaming setting. We provide results that relate the expected detection delay and average run length for our proposed procedure when both prechange and postchange distributions are normally distributed. Experiments on simulated and real-world data show the utility of DAS-CUSUM. [ABSTRACT FROM AUTHOR]

Wheelchair users often experience prolonged periods of stationary sitting. Such periods are accompanied with increased loading of the ischial tuberosities. This can lead to the development of pressure ulcers which can cause complications such as sepsis. Periodic pressure offloading is recommended to reduce the onset of pressure ulcers. Experts recommend the periodic execution of different movements to provide the needed pressure offloading. Wheelchair users, however, might not remember to perform these recommended movements in terms of both quality and quantity. A system that can detect such movements could provide valuable feedback to both wheelchair users as well as clinicians. The objective of this study was to present and validate the WiSAT – a system for characterizing in-seat activity for wheelchair users. WiSAT is designed to detect two kinds of movements – weight shifts and in-seat movements. Weight shifts are movements that offload pressure on ischial tuberosities by 30% as compared to upright sitting and are maintained for 15 seconds. In-seat movements are shorter transient movements that involve either a change in the center of pressure on the sitting buttocks or a transient reduction in total load by 30%. This study validates the use of WiSAT in manual wheelchairs. WiSAT has a sensor mat which was inserted beneath a wheelchair cushion. Readings from these sensors were used by WiSAT algorithms to predict weight shifts and in-seat movements. These weight shifts and in-seat movements were validated against a high-resolution interface pressure mat in a dataset that resembles real-world usage. The proposed system achieved weight shift precision and recall scores of 81% and 80%, respectively, while in-seat movement scores were predicted with a mean absolute error of 22%. Results showed that WiSAT provides sufficient accuracy in characterizing in-seat activity in terms of weight shifts and in-seat movement. [ABSTRACT FROM AUTHOR]

In recent times, there is increasing consensus that the traditional Internet architecture needs to be evolved for it to sustain unstinted growth and innovation. A major reason for the perceived architectural ossification is the lack of the ability to program the network as a system. This situation has resulted partly from historical decisions in the original Internet design which emphasized decentralized network operations through colocated data and control planes on each network device. The situation for wireless networks is no different resulting in a lot of complexity and a plethora of largely incompatible wireless technologies. With traditional architectures providing limited support for programmability, there is a broad realization in the wireless community that future programmable wireless networks would require significant architectural innovations. In this paper, we will present an unified overview of the programmability solutions that have been proposed at the device and the network level. In particular, we will discuss software-defined radio (SDR), cognitive radio (CR), programmable MAC processor, and programmable routers as device-level programmability solutions, and software-defined networking (SDN), cognitive wireless networking (CWN), virtualizable wireless networking (VWN) and cloud-based wireless networking (CbWN) as network-level programmability solutions. We provide both a self-contained exposition of these topics as well as a broad survey of the application of these trends in modern wireless networks. [ABSTRACT FROM AUTHOR]