The mobile ad hoc network (MANET) has become a popular technology in recent years. Due to most devices are battery powered, energy conservation is a critical issue in the MANET. To save energy and extend battery life, nodes should turn their radios off when they have no packet to send or receive. To achieve this, IEEE 802.11 defined a synchronous power saving mechanism (PSM) based on periodical beacon transmission. It allows devices to turn their radios off when no data has to be sent or received. However, the idle state is long because the device must remain awake during the entire beacon interval even though there is only a small amount of data packets to be sent. Although some PSMs have been proposed, they still suffer from a long idle state. In this paper, we propose a new power saving mechanism by dynamically adjusting the sleeping time based on the network traffic. Simulation results show that the proposed PSM outperforms other PSMs in energy goodput and lifetime.

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The diagnosis of obstructive sleep apnea (OSA) syndrome is overnight PSG (mutli-channel system). But it¡¦s hard to be popularized for the general population (about twenty channel signals). In recent decades, several researches were devoted to a replacement system with only one channel signal (oxyhemoglobin saturation). However, it¡¦s hard to match PSG system¡¦s report without EEG wake information. Consequently, two channels (oxyhemoglobin saturation and EEG) were used of this study to enhance the AHI (estimation index for sleep apnea) prediction performance. After surveying the most recent studies, this work proposes a new basleline removal technique for oxygen saturation signal (SpO2) by using median filter. It was proved this technique improves the diagnostic accuracy for OSA. Furthermore, it is also found that by removing the wake periods, diagnostic accuracy can be improved further. By counting the number of times that the desaturation level has dropped more than 2% for at least 3 seconds, the correlation coefficient between AHI and proposed feature is 0.9218. In addition, by removing the wake period, this correlation increases to 0.9425. By using this feature to classify patients with AHI value larger than 5, the proposed approach achieves 93.78% accuracy, 95.94% sensitivity, 78.87% specificity f. Such results demonstrate the feasibility of using single SpO2 channel system for OSA diagnosis.

A wireless sensor network can be used to track an object. Every sensor has limited energy and detecting range. In order to conserve energy, sensors may be put into sleeping mode. A sensor in the sleeping mode can not communicate with other sensors or detect objects. When the object moves to the sensing range of a sleeping sensor, a tracking error occurs. To minimize the tracking error subject to an constraint on energy consumption, we should determine the sleeping schedules of sensors based on the mobility pattern of the object. We propose determining the sleeping schedules based on the observation history of the moving object. We use computer simulation to justify the usage of the proposed approach.

Thesis (M.S. in Human Systems Integration)--Naval Postgraduate School, December 2009. / Thesis Advisor(s): Miller, Nita Lewis. Second Reader: McCauley, Michael E. "December 2009." Description based on title screen as viewed on January 26, 2010. Author(s) subject terms: Sleep Efficiency, Sleeping Surface, Acceleration, Motion Effects on Sleep, Actigraphy, Sleep Quality, Shipboard Sleep. Includes bibliographical references (p. 83-87). Also available in print.

Thesis (M.S. in Applied Science (Operations Research))--Naval Postgraduate School, June 2004. / Thesis advisor(s): Nita Lewis Miller. Includes bibliographical references (p. 103-107). Also available online.

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 65-75).

Thesis (M. D.)--University of Hong Kong, 2009. / Includes bibliographical references (leaves 168-215). Also available in print.

A higher prevalence of sleep problems and a few specific sleep-wake characteristics have been preliminarily found to be associated with pervasive developmental disorders (PDD). However, there is limited research that has examined multiple variables associated with sleep-wake characteristics and problems of children with PDD. This dissertation study assessed and examined the sleep-wake characteristics, sleep problems, and daytime problem behaviors of children with PDD aged three to fifteen years, and their caregivers’ sleep as well as contextual variables using data from the primary caregivers’ reports and recordings. This study confirmed several findings in the literature related to sleep-wake characteristics and sleep problems in children with both PDD and sleep problems. Although the relationship between sleep and daytime problem behaviors of the children was not found to be statistically correlated, the descriptive data indicated that some conditions such as illness or anxiety of the children negatively impacted their sleep and behaviors. In addition, the children participants with PDD and sleep problems tended to watch TV or to use computer/play video games before bedtime, in comparison to those with PDD but without sleep problems in this study. Moreover, a significant correlation between sleep of the caregivers and of their children was found in the group of children with PDD and sleep problems, but not in the other group of children with PDD but without sleep problems. Lastly, the results of this study showed that the children with diagnoses of PDD were 3.84 times more likely to have sleep problems than those with diagnoses of Asperger’s Disorder (AD) or PDD not otherwise specified (PDD-NOS). These findings are discussed in light of the similarities and differences between the current study and previous literature, and with respect to the implications for practice and research in the field of PDD and sleep. / text

published_or_final_version / Medical Sciences / Master / Master of Medical Sciences