Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Psychological Perspectives on the Civil Liberties of Transgendered Inmates in a Prison Setting

As society becomes increasingly less binary, and moves towards a more spectrum based approach to mental illness, medical illness, and personality, it becomes necessary to address this shift within formerly rigid institutions. This paper explores this shift as it is occurring within correctional settings around the United States concerning the medical care, housing, and safety of transgendered inmates. As there is no legal standard for the housing or access to gender-affirming medical care (i.e., hormone therapy, sexual reassignment surgery), these issues are addressed on an institutional level, with very little consistency throughout the country. Currently, most institutions follow a genitalia-based system of classification. Within the system, core beliefs are held, some adaptive and some no longer adaptive, that drive the system's behavior and outcomes. With regard to transgendered inmates, several underlying beliefs within the system serve to maintain the status quo; however, the most basic underpinning is the system's reliance on a binary gender system. As views of humane treatment of the incarcerated expand and modernize, the role of mental health within corrections has also expanded. Psychologists, social workers, counselors, and psychiatrists are found in almost all correctional facilities, and have become a voice of advocacy for an often underserved population.

Onsite Wastewater Model Performance Code Implementation Plan

As the population of Colorado continues to grow, the impacts from individual sewage disposal systems, or onsite wastewater systems (OWS), are becoming more apparent. Increased use of OWS impacts not only water quality but land use and development as well. These impacts have led to the need for a new generation of wastewater regulations in the state, a transition from the historic prescriptive requirements to a more progressive, performance-based system. A performance-based system will allow smarter growth, improved water quality, and cost savings for both the regulatory agencies and the OWS industry in Colorado. This project outlines the challenges and essential elements required to make this transition, and provides guidance on how to meet the challenges and overcome barriers to implementing a performance code in Colorado.