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OBJECTIVE To determine the incidence of surgically managed pelvic organ prolapse and urinary incontinence in a population-based cohort, and to describe their clinical characteristics. METHODS Our retrospective cohort study included all patients undergoing surgical treatment for prolapse and incontinence during 1995; all were members of Kaiser Permanente(More)
Nineteen women who had an abdominal sacrocolpopexy (ASC) with synthetic mesh and 18 women who had an ASC with freeze-dried, irradiated cadaveric fascia lata returned for blinded pelvic organ prolapse quantification (POPQ) examinations. The mean relative vaginal descent (delta) from perfect total vaginal length in the mesh group was 1.1 (0.3) cm, and the(More)
This paper presents an automated system for generating a semantic map of inventory in a retail environment. Developing this map involves assigning a department label to each discrete section of shelving. We use a priori information to boost data from laser and camera sensors for object recognition and semantic labeling. We introduce a soft object map and a(More)
"', The l}SDA Forest Service manages vast tracts of publicly own6c;! land and .,.",lter resources across the United States, especially in the South and the West. The Forest and Rangeland Renewable Resources Planning Act of 1974 (RPA). as amended by the National Forest Management Act of 1976 (l\'F.vfA). was passed to make resource management by the 1:S(More)
– This paper presents a novel granular method of aggrega-tion. The method is suitable for use in simple resource-constrained sensor networks, in which full statistical estimation is not applicable. The method models the measurement uncertainty through the use of shadowed sets, and exploits the localised uncertainty within shadowed sets to provide improved(More)
This paper presents an automated robotic system for generating semantic maps of inventory in retail environments. In retail settings, semantic maps are labeled maps of stores where each discrete section of shelving is assigned a department label describing the types of products on that shelf. Starting from a metric map of the store, the robot autonomously(More)
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