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Ektara [18,75] EKTARA de nes a full framework for Context-Aware Wearable and Ubiquitous Computing Applications The EKTARA framework consists of the following components: Context-Aware Integration Manager (CAIM) This provides a uniform framework for interaction between applications and the user The primary goal of the CAIM is to minimize the demands on the user's time and attention while maximizing the relevance of the information provided The CAIM aims to achieve this goal by taking into account the HCI resources currently available to the user, important contextual factors making the user's ability to pay attention to the UWC system, and the actions of the user's applications Further, the criteria by which the CAIM makes these decisions must be understandable and controllable by the user.

Retracted confessions: Legal, psychological and psychiatric aspects Medical Science Law, 28, 187 194..

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19 Zaino RJ, Kauderer J, Trimble CL, et al Reproducibility of the diagnosis of atypical endometrial hyperplasia: a Gynecologic Oncology Group study Cancer 2006;106:804 811 20 Trimble CL, Kauderer J, Zaino R, et al Concurrent endometrial carcinoma in women with a biopsy diagnosis of atypical endometrial hyperplasia: a Gynecologic Oncology Group study Cancer 2006;106:812 819 21 Zaino RJ, Kauderer J, Trimble CL, et al Reproducibility of the diagnosis of atypical endometrial hyperplasia Cancer 2006;106:804 811 22 Mutter GL, Baak JP, Crum CP, et al Endometrial precancer diagnosis by histopathology, clonal analysis, and computerized morphometry J Pathol 2000;190:462 469 23 Mutter GL Diagnosis of premalignant endometrial disease J Clin Pathol 2002;55:326 331 24 Mutter GL; the Endometrial Collaborative Group Endometrial intraepithelial neoplasia (EIN): will it bring order to chaos Gynecol Oncol 2000;76:287 290 25 Trimble CL, Kauderer J, Zaino RJ, et al.

Ideally the CAIM should implicitly learn the user's preferences over time yet still be able to provide the user with an explicit description of its decision model, which becomes part of the user's personal pro le, which is always accessible wherever she goes (eg, by being stored on her person in a wearable computer) Contextual Information Service (CIS) This is a distributed database service, which provides UWC applications and services a uniform means of storing and retrieving contextual information Clients may query a server for all records matching a context template or subscribe to receive records when matching information is posted or expires CIS Servers may register selected contexts of other servers, allowing clients to discover other members of the CIS federation.

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The CIS must support a range of context classi cations, including location, authorship, intended recipient of information, time of posting, time of relevance, time of expiry, deliverability (whether a record is ordinarily intended to be delivered once or multiple times), MIME document type, and an extensible mechanism to allow the uniform handling of unexpected or idiosyncratic contexts Perceptual Context Engine (PCE) This is a means of turning raw sensor data and information from other sources, such as a real-world description such as `Meeting in Espoo,' into symbolic context descriptions The PCE has a two-layer structure, with an inference system running over a perceptual context classi er system The Perceptual Context Classi er System (PCCS) is a signal-processing system, which converts the raw sensor data into a collection of probabilistic estimates.

Here 0 = 0, 0 > 0, i > 0, and i > 0 for i = 1, 2, 3, . . .. The rst and last conditions are boundary conditions. The differential equations for this process are derived using the Chapman Kolmogorov equations, P0j (t) = 0 P0j (t) + 0 Pij (t) Pij (t) = i Pi 1,j (t) ( i + i )Pij (t) + i Pi+1,j (t). (7.7) (7.8)

Conceptually, the classi er system allows the user to train event recognition functions, or classi ers, to recognize patterns in the sensory data and tag them as speci c events The mechanism by which this time-series recognition occurs is a multi-level HMM grammar that is capable of recognizing patterns over a range of timescales from seconds to days Inference System (IS) The job of the Inference System is to take the output of the classi cation system (and other sources of context such as a system clock or GPS.

of the interaction gate with two inputs and three outputs, that is, just one xy output instead of two. Such collision gate is shown in Figure 5.10. Rich dynamics of subexcitable Belousov-Zhabotinsky medium allows us also to implement complicated logical operations just in a single interaction event (see details in the work by Adamatzky et al. [5]).

Concurrent endometrial carcinoma in women with a biopsy diagnosis of atypical endometrial hyperplasia: a Gynecologic Oncology Group study Cancer 2006;106:812 819 26 Figueroa-Casas PR, Ettinger B, Delgado E, Javkin A, Vieder C Reversal by medical treatment of endometrial hyperplasia caused by estrogen replacement therapy Menopause 2001;8:420 423 27 Orbo A, Arnes M, Hancke C, Vereide AB, Pettersen I, Larsen K Treatment results of endometrial hyperplasia after prospective D-score classi cation A followup study comparing effect of LNG-IUD and oral progestins versus observation only Gynecol Oncol 2008 28 Ushijima K, Yahata H, Yoshikawa H, et al Multicenter phase II study of fertility-sparing treatment with medroxyprogesterone acetate for endometrial carcinoma and atypical hyperplasia in young women J Clin Oncol 2007;25:2798 2803 29 Cohen I Endometrial pathologies associated with postmenopausal tamoxifen treatment Gynecol Oncol 2004;94:256 266 30 Varma R, Sinha D, Gupta JK.

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