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25. Curtis Lavarello, Police in Schools: Improve Safety, Prevent School Violence, Quantico,
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Easily lost, wandering and dif culty dressing (spatial disorientation) Usually lacking in insight, facile Occasionally insight is intact, causing anxiety and depression Emotional lability may be present Socially or sexually inappropriate behaviour
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MARQ: Mobility Assisted Resolution of Queries MARQ [46] makes use of the mobile nodes to collect data from the sensor network. In MARQ, every node has contact with some of the other nodes. When contacts move around, they interact with other nodes and collect data. Nodes collaborate with their contacts to resolve the queries. SQTL: Sensor Query and Tasking Language Sensor query and tasking language (SQTL) [114] is proposed as an application layer protocol that provides a scripting language. SQTL supports three types of events, which are de ned by the keywords receive, every and expire. The receive keyword de nes events generated by a node when the node receives a message; the every keyword de nes events occurred periodically; and the expire keyword de nes the events occurred when a timer expires. If a node receives a message that is intended for it and contains a script, the node executes the script. SQS: SeMA Querying Protocol for Micro-Sensors
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26. Bureau of Justice Statistics, U.S. Department of Justice, Violence in the Workplace,
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There is an increasing interest in computer applications that are aware of the user's context. Currently these applications are normally handcrafted [53,56,58,90]. Many of them present information to users as they enter a given context [54], for example a tourist nearing a site within a city or a visitor moving round a building. Orr and Abowd [62] describe a system for identifying people based on their footstep ground reaction force (GRF) pro les and how its accuracy was tested against a large pool of footstep data. This oor system may be used to identify users transparently in their everyday living and working environments. They created user footstep models based on footstep pro le features and achieved a recognition rate of 93%. They mention that they planned to integrate the system into the Context Toolkit for live use. The Context Toolkit aims to ease the development of context-aware applications by providing a library of `context widgets' that free the application writer from the details of context sensing (i.e., interfacing with sensors). In the same way that GUI widgets insulate applications from certain interface presentation concerns, context widgets insulate applications from context acquisition concerns. The system consists of these context widgets and a distributed infrastructure that hosts and coordinates the widgets. In order to integrate the Smart Floor with the Context Toolkit, a software layer would have to output the calculated identity of the user (or perhaps the top three choices, along with a certainty score), providing a ready-to-use
The use of probability analysis, and especially Bayesian analysis, to evaluate evidence and the inferences to which the evidence leads, has been discussed sporadically for decades (Kaplan, 1968; Finkelstein and Fairley, 1970; Lempert, 1977; Kaye, 1988a; Robertson and Vignaux, 1995), and has become one of the centerpieces of the new evidence scholarship. Bayes theorem is a basic principle of logic that indicates how a rational evaluator should adjust a subjective probability assessment in light of new evidence. The process of reassessment in the light of new information can begin with the rst piece of evidence and continue in iterative fashion through to the last. Or it can describe the effect that any given piece of evidence should have on a fact nder s belief in alternative hypotheses. Bayes theorem is best understood as a statement regarding the logical consistency of beliefs. It is useful for identifying inconsistencies among the various beliefs a fact- nder might hold and for demonstrating the logical
Foundation Determinants of Risk Weights Probability of default (PD) Bank determines Loss in the event of default Supervisor (LGD) determines Exposure at default (EAD) Supervisor determines Maturity (M) Credit Risk Mitigation Collateral Credit derivatives Bank guarantees Calculation of Reg Capital Floor Advanced Bank determines Bank determines Bank determines Maturity adjustment incorporated
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