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4 If the policies permit the user to have access to the requested data, a positive response is sent to the CP, otherwise the request is denied by sending a false noti cation 5 The CP checks the response given by the PEP and reacts accordingly If the response grants access, the CP gets the data from the Data Repository and sends it to the requester, else not 6253 Policy Management Privacy and trust policies are initialised and updated by the user on her local device The speci ed policies are then distributed to remote Context Providers that provide access to personal data of the user The policies can be distributed either by storing them on a policy server, or directly uploading them to the policy repositories of the CP Trust Engines.

The remotely stored policy sets are always uploaded from the local set, and user intervention is called for when a discrepancy between user and group policies is detected The latter modi cation of privacy policies is under the strict control of the initial Management and Rules Layer policies Changes to existing policies are possible only if the MRL policies allow the policies to be modi ed The message sequence chart in Figure 613 shows the interactions that take place at start-up when the Trust Engine is used for setting the policies for the user When the user has chosen her preferences, the GUI sends the data to the Policy Decision Point (User Trust Engine) that stores them in the Policy Repository for the userID in question Therefore, every userID has an own set of policies, which is uploaded appropriately to the relevant servers.

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These servers contain the policy repositories that the PEPs (the CP Trust Engines) check when evaluating access requests The set of relevant servers covers the user s mobile environment; it includes the locations where user data are stored and the groups that the user is a member of 626 Group Policies and Policy Enforcement In addition to the individual policies of the user, two types of privacy policies are used for managing the privacy settings for the mobile groups: Group Data Policies and Group Membership Policies..

The minimizing matrix is B = [VI,"" vn]. ll1ax{ det( B'AB) : B (mx n) real, B' B = In} == .\m ''\m-I ... .\m-nt I The maximizing matrix is B

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After clustering, the fuzzy rule base is constructed using a procedure similar to eTS, described in section 4.2. The cluster centers de ne the modal values of the Gaussian membership functions while dispersions are chosen to achieve appropriate levels or rule overlapping. Moreover, for each cluster found, the corresponding rules have their linear consequent function parameters adjusted using the recursive least-squares algorithm. The computational details are as follows. Let xk bxk ; xk ; . . . ; xk c 0; 1 p be the vector of observations and yk 2 0; 1 the 1 2 p i output of the ith rule, i 1; . . . ; ck , at k 1, 2,. . .. Each local model is estimated by a linear equation: Y k Xk g k where g k 2 Rp 1 is a vector of unknown parameters de ned by h i g k T g k g k g k . . . g k 0 1 2 p 4:11

Livestock Australia LTD, ABN 39 081 678 364 Final Report, Food Safety, PRMS 0 83 Available at http:// wwwmeatupdatecsiroau/new/Introduction%20 to%20Interventionshtm Accessed 23 December 2008 Morgan, A I, N Goldberg, E R Radewonuk, and O J Scullen 1996 Surface pasteurization of raw poultry meat by steam LWT-Food Science and Technology 29(5 6):447 451 Mullerat, J, B W Sheldon, and N A Klapes 1995 Inactivation of Salmonella species and other foodborne pathogens with SalmideR, a sodium chloritebased oxyhalogen disinfectant Journal of Food Protection 58(5):535 540 Naidu, A S 2001 Immobilized lactoferrin antimicrobial agents and the use US patent 6,172,040 B1 Naidu, A S 2002 Activated lactoferrin: A new approach to meat safety Food Technology 56(3):40 45 Naidu, A S, and W R Bidlack 1998 Milk lactoferrin natural microbial blocking agent (MBA) for food safety Environmental and Nutritional Interactions 2:35 50 Naidu, A S.

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