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Bose et al. described FACE, the rst memoryless single-path recovery mechanism with guaranteed delivery [13] in a unit-disk graph model of communication (assuming ideal medium-access control (MAC) layer and connectivity). The FACE algorithm is an improvement of the routing algorithm due to Kranakis et al. [4], which guaranteed delivery in connected geometric planar graphs. A geometric planar graph partitions the plane into faces bounded by the polygons made up of the edges of the graph, and the nodes are described by geographic positions. A geometric graph is said to be planar if there is no intersection between any two edges of the graph (see the graph depicted in Fig. 12.3, for example). The main idea of the FACE algorithm is to route a packet along the interiors of the faces intersected by the straight line connecting the source node S and destination D (see Fig. 12.3). Each face interior is traversed by applying the right-hand rule

Edelmann, R J (1985) Individual differences in embarrassment: Self-consciousness, self-monitoring, and embarrassability Personality and Individual Differences, 6, 223 230 Edwards, A L, & Klockars, A J (1981) Signi cant others and self-evaluation: Relationships between perceived and actual evaluations Personality and Social Psychology Bulletin, 7, 244 251 Ehrenreich, B, & English, E (1978) For her own good: 150 years of the experts advice to women New York: Doubleday Erikson, E H (1950) Childhood and society New York: Norton Erikson, E H (1968) Identity: Youth and crisis New York: Norton Exline, J J, & Lobel, M (1999) The perils of outperformance: Sensitivity about being the target of a threatening upward comparison Psychological Bulletin, 125, 307 337 Felson, R B (1989) Parents and the re ected appraisal process: A longitudinal analysis Journal of Personality and Social Psychology, 56, 965 971 Festinger, L (1954) A theory of social comparison processes.

Human Relations, 7, 117 140 Folkes, V S (1982) Communicating the reasons for social rejection Journal of Experimental Social Psychology, 18, 235 252 Fong, G T, & Markus, H (1982) Self-schemas and judgments about others Social Cognition, 1, 191 204 Frum, D (2000) How we got here: The 1970s, the decade that brought you modern life for better or worse New York: Basic Books Fukuyama, F (1999) The great disruption: Human nature and the reconstitution of social order New York: Free Press Garbarino, J (1999) Lost boys: Why our sons turn violent and how we can save them San Francisco: Jossey-Bass Gardner, W L, Pickett, C L, & Brewer, M B (2000) Social exclusion and selective memory: How the need to belong in uences memory for social events Personality and Social Psychology Bulletin, 26, 486 496 Gergen, K J (1973) Social psychology as history.

257 271 292

Journal of Personality and Social Psychology, 26, 309 320 Gilbert, D T, & Jones, E E (1986) Perceiver-induced constraint: Interpretations of self-generated reality Journal of Personality and Social Psychology, 50, 269 280 Goffman, E (1959) The presentation of self in everyday life New York: Anchor Books Harano, R M, Peck, R L, & McBride, R S (1975) The prediction of accident liability through biographical data and psychometric tests Journal of Safety Research, 7, 16 52 Harrington, D M, & McBride, R S (1970) Traf c violations by type, age, sex, and marital status Accident Analysis and Prevention, 2, 67 79 Higgins, E T, King, G A, & Mavin, G H (1982) Individual construct accessibility and subjective impressions and recall Journal of Personality and Social Psychology, 43, 35 47..

The Mobile Context Ontologies developed for this book have been validated against the language speci cation using the WonderWeb [33] OWL-Validator and common design aws have been avoided using the ontology test rules that have been integrated into Prot g Their e e consistency has been ensured by the fully automatic OWL DL inference engines Racer and Pellet Furthermore, the sublanguage (ie the DL complexity) used in each component ontology and the number of constructs used (ie its size) have been determined using the ontology editor SWOOP To ensure easy maintainability of the ontologies, particular naming conventions have been strictly followed The ontologies have been developed in an incremental way guided by the application scenarios (see the Appendix) At rst, the initial baseline Mobile Context Ontologies were de ned in the SHIF(D) fragment of OWL DL, consisting of six components covering most of the intended vocabulary.

A rst (naive) re nement of those ontologies resulted in considerable extensions by a factor of ve in size, adding detailed descriptions of the initial concepts, formulating additional vocabulary informed by vCard standard [110] and the FOAF (Friend-OfA-Friend) vocabulary, linking to standard ontologies like time-entry (a OWL DL variant of Time OWL as used in OWL-S), and adding three additional components The evaluation of these re ned ontologies revealed de cits in reasoning performance, mainly caused by the size of the extensional knowledge formulated and due to the use of modelling constructs known to be computationally expensive (such as nominals in combination with inverse roles) pushing the underlying logic to SHOIF(D).