Indian and white in the Northwest : a history of Catholicity in Montana, 1831-1891 / by L.B. Palladino ; with an introduction by John B. Brondel.

http://www.archive.org/details/indianandwhite00palliala

Christianity and civilization in the South Pacific : the influence of missionaries upon European expansion in the Pacific during the nineteenth century

http://www.archive.org/details/christianityandc00younuoft

Across the prairie in a motor caravan; a 3,000 mile tour by two Englishwomen on behalf of religious education,

http://www.archive.org/details/acrosstheprairie00haseuoft

Wanted - Leaders! : a study of Negro development / Theodore DuBose Bratton.

http://www.archive.org/details/wantedleadersstu00bratrich

Canadian Baptists at work in India.

http://www.archive.org/details/canadianbaptists00orchuoft

Christian education in China : a study made by an educational commission representing the mission boards and societies conducting work in China.

http://www.archive.org/details/christianeducati008935mbp

China.

http://www.archive.org/details/handbooksonmissi01episuoft

Self-Organizing Hierarchical Knowledge Discovery by an ARTMAP Image Fusion System

Classifying novel terrain or objects front sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods described here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among objects are assumed to be unknown to the automated system or the human user. The ARTMAP information fusion system used distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierarchical knowledge structures. The system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships.