Three score and ten years of co-operative banking in Massachusetts /

Map on lining papers.

Co-operative farming.

Mode of access: Internet.

The co-operative news.

Description based on: Vol. 5, no. 1 (Jan. 1894); title from volume t.p.

The consumers' co-operative movement.

Mode of access: Internet.

International co-operative bulletin.

Mode of access: Internet.

Corporation laws of the state of Oregon relating to the organization and regulation of corporations and defining their powers and privileges ... Also, constitutional provisions: Blue Sky Law, Building and Loan Associations, Co-operative Associations, Agricultural Lime Act, Irrigation and drainage corporations, Religious, charitable and educational corporations and the 1911-1913-1915-1917 amendments of the legislature.

Mode of access: Internet.

Co-operative associa

Mode of access: Internet.

Report of the proceedings of the congress of the Co-operative League

Vols.1-2 issued by the league under its earlier name: Co-operative League of AMerica

The American reports ; containing all decisions of general interest decided in the courts of last resort of the several states [1869-1887]. / Extra annotated by the Editorial department of the Lawyers co-operative publishing company.

In the original edition, published in 1871-88, the notes and references for v. 1-27 were I. G. Thompson, and for v. 28-60 by Irving Browne.

Exploring tomorrow's agriculture; co-operative group farming, a pratical program of rural rehabilitation

Bibliographical foot-notes.

Development of a co-operative distributed process mining system for quality assurance

In this paper, a co-operative distributed process mining system (CDPMS) is developed to streamline the workflow along the supply chain in order to offer shorter delivery times, more flexibility and higher customer satisfaction with learning ability. The proposed system is equipped with the ‘distributed process mining’ feature which is used to discover the hidden relationships among each working decision in distributed manner. This method incorporates the concept of data mining and knowledge refinement into decision making process for ensuring ‘doing the right things’ within the workflow. An example of implementation is given, based on the case of slider manufacturer.

Mach Bands: multi-scale spatial filtering and co-operative coding of edges and bars

Perception of Mach bands may be explained by spatial filtering ('lateral inhibition') that can be approximated by 2nd derivative computation, and several alternative models have been proposed. To distinguish between them, we used a novel set of ‘generalised Gaussian’ images, in which the sharp ramp-plateau junction of the Mach ramp was replaced by smoother transitions. The images ranged from a slightly blurred Mach ramp to a Gaussian edge and beyond, and also included a sine-wave edge. The probability of seeing Mach Bands increased with the (relative) sharpness of the junction, but was largely independent of absolute spatial scale. These data did not fit the predictions of MIRAGE, nor 2nd derivative computation at a single fine scale. In experiment 2, observers used a cursor to mark features on the same set of images. Data on perceived position of Mach bands did not support the local energy model. Perceived width of Mach bands was poorly explained by a single-scale edge detection model, despite its previous success with Mach edges (Wallis & Georgeson, 2009, Vision Research, 49, 1886-1893). A more successful model used separate (odd and even) scale-space filtering for edges and bars, local peak detection to find candidate features, and the MAX operator to compare odd- and even-filter response maps (Georgeson, VSS 2006, Journal of Vision 6(6), 191a). Mach bands are seen when there is a local peak in the even-filter (bar) response map, AND that peak value exceeds corresponding responses in the odd-filter (edge) maps.