Scientific statistics and graphics on the Macintosh

The personal computer has become commonplace on the desk of most scientists. As hardware costs have plummeted, software capabilities have expanded enormously, permitting the scientist to examine extremely large datasets in novel ways. Advances in networking now permit rapid transfer of large datasets, which can often be used unchanged from one machine to the next. In spite of these significant advances, many scientists still use their personal computers only for word processing or e-mail, or as "dumb terminals". Many are simply unaware of the richness of software now available to statistically analyze and display scientific data in highly innovative ways. This paper presents several examples drawn from actual climate data analysis that illustrate some novel and practical features of several widely-used software packages for Macintosh computers.

Catalogue of EAFFRO scientific archives

Besides the formal publications held in the library (books, annual reports. Journals and reprints) a considerable quantity of unpublished Information on subjects relevant to freshwater fisheries in East Africa is held on various departmental files, etc.in Jinja. This material is extremely valuable: firstly because it is usually of immediate reference to current research work at EAFFRO, and secondly because it usually exists only as original material: no other copies are available elsewhere.

A survey of research and scientific services in East Africa, 1947-56

This "Survey of Research and Scientific Services in East Arica 1947-1956" has been prepared by Dr. E. B. Worthington, who held the post of Scientific Secretary in the Office of the Chief Secretary to the East African Governor's Conference and subsequently in the Administrator's Office of the East Mrica High Commission during the period January, 1947-May, 1951. Dr. Worthington is now Secretary General of the Scientific Council for, Arica South of the Sahara

Automated Computation of the Fundamental Matrix for Vision-Based Construction Site Applications

Estimating the fundamental matrix (F), to determine the epipolar geometry between a pair of images or video frames, is a basic step for a wide variety of vision-based functions used in construction operations, such as camera-pair calibration, automatic progress monitoring, and 3D reconstruction. Currently, robust methods (e.g., SIFT + normalized eight-point algorithm + RANSAC) are widely used in the construction community for this purpose. Although they can provide acceptable accuracy, the significant amount of required computational time impedes their adoption in real-time applications, especially video data analysis with many frames per second. Aiming to overcome this limitation, this paper presents and evaluates the accuracy of a solution to find F by combining the use of two speedy and consistent methods: SURF for the selection of a robust set of point correspondences and the normalized eight-point algorithm. This solution is tested extensively on construction site image pairs including changes in viewpoint, scale, illumination, rotation, and moving objects. The results demonstrate that this method can be used for real-time applications (5 image pairs per second with the resolution of 640 × 480) involving scenes of the built environment.