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This is Volume I of a two-volume report of a study on the exchange and use of knowledge for school improvement in three paired educational systems in Boston, Massachusetts. The pairings, which involved the collaboration of a college/university with one or more of the Boston public schools, were among 26 such collaborative arrangements mandated by court order in 1975 as part of Boston's desegregation program. The pairs investigated were: (1) Harris University-Boston Public Schools District A; (2) Massachusetts College-District B; and (3) Dunfey University-District C. The study investigated the process of interorganizational collaboration on school improvement projects within each of the paired systems. Case studies of the systems investigated are contained in the second volume of this report. This volume explains the study purposes, defines key terms, and discusses the study approach. A conceptual model of the interorganizational process derived from the case studies is described, followed by an application of the model in cross case analysis. The report concludes that in varying degrees, knowledge was exchanged and used in the pairings primarily through face-to-face rather than written communication. Such knowledge exchange/use was found to be governed by the interaction of the systems' structural arrangements, history and environment, and the hierarchy of needs and resources. Details of cross-coding schemes, a bibliography, and a directory of similar collaboratives are included as appendices. (Author/MJL)

A preliminary report is presented on the work on the tracking of internal layers in a singularly-perturbed convection-diffusion equation. It is shown why such tracking may be desirable, and it is also shown how to do it using domain decomposition based on asymptotic analysis.

A constrained iterative image restoration method is applied to multichannel diffraction-limited imagery. This method is based on the Gerchberg-Papoulis algorithm utilizing incomplete information and partial constraints. The procedure is described using the orthogonal projection operators which project onto two prescribed subspaces iteratively. Its properties and limitations are presented. The effect of noise was investigated and a better understanding of the performance of the algorithm with noisy data has been achieved. The restoration scheme with the selection of appropriate constraints was applied to a practical problem. The 6.6, 10.7, 18, and 21 GHz satellite images obtained by the scanning multichannel microwave radiometer (SMMR), each having different spatial resolution, were restored to a common, high resolution (that of the 37 GHz channels) to demonstrate the effectiveness of the method. Both simulated data and real data were used in this study. The restored multichannel images may be utilized to retrieve rainfall distributions.

The constrained optimization problem for image restoration, utilizing incomplete information and partial constraints, is formulated using nonlinear proramming techniques. This method restores a distorted image by optimizing a chosen object function subject to available constraints. The penalty function method of nonlinear programming is used. Both linear or nonlinear object function, and linear or nonlinear constraint functions can be incorporated in the formulation. This formulation provides a generalized approach to solve constrained optimization problems for image restoration. Experiments using this scheme have been performed. The results are compared with those obtained from other restoration methods and the comparative study is presented.

A restoration of the 37, 21, 18, 10.7, and 6.6 GHz satellite imagery from the scanning multichannel microwave radiometer (SMMR) aboard Nimbus-7 to 22.2 km resolution is attempted using a deconvolution method based upon nonlinear programming. The images are deconvolved with and without the aid of prescribed constraints, which force the processed image to abide by partial a priori knowledge of the high-resolution result. The restored microwave imagery may be utilized to examined the distribution of precipitating liquid water in marine rain systems.

An overview is given on considerations involved in the computation of solution to problems involving several scales. Examples of problems with multiple scales are studied, showing that the presence of multiple scales in a physical system may be manifested in different ways which depend on the degree of interaction between the various scales. Numerical methods commonly used to solve problems with multiple scales discussed, and it is found that the effective methods are based on subspace projection.

A constrained iterative image restoration method is applied to multichannel diffraction-limited imagery. This method is based on the Gerchberg-Papoulis algorithm utilizing incomplete information and partial constraints. The procedure is described using the orthogonal projection operators which project onto two prescribed subspaces iteratively. Some of its properties and limitations are also presented. The selection of appropriate constraints was emphasized in a practical application. Multichannel microwave images, each having different spatial resolution, were restored to a common highest resolution to demonstrate the effectiveness of the method. Both noise-free and noisy images were used in this investigation.

A adaptive filtering method, the Windrow-Hoff algorithm, for enhancing multichannel signals against aditive noise was investigated. It removes noise for multichannel images containing correlated signal compoments but uncorrelated noise components. Its potential application is the enhancement of multichannel microwave satellite images as a preprocessing step for the extraction of geophysical parameters.

An automated technique is presented for designing effective decision tree classifiers predicated only on a priori class statistics. The procedure relies on linear feature extractions and Bayes table look-up decision rules. Associated error matrices are computed and utilized to provide an optimal design of the decision tree at each so-called 'node'. A by-product of this procedure is a simple algorithm for computing the global probability of correct classification assuming the statistical independence of the decision rules. Attention is given to a more precise definition of decision tree classification, the mathematical details on the technique for automated decision tree design, and an example of a simple application of the procedure using class statistics acquired from an actual Landsat scene.

Large antenna multi-channel microwave radiometer (LAMMR) software specifications were written for LAMMR ground processing. There is a need to determine more computationally-efficient antenna temperature correction methods in compensating side lobe contributions especially near continents, islands and weather fronts. One of the major conclusions was that the antenna pattern corrections (APC) processes did not accomplish the implied goals of compensating for the antenna side lobe influences on brightness temperature. A-priori knowledge of land/water locations was shown to be needed and had to be incorporated in a context sensitive APC process if the artifacts caused by land presence is to be avoided. The high temperatures in land regions can severely bias the lower ocean response.

The primary purpose of the World Surface Map is to provide the LAMMR subsystem with world surface type classifications that are used to set up LAMMR LEVEL II process control. This data base will be accessed solely by the LAMMR subsystem. The SCATT and ALT subsystems will access the data base indirectly through the T sub b (Brightness Temperature) Data Bank, where the surface types were updated from a priori to current classification, and where the surface types were organized on an orbital subtrack basis. The single most important factor in the design of the World Surface Maps is the ease of access to the information while the complexity of generating these maps is of lesser importance because their generation is a one-time, off-line process. The World Surface Map provides storage of information with a resolution of 7 km necessary to set flags concerning the earth's features with a different set of maps for each month of the year.

The purpose of the information adaptive system (IAS) study was to determine how some selected Earth resource applications may be processed onboard a spacecraft and to provide a detailed preliminary IAS design for these applications. Detailed investigations of a number of applications were conducted with regard to IAS and three were selected for further analysis. Areas of future research and development include algorithmic specifications, system design specifications, and IAS recommended time lines.