There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

The power of feedback.

The Visual Display of Quantitative Information

Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories Alternative teaching approaches are more inductive Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes

Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

Scalability has become an important consideration in parallel algorithm and machine designs. The word scalable, or scalability, has been widely and often used in the parallel processing community. However, there is no adequate, commonly accepted definition of scalability available. Scalabilities of computer systems and programs are difficult to quantify, evaluate, and compare. In this paper, scalability is formally defined for algorithm-machine combinations. A practical method is proposed to provide a quantitative measurement of the scalability. The relation between the newly proposed scalability and other existing parallel performance metrics is studied. A harmony between speedup and scalability has been observed. Theoretical results show that a large class of algorithm-machine combinations is scalable and the scalability can be predicted through premeasured machine parameters. Two algorithms have been studied on an nCUBE 2 multicomputer and on a MasPar MP-1 computer. These case studies have shown how scalabilities can be measured, computed, and predicted. Performance instrumentation and visualization tools also have been used and developed to understand the scalability related behavior. >

Scalability of parallel algorithm-machine combinations

Convolution is a fundamental operation in many signal and image processing applications. Since the computation and communication pattern in a convolution operation is regular, a number of special architectures have been designed and implemented for this operator. The Von Neumann architectures cannot meet the real-time requirements of applications that use convolution as an intermediate step. We combine the advantages of systolic algorithms with the low cost of developing application specific designs using field programmable gate arrays (FPGAs) to build a scalable convolver for use in computer vision systems. The performance of the systolic algorithm of (Kung et al., 1981) is compared theoretically and experimentally with many other convolution algorithms reported in the literature. The implementation of a convolution operation on Splash 2, an attached processor based on Xilinx 4010 FPGAs, is reported with impressive performance gains.

Convolution on Splash 2

PC-1D is a finite-element program for modeling semiconductor devices in one dimension on personal computers. It has the ability to address complex issues associated with heavy doping, high-level injection, and transients. Significant improvements have been made to the program, resulting in a new version. The authors describe the enhancements and their application to modern crystalline cells, including new provisions for heterostructures, antireflection coatings and light trapping, an upgraded user interface, and unattended operation for optimization studies. >

PC-1D version 2: enhanced numerical solar cell modelling

Several performance visualization tools have demonstrated that helpful insights into parallel performance can be gained through graphical displays. However, much of this work has been experimental, specialized, and ad hoc. Evolving performance visualization into an integral, productive tool for evaluating parallel performance requires a more systematic, formal methodology that relates behavior abstractions to visual representations in a more structured way. We propose a high-level abstract model for the performance visualization process, explain its relationship to the most important concepts and principles of effective visualization practice, and illustrate the relationship between these concepts and our abstract model through specific case studies. We also discuss the relationship of performance visualization to general scientific visualization. >

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The visual display of parallel performance data

As systems increase in complexity and technology advances, curriculum and laboratories are challenged to keep pace. This is especially true in computer engineering, which has seen dramatic growth in the scope and diversity of computer-based systems. One of the key challenges is developing the educational context for the new technologies, which are being encountered earlier and earlier in a student's program of study. Problem-based learning has been central to engineering education, and it is particularly relevant to the integration of new system design concepts and technologies into introductory courses. In this paper, we describe steps taken at Iowa State University to revitalize a sophomore level course in embedded systems by addressing the type and extent of problem-based learning used in the course. Our goal was to develop a more interesting and relevant integrated classroom/laboratory experience for the students. We present the revisions in terms of the "3C5I" model, which creates an educational context based on Concepts within Courses within a Curriculum (3C), and in each, progressing along the five "Is" of Introduction, Illustration, Instruction, Investigation, and Implementation. Problem-based learning may extend through to either Investigation or Implementation, and in each case, to differing degrees, depending on the scope of the problem. In the revised class, we use both, with a real-world theme guiding weekly labs that culminate as parts of a final project. We examine student learning and experiences with the thematic labs as well as the effects of several other changes such as competitive programming exercises and alternative evaluation methods.

Diane T. Rover

Papers

Scalability of parallel algorithm-machine combinations

Convolution on Splash 2

PC-1D version 2: enhanced numerical solar cell modelling

The visual display of parallel performance data

Problem-based learning in an introductory computer engineering course