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This graphics extension uses a preprocessor which converts graphics commands into calls to a lower level graphics package. The preprocessor converts the source code containing the extended statements into a Fortran program. The objective is to generate contour plots or graphs with minimum effort by statements such as PLOT(U) or PLOT((X, Y)). In these cases, we are using the default options to specify scaling, coordinate labels, headings, etc. The user may override these default options at the expense of a more complex statement. Use of a preprocessor allows considerable freedom in the syntax.

A general approach to the problem is suggested. Using optical contrast as a general characteristic it is shown how objects are identified as such before their structure is analysed. Perception is regarded as a preprocessing phase for pattern recognition, in which essential information is abstracted from an optical image. A focusing device enables the suggested system to analyse the shape of objects in detail.

In this paper, a new technique for recognizing objects in digitized gray-level pictures is presented. It may be interpreted as a simplified and thus more restricted version of a previously presented "semantic" paradigm. Its simplicity and power, however, warrant its being treated as an interesting technique on its own. The new technique is based on (1) the use of preprocessing procedures for determining the existence of "primitive" properties and relations which hold for or between objects in a picture; (2) the succinct and explicit representation, in the form of "rules of inference", of the relational structure of the objects or scenes to be analyzed; and (3) the unique application of the rules to a sequence of thresholded versions of the input picture. The power of the technique is illustrated in the successful recognition of facial features in pictures of faces of people.

A microcomputer system is described which serves as a preprocessor/postprocessor for analog signals which are processed by a minicomputer. Both hardware and software characteristics are discussed.

A description is given of an analogue preprocessor designed to supply outputs corresponding to the systolic, diastolic, pulse and mean pressures of an arterial blood-pressure waveform obtained from a blood-pressure transducer. These can be fed, under program control, to an associated digital computer system. An indication of any pulse deficit present is also provided.

In the high data rate systems (> MHz) associated with signal processing, a standard stored program computer is not fast enough. At the present time, parallel (1, 2) and pipeline (3) architectures are being used to solve these computational problems.This paper describes a preprocessor which is optimized to perform sum-of-product operations with a "pipeline ripple through" architecture. A breadboard built to perform the "absolute difference" and "product" correlation functions using this architecture is described.

In pattern recognition, the raw data and dimensionality of the measurement space is usually very large. Therefore, some form of dimensionality reduction has been commonly considered as a practical preprocessing method for feature selection. Based on a method that increases the variance while maintaining local structure, a technique is developed to determine intrinsic dimensionality. A cost function is introduced to guide the maintenance of the rank order and therefore local structure. Two criteria of using the cost function to increase the variance have been introduced. Several methods of defining the local regions are suggested. A program is implemented and tested to find the intrinsic dimensionality of a variety of experimental data.

It is generally a problem to select the appropriate preprocessing and feature-extraction technique in most pictorial pattern recognition applications so that an accurate classification is possible. In this paper a class of pictures of medical importance, namely, chest X-ray pictures, is used to test the proposed preprocessing and feature-extraction technique. The technique presented in this paper is applied only to chest X-ray images; however, the same technique could also be applied to a fairly broad class of picture patterns with only some minor modifications. The proposed preprocessing technique, which utilizes the local and global information of the picture patterns, is to extract the lung boundary. The lung field is then enclosed by a polygon which is the piecewise linear approximation of the lung boundary. The set of texture features, which are the average of some local property measures, is has then extracted in this approximated lung area. The proposed technique been tested on two sets of X-ray picture classes?one with abnormalities caused by a known disease and the others with abnormalities caused by some unkown effects in the lung region. The classification results presented in this paper show the feasibility of the proposed pictorial pattern recognition system in effectively screening out the abnormal pictures without human intervention.

In this paper a review of the approaches to modelling adopted by programming languages currently available for discrete-system simulation leads to a close look at some of the advantages of languages which employ an "activity scan." These advantages include faster run-times for highly interrelated systems, simpler event routines, and increased security for the model. Decision tables provide a clear and concise format for specifying a complex set of conditions and the various consequent courses of action. They are therefore ideal for describing the conditions for interaction between component parts of a model as specified in the user-defined event routines. A preprocessor to make decision tables computer- readable would greatly enhance the process of modeZ ling and would allow a considerable extension of the range of conditioned statements to be used in the condition stubs of the table. A decision-table facility would form a useful extension to the many event-oriented simulation programming languages.

Sternberg has suggested that a possible way of achieving identification of degraded stimuli would be to execute “preprocessing” operations prior to recognition. Such operations would have some parallels with the “filtering” operations, suggested by Broadbent and others, for perceptual selection and attention. But when trying, in this paper, to consider how such operations could be implemented, some rather non-trivial problems emerge. Experimentally, these doubts find support in visual selection tasks of quite general character, in that filtering does not appear to take place. It seems, however, that these problems may be successfully overcome by some simple, though implicative, conceptual changes. The main implication is that effective focal attention is rather likely to be achieved through a process that is best described as “context-sensitive” selection.

Factor selection and preprocessing are important aspects of optimization studies. When simplex optimization is used, as many factors as can be handled conveniently should be included in the optimization; additional factors do not greatly increase the number of experiments required to reach the optimum. If the risk associated with poor response is minimal, a large initial simplex will provide information about a larger volume of the factor space. It is unnecessary to assign to each of the factors a step size that is inversely proportional to the factor's significance. The vertices of the initial simplex can be easily calculated by a minor modification of a published algorithm.

J. M. Foster (1968) has described a program called SID (Syntax Improving Device) which can take in a syntax rule set containing embedded actions, automatically produce an equivalent one-track form, and then output a syntax analyser to run on a given object machine. The form of the analyser is ideally a code program which checks the syntactic legality of the input data and arranges the calling of embedded actions as and when required; it does not produce a formal parsing of the input data, although the actions could be programmed to perform this function. SID has proved to be a valuable aid in compiler writing over a wide range of practical applications, extending from simple assembly languages through to quite complicated high level languages (Currie and Griffiths, 1967). The work described in this paper is based on a program called SAG (Syntax Analyser Generator, Simpson, 1968). SAG and SID require similar forms of input data and can produce similar forms of output analyser. However, SAG does not undertake automatic rule transformation; instead it checks the syntax for one-track properties and outputs data to assist in the process of manual transformation into an equivalent one-track set. SAG is a simpler program than SID and can be quickly and easily implemented on quite small computers with limited software facilities. Nonetheless it provides a powerful and flexible aid, particularly when writing compilers to a given specification. Early versions of SAG produced syntax analyser programs in code which were identical in form to analysers produced by SID. However, for certain machines, this led to a rather lengthy analyser, and so an alternative interpretive form of output was developed. In this case SAG produces data which can be operated on by a simple interpreter program. The resulting analyser can be made extremely compact with very little penalty in terms of running time. This paper concerns itself entirely with the interpretive form. The principal elements of the technique are illustrated in Fig. 1. Syntax rules containing actions are processed by SAG; SAG may reject the results if they do not correspond to an acceptable one-track form. If the rules are one-track, then SAG produces a data set which can be operated on by a simple interpreter program. This data set represents a close-packed form of the rules, and includes additional information to assist in the process of syntax analysis. The data set and the interpreter program together form a syntax analyser which can operate on basic symbols generated by a preprocessor. The preprocessor derives the basic symbols from the syntactic content of the input data. The analyser matches the basic symbols against the data set representing the syntax rules and generates a stream of action calls. These action calls control the sequence and timing of the actions which must be programmed to effect the required transformation between input and output. The actions may require value data associated with the input; the preprocessor derives this value data from the semantic content of the input. Also the actions may need global workspace for intercommunication purposes and the storage of intermediate results. This is a very condensed summary of the technique; the various component parts are fully discussed in the paper and a number of examples illustrate how the method might be used in practice. This paper shows how syntax directed techniques can be applied in a direct and straightforward manner. The content of the paper covers four main areas

A system for mathematically identifying unknown nonlinear systems based upon Wiener kernels and G-functionals is presented as an example of the sophisticated analyses of electrophysiological and behavioral data made possible by the introduction of powerful digital computers to the laboratory environment. The applicability of these methods to a wide variety of systems is emphasized. By measuring the response of the unknown system to appropriate white noise stimulation, data may be obtained which are sufficient for the characterization of the system under test. The only restrictions upon the unknown system is that it be approximately stationary during the period of measurement and that its output depend upon its input in the finite past. Various pretests to evaluate the applicability of the method are presented. Simple FORTRAN programs that clarify the methods of computation are given for the preprocessing of data, the analysis of lower-order kernels, the synthesis of system response from the computed kernels, and the computation of the proportion of the variance in the systems output which is accounted for by the kernels zero, one, and two. These programs may be implemented on a digital laboratory computer of moderate size. Analysis may be performed either on-line or after data collection, depending upon the temporal characteristics of the system under test. This method represents one of the few analytical techniques presently available for the characterization of both linear and nonlinear systems. For this reason, it constitutes a uniquely powerful tool for many branches of psychology. Successful applications of this method to electrophysiological and behavioral data are mentioned. Limiting factors in the use of Wiener kernel analysis are also discussed.

An implementation of interrupt handling facilities for LISP is described. Although simple and straightforward, the inclusion of these facilities into the language has been neglected. Thus LISP remains a second-generation language. The incorporation of PL/1-like on-conditions allows the user much greater control over the action of the LISP program, and enables him to trap conditions in data that would otherwise terminate the processor.

A laboratory-developed analog signal processor, driven by a conventional polygraph recorder and associated signal conditioning devices, provides automatic heart beat-by-heart beat preprocessing of various cardiovascular functions for input to a laboratory-type minicomputer. The technique of preprocessing individual functions, integrated with the minicomputer system which includes an A/D converter and teletype as input-output peripherals, provides a low-cost data acquisition and reduction system for the on-line computation and analysis of cardiovascular functions in experimental research applications. Such preprocessing more efficiently uses the minicomputer's memory to handle large amounts of information since the digitized data is in the form of one data sample, per function, per heart beat. Preprocessing analog data provides a low density data format and simplified software programs that are ideally suited for the utilization of a minicomputer in this on-line application.

A major problem in picture processing is to detect all the contrast boundaries (or edges) in a picture, independently of the particular gray levels involved. Several edge detection methods are described. The boundary elements detected by these methods are characterized by directions in order to speed up nonsystematic search algorithms. Since the detected boundaries tend to be broad bands, a thinning procedure, based on a local distance transformation, has been developed. Finally, the results of a search algorithm which makes use of the direction information are presented.

In this paper, an improved strategy for automated text based speaker identification scheme has been proposed. The identification process incorporates the Hidden Markov Model technique. After preprocessing the speech, HMM is used in the learning and identification. Features are extracted by different techniques such as RCC, MFCC, ΔMFCC, ΔΔMFCC, LPC and LPCC which is almost different in each case. The highest identification rate of 93% has been achieved in the close set text dependent speaker identification system. Keywords: Biometric Technologies; Automatic Speaker Identification; Cepstral Coefficients; Feature Extraction; Hidden Markov Model. DOI: http://dx.doi.org/10.3329/diujst.v6i2.9341 DIUJST 2011; 6(2): 14-21

The fastest parallel and pipeline computers presently being designed use interleaved memory systems with more than 16 individual memory units. A common difficulty in these machines is the alignment of data before it is arithmetically processed. Usually the arithmetic unit is used to preprocess the data. This may increase the computation time by a factor of two or more. This paper proposes a programmed memory preprocessing system which aligns the data before it is passed to the arithmetic processor.

In this paper, a multistage linear programming method of pattern recognition is proposed. The usual n-dimensional linear program has been split up into n stages of a one-dimensional linear program in such a way that more and more patterns belonging to two classes A and B are correctly classified as we proceed to higher and higher stages. It has been shown that if the threshold is kept fixed for ali the stages, the formulation of the problem entails a preprocessing of the feature coordinates; on the other hand, if the threshold is allowed to be different values in different stages, no such preprocessing is required. The application of the proposed method for the recognition of two handwritten Bengali characters has been discussed and compared with the results of other methods.

The circuitry is presented for an analogue preprocessor to measure R-R intervals and R wave widths from an analogue e.c.g. signal in conjunction with a digital computer. The circuit will handle both positive- and negative-going R waves, and will cope with e.c.g. baseline shifts due to respiration. Examples are given of the use of the preprocessor and its associated computer programs.

Electrocardiograms were placed on magnetic tape or transmitted over telephone wires to a 1401 computer using a data gathering console developed especially for the task. An analog preprocessor was used to select certain points on the waveform as particularly valuable for analysis by the computer. Novel electronic techniques were developed to compensate for tape recorder “wow” and “flutter.” This paper describes the system and special equipment.

When it was first formulated in 1960, (1) the programming language LISP was a truly machine independent language. However, even the earliest computer implementation encountered problems in input-output control and the handling of free variables which were not considered in the original paper. Successive implementations of LISP on more sophisticated machines have solved such problems by independent methods and introduced extensions of the language peculiar to those machines. Consequently, a LISP user now faces considerable difficulty in moving a program from one machine to another and is often involved in weeks of debugging in the process. As a possible solution to this problem, this paper is an attempt to provide a uniform subset of LISP 1.5 and its variants as it exists today. The version of LISP described, which we call Standard LISP, is sufficiently restricted in form so that programs written in it can run under any LISP system upwardly compatible with LISP 1.5 as described in the LISP 1.5 Programmer's Manual (2). As function names vary from system to system and input-output control is different, some modification of the code is of course necessary before function definitions can be successfully compiled in any given system. However, this modification is performed automatically by a preprocessor, whloh is custom built for a particular system. This preprocessor is a LISP program which is loaded before any Standard LISP programs are run, and could be built automatically into a system if only Standard LISP programs are run. Parts of this preprocessor are similar for all systems, but some of it is peculiar to a given implementation. Standard LISP preprocessors have been written for SHARE LISP for the IBM 7090 series machines, Stanford LISP/360 for IBM System 360 machines, Stanford AI LISP 1.6 for the PDP-6 and PDP-10, BBN-LISP for the SDS 940 and Texas LISP for the CDC 6600. For convenience in exposition we shall refer to the first four systems as SHARE LISP, LISP/360, PDP LIST and BBN-LISP respectively.

A version of the Logic Theory Machine of Newell, Shaw and Simon was written in LISP 1.5 on an IBM-7094. The program provides an experimental model for form-map, a method of information storage and retrieval particularly suited for list structures. The program was able to prove 17 out of 20 theorems from Principia Mathematica in 21.5 seconds.

This report describes the program for utilizing a small hybrid computing system to process coronary arterial flow and pressure signals obtained from chronically instrumented, conscious animals and discusses the advantages and disadvantages of the hybrid approach. Extensive analog preprocessing using parallel logic facilitates formation of data during the experiment and minimizes later editing. Moreover, it allows the digital portion of the program to be much smaller and more general than similar applications using only digital systems. Final output consists of an ink-jet recording of the analog signals, a printout of the digital results, and CalComp plots.

Detab/65, which was distributed by the ACM, is a decision table preprocessor written in second-generation Cobol (Cobol-61). This paper indicates the history of decision tables, reviews their structure, advantages and disadvantages, and presents the modifications to Detab/65 that are needed to allow its compilation by Cobol-65 or ANS Cobol.

In this paper it is tried to find a mathematical model for a number of mainly electrophysiological results concerning pattern recognition of mammals. The interpretations are essentially based on the experiments of Hubel and Wiesel in the visual system of the cat and the monkey. After a short introduction to the applied theory of linear nervous nets the investigations in the retina are interpreted. This part of the visual system can be considered as a bandpass-filter for space dependent oscillations. At the level of the geniculate body, a further filtering takes place which especially attenuates the low and the very high frequencies. The processes in the cortex regions 17, 18 and 19, where the further preprocessing of the pattern recognition takes place, can be interpreted by the theory of matched filters. In Area 17 the input pattern is reduced to the contour lines. In the two other areas the extraction of simple characteristic features such as line ends and corners takes place. By means of the present results it is not possible to draw complete conclusions on the structure of the recognition process.

Design of a language (PDELAN) to assist the programming of finite difference approximations to partial differential equations is described. A key part of the language is the representation of finite difference operators. The language is an extension of FORTRAN and is implemented as a preprocessor to a FORTRAN compiler.

This paper reviews some of the techniques which can be used to automatically classify and describe pictorial patterns. It discusses representative “preprocessing” and “property measurement” methods, with emphasis on methods which may be useful in processing biomedical pictures. (The decision-making aspect of pattern recognition is not discussed.) Techniques for subdividing pictures into regions, and measuring geometrical properties of such regions, are also considered. The paper is intended to serve as an introduction to the extensive literature in this field; it includes numerous references to this literature.

APAREL is described: this language is an extension to an algorithmic language (PL/I) that provides the pattern-matching capabilities normally found only in special purpose languages such as SNOBOL4 and TMG. This capability is provided through parse-requests stated in a BNF-like format. These parse-requests form their own programming language with special sequencing rules. Upon successfully completing a parse-request, an associated piece of PL/I code is executed. This code has available for use, as normal PL/I strings, the various pieces (at all levels) of the parse. It also has available, as normal PL/I variables, the information concerning which of the various alternatives were successful. Convenient facilities for multiple input-output streams, the initiation of sequences of parse-requests as a subroutine, and parse-time semantic checks are also included. APAREL has proven convenient in building a powerful SYNTAX and FUNCTION macro system, an algebraic language preprocessor debugging system, an on-line command parser, a translator for Dataless Programming, and as a general string manipulator.

This paper describes the implementation of a pedagogical version of Evalquote with a set of Fortran subroutines. Their study enables the user to understand the programming machinery needed to interpret Lisp programs; the implementation of the subroutines allows him to run pure Lisp in machines for which only Fortran is available. The approach used in this paper is to define a stack-machine capable of executing a sequence of pseudo-instructions which represent a Lisp program in post-fixed notation. These instructions are easily simulated by Fortran subroutines. Once the subroutines are implemented in a computer it is a simple matter to manually transcribe Evalquote into a sequence of these pseudo-instructions and thus obtain a Lisp interpreter with a minimum of programming effort. The paper does not attempt to describe a complete and efficient Lisp interpreter; instead, it concentrates on the description of a minimal set of pseudo-instructions and their actions.

The dead time of a channel plate has been regarded so far as an inevitable defect in many applications; however, it is pointed out in this paper that it can be considered as the memory time during which the input image is stored. Line drawing, moving object detection, and inversion of images were performed by an experimental preprocessor using the dead time characteristics. The device should be recognized as a two‐dimensional operator with no scanning and without an electronic computer. The features of the device are very high‐speed operation and high sensitivity for dark images.

CAI course authors have been faced with the distinct problem of having to learn an instructional coding language before they can get their courses into the computer. A system has been devised so that an author may easily write his course in English on course planning forms and then a preprocessor will generate the coding which will be input for the machine assembler.

This paper describes the common control subsystem of the No. 1 electronic automatic exchange (EAX) switch. The data-processing unit is a high-speed interrupt-driven general-purpose computer. It is broken down into its component parts of control, memories, communication channels, and input/output and its functions are described. The register-sender, a hard-wired preprocessor that handles both incoming and outgoing signaling for the switch is described, together with its relationship with the space-divided junctor circuits. The level of redundancy and its effect on the system structure and organization are described and discussed.

Digital preprocessors can ease the increasing data collection demands placed on real-time computers in patient monitoring. This paper describes a preprocessor that detects in real time an electrocardiogram QRS complex and computes the R-R interval. Detection is performed using multiple digital differentiation, which is encouraging as an ultrareliable means for locating the QRS. Inherent in the technique is a dependable control that can automatically compensate for signal-level variations. Clinical data demonstrate that detection is insensitive to low- and high-frequency noise, from baseline drift to muscle artifact and cautery bursts. The device can be connected directly to a patient, whose safety is guaranteed by optoelectronic isolation and interelectrode current limiting. Preprocessor operation has been human-engineered to a simple on/off procedure.

A feasible pavement crack detection system plays an important role in evaluating the road condition and providing the necessary road maintenance. In this paper, a back propagation neural network (BPNN) is used to recognize pavement cracks from images. To improve the recognition accuracy of the BPNN, a complete framework of image processing is proposed including image preprocessing and crack information extraction. In this framework, the redundant image information is reduced as much as possible and two sets of feature parameters are constructed to classify the crack images. Then a BPNN is adopted to distinguish pavement images between linear and alligator cracks to acquire high recognition accuracy. Besides, the linear cracks can be further classified into transversal and longitudinal cracks according to the direction angle. Finally, the proposed method is evaluated on the data of 400 pavement images obtained by the Automatic Road Analyzer (ARAN) in Northern China and the results show that the proposed method seems to be a powerful tool for pavement crack recognition. The rates of correct classification for alligator, transversal and longitudinal cracks are 97.5%, 100% and 88.0%, respectively. Compared to some previous studies, the method proposed in this paper is effective for all three kinds of cracks and the results are also acceptable for engineering application.

Planning and control problems are discussed. Siemens preprocessor PAN and SINETIK are oriented to CPM, PERT, MPM and other network methods. Preprocessor PLEIADES provides manufacturing organizations with a large kind of techniques.

A distinct and straightforward method to test and realize linearly-separable switching functions is presented. This method makes use of a universal map which facilitates the generation of inequalities and the detection of contradictions. It also eliminates any preprocessing (such as positivizing and ordering) of a given function. The concept of composite level is first defined. A map is then developed, which is not restricted by the number of variables in the given function. A switching function can be easily mapped. A simple process is presented to generate inequalities by inspection. This process will either conclude that the given function is not linearly-separable or generate a set of composite levels and, consequently, a set of weights for the threshold switching device. Two illustrative examples are provided.

A general model for speech synthesis by rule is presented along with a discussion of one specific implementation of the model. The conversion from discrete input signals to continuous synthesizer control signals is performed by the synthesis strategy. The details of the synthesis strategy, including linguistic preprocessing of the input and separate but interdependent segmental and suprasegmental models, are described. An experimental evaluation of the specific model is included, along with specific recommendations as to areas of speech synthesis and speech production requiring further study.

Feature extraction is one of the more difficult steps in image pattern recognition. Some sources of difficulty are the presence of irrelevant information and the relativity of a feature set to a particular application. Several preprocessing techniques for enhancing selected features and removing irrelevant data are described and compared. The techniques include gray level distribution linearization, digital spatial filtering, contrast enhancement, and image subtraction. Also, several feature extraction techniques are illustrated. The techniques are divided into spatial and Fourier domain operations. The spatial domain operations of directional signatures and contour tracing are first described. Then, the Fourier domain techniques of frequency signatures and template matching are illustrated. Finally, a practical image pattern recognition problem is solved using some of the described techniques.

The problem of machine vision as evidenced in the various robot projects in existence is attacked by analogy with the supposed nature of human visual processing in that edges are enhanced, texture is examined and various heuristic approaches are studied. This paper describes a non-anthropomorphically based method of decomposing a scene subjected to a special form of illumination into elementary planar areas. The method consists in coding the various planar areas as the modulation on a spatial frequency carrier grid so that the extraction of the planar areas becomes a matter of linear frequency domain filtering. The paper also addresses the application of grid coding to other problems in recording and extracting information from 3-D images.

This paper describes an implementation of syntax definitions in ALGOL in the form of phrase structures which are translated into ALGOL source statements by a preprocessor. No analysis records are constructed but ALGOL statements within the syntax definitions specify any action to be taken as soon as data are recognized. The first sections are concerned with definitions of the syntax and the semantics of phrases and phrase elements. The use of ALGOL phrases is illustrated by a complete phrase structure program, and finally the method of implementation is described This work arose from a need for extended teaching facilities in an environment in which the main programming languages in use were ALGOL and FORTRAN. The facilities implemented have also been used in applications requiring the input of structured data.

Analyses of diagnostic performance obtainable from inexperienced human interpretation of preprocessed dental radiographs demonstrate task dependent, perceptually meaningful guidelines for optimal coding of visual information. The transformations found to be most appropriate are based on essential stimuli common to the environment and containing features known to elicit visual responses.

META/LISP is a general purpose translator writing system for IBM System/360 currently running on TSS, CP/CMS, and OS/360. The input to the system is a source program which simultaneously describes 1) the syntax of some input data to be translated and 2) algorithms which operate on the input data and a pushdown stack to accomplish a desired translation; the output of the system is a compiled program for translating that input data. In particular when the input data are statements of a higher-level language to be translated into assembly language, META/LISP serves as a compiler-compiler. META/LISP uses the top-down syntax-directed approach which makes the system extremely attractive for the design and implementation of experimental languages; using META/LISP such compilers are easy to write, easy to check out, and - most importantly - easy to modify interactively. The appendices which follow a rather complete description of the system include a self-description of the META/LISP compiler.

This paper presents an analysis program that has been actively used for the last few years in design procedures for guyed transmission towers. The program uses a large scale sparse matrix technique to solve a linear three dimensional truss problem with multiple load cases. This solution incorporates an additional unit load case for each non-linear cable. The forces and displacements from the unit load cases are used as influence coefficients to re-solve for the non-linear members and form a statically and kinematically consistent solution. Among the special features of the program, are a preprocessor to check input data against the prototype and plot views of the structure, and a built-in reordering device which allows the practicing engineer to specify the data in arbitrary order but still obtain an efficient solution. A description of the input data and output reports is given and examples of application of the program to large structures are presented.

This paper describes a heuristic scene description system called INTERPRET. This system accepts as input a scene represented as a line drawing. Based on a set of known object models the program attempts to determine the identity and location of each object viewed. INTERPRET uses knowledge about the world in a variety of ways to produce a description of the scene that is consistent with its input. The most significant feature of the system is its ability to deal with imperfect input data. This ability appears essential in light of our current stock of preprocessing technique and the variation that is possible in real world data.