Instance and System: a Figure and its 2 18 Variations

Similar documents
1/9. Descartes on Simple Ideas (2)

UNIVERSAL SPATIAL UP-SCALER WITH NONLINEAR EDGE ENHANCEMENT

STUDENTS EXPERIENCES OF EQUIVALENCE RELATIONS

Musical Harmonization with Constraints: A Survey. Overview. Computers and Music. Tonal Music

PLANE TESSELATION WITH MUSICAL-SCALE TILES AND BIDIMENSIONAL AUTOMATIC COMPOSITION

Typography & Page Layout

Computer Graphics Hardware

Authentication of Musical Compositions with Techniques from Information Theory. Benjamin S. Richards. 1. Introduction

Lab P-6: Synthesis of Sinusoidal Signals A Music Illusion. A k cos.! k t C k / (1)

Mechanical aspects, FEA validation and geometry optimization

UC San Diego UC San Diego Previously Published Works

Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at

Finding a key detection method with TRIZ

Development of an Optical Music Recognizer (O.M.R.).

Module 8 VIDEO CODING STANDARDS. Version 2 ECE IIT, Kharagpur

Motion Video Compression

Improving Performance in Neural Networks Using a Boosting Algorithm

SIMULATION OF PRODUCTION LINES THE IMPORTANCE OF BREAKDOWN STATISTICS AND THE EFFECT OF MACHINE POSITION

Lab Determining the Screen Resolution of a Computer

inter.noise 2000 The 29th International Congress and Exhibition on Noise Control Engineering August 2000, Nice, FRANCE

Choices and Constraints: Pattern Formation in Oriental Carpets

Quantify. The Subjective. PQM: A New Quantitative Tool for Evaluating Display Design Options

Sidestepping the holes of holism

Increasing Capacity of Cellular WiMAX Networks by Interference Coordination

The SmoothPicture Algorithm: An Overview

1/8. Axioms of Intuition

NOTE ON PERFORMANCE TESTING

Lab 6: Edge Detection in Image and Video

Bas C. van Fraassen, Scientific Representation: Paradoxes of Perspective, Oxford University Press, 2008.

20 Mar/Apr 2016 Energy Magazine. Copyright Healing Touch Program Inc.

CURIE Day 3: Frequency Domain Images

Colour Reproduction Performance of JPEG and JPEG2000 Codecs

CPU Bach: An Automatic Chorale Harmonization System

CSE 166: Image Processing. Overview. Representing an image. What is an image? History. What is image processing? Today. Image Processing CSE 166

The Museum of Modern Art

Table of content. Table of content Introduction Concepts Hardware setup...4

TechNote: MuraTool CA: 1 2/9/00. Figure 1: High contrast fringe ring mura on a microdisplay

EVOLVING DESIGN LAYOUT CASES TO SATISFY FENG SHUI CONSTRAINTS

Optimized Color Based Compression

Optical Engineering Review Form

BIC Standard Subject Categories an Overview November 2010

About video compressions, JPG blocky artefacts, matrices and jagged edges

OPERATIONS SEQUENCING IN A CABLE ASSEMBLY SHOP

Characterization and improvement of unpatterned wafer defect review on SEMs

Chapter 2 Christopher Alexander s Nature of Order

Multi-Frame Matrix Capture Common File Format (MFMC- CFF) Requirements Capture

SocioBrains THE INTEGRATED APPROACH TO THE STUDY OF ART

PROPORTIONS AND THE COMPOSER'

Pivoting Object Tracking System

MATH& 146 Lesson 11. Section 1.6 Categorical Data

BA single honours Music Production 2018/19

Permutations of the Octagon: An Aesthetic-Mathematical Dialectic

CS2401-COMPUTER GRAPHICS QUESTION BANK

Objective Interpretation and the Metaphysics of Meaning

Boosting Creativity Skills & Innovation in Architectural Design Process Using Multimedia

Adaptive decoding of convolutional codes

FIT OR MISFIT IN THE BUILT ENVIRONMENT

ATOMIC NOTATION AND MELODIC SIMILARITY

PROLITE B2791HSU-B1 HAS + PIVOT FLICKER FREE + BLUE LIGHT

IMS B007 A transputer based graphics board

Key-based scrambling for secure image communication

1/ 19 2/17 3/23 4/23 5/18 Total/100. Please do not write in the spaces above.

Route optimization using Hungarian method combined with Dijkstra's in home health care services

Entry 1: Turtle graphics 1.8

TeeJay Publishers. Curriculum for Excellence. Course Planner - Level 1

inter.noise 2000 The 29th International Congress and Exhibition on Noise Control Engineering August 2000, Nice, FRANCE

National Standards for Visual Art The National Standards for Arts Education

technology T05.2 teach with space MEET THE SENSE HAT Displaying text and images on the Sense HAT LED matrix

R&D White Paper WHP 085. The Rel : a perception-based measure of resolution. Research & Development BRITISH BROADCASTING CORPORATION.

Rethinking the Aesthetic Experience: Kant s Subjective Universality

Lecture 7: Incongruent Counterparts

Internal assessment details SL and HL

Bibliometric glossary

Music Performance Panel: NICI / MMM Position Statement

Chapter 1. Introduction to Digital Signal Processing

Similarity matrix for musical themes identification considering sound s pitch and duration

Setting the quality standards. Glass Inspection. Defect detection from the technology leader

A PSYCHOACOUSTICAL INVESTIGATION INTO THE EFFECT OF WALL MATERIAL ON THE SOUND PRODUCED BY LIP-REED INSTRUMENTS

Wipe Scene Change Detection in Video Sequences

Analysis of local and global timing and pitch change in ordinary

Visual Encoding Design

TERMS & CONCEPTS. The Critical Analytic Vocabulary of the English Language A GLOSSARY OF CRITICAL THINKING

Data Representation. signals can vary continuously across an infinite range of values e.g., frequencies on an old-fashioned radio with a dial

Subtitle Safe Crop Area SCA

VISUAL INTERPRETATION OF ARCHITECTURAL FORM

MELONET I: Neural Nets for Inventing Baroque-Style Chorale Variations

Example: compressing black and white images 2 Say we are trying to compress an image of black and white pixels: CSC310 Information Theory.

Music Composition with Interactive Evolutionary Computation

Choosing the Right Machine Vision Applications

Brand Identity Standards

Practical Application of the Phased-Array Technology with Paint-Brush Evaluation for Seamless-Tube Testing

THE INDIAN KEYBOARD. Gjalt Wijmenga

xlsx AKM-16 - How to Read Key Maps - Advanced 1 For Music Educators and Others Who are Able to Read Traditional Notation

INSTRUCTIONS FOR COMPILATION OF THESIS/RESEARCH DISSERTATION

Laboratory Assignment 3. Digital Music Synthesis: Beethoven s Fifth Symphony Using MATLAB

Micro-DCI 53ML5100 Manual Loader

Investigation of Look-Up Table Based FPGAs Using Various IDCT Architectures

Example the number 21 has the following pairs of squares and numbers that produce this sum.

Experimental Music: Doctrine

In basic science the percentage of authoritative references decreases as bibliographies become shorter

Transcription:

Instance and System: a Figure and its 2 18 Variations Univ.-Prof. H. E. Dehlinger, Dipl.-Ing, M.Arch., Ph.D. (UC Berkeley) Kunsthochschule Kassel, University of Kassel, Germany e-mail: dehling@uni-kassel.de Abstract From the structural characteristics of an existing figure - a graphical logo a plausible solution space of related figures is constructed, which contains all other figures, which may be generated by systematically exploiting the structural characteristics of the input figure. The constructed space of figures can be understood to represent the solution space for the design of the logo. A designer, proceeding systematically by following some generative set of rules would have to construct this solution space at least to the point of a decision, if not entirely. In the presented experiment, this solution space will be exhausted completely and the resulting images (there are 2 18 will be outputted graphically. Questions will be asked concerning the design process, the generative rules, and the selection of the one instance representing a solution. The presented results are to be seen as work in progress. Constructing and inspecting solution spaces We regard here generative processes in designing and mean by that, processes, procedures, algorithms etc., which produce "designs". There are examples of generative processes in architecture in literature in music in design; in the fine arts and in a number of other areas. Many of them are represented at this conference [1]. Frequently (but not necessarily) such generative processes are based on very general and universally applicable rule systems that are not specific to the discipline they may serve (examples are the rules of logic or those of combinatorial mathematics). The existence of such "universally" applicable rules also brought out "universally" applicable methods for the treatment of any kind of problem. A well-known example is the method of morphological analysis suggested by Zwicky [2], which applies combinatorial rules to a structured matrix of parameters Common to all these efforts is to find rule systems, which, when applied will produce solutions / alternatives fulfilling, more or less, the requirements of a set task. One imagines a solution space which we do not know yet but in which the searched for solutions already exist, however at unknown coordinates. They are made visible by a process of generative steps, which send the designer on a journey through the solution space, which ends at a discrete point ( the journey ends on a station. The rules for the generative process are instrumental rules, which actually lead in a finite number of steps to a defined point in the solution space. Thus, the rules must contain a stopping rule. In mathematics such procedural systems are known as algorithms. The imagination of an ordered solution space is useful, because it presupposes that the solutions contained in it possess a certain structure. If solutions are close to each other, they have similar properties. The differences become larger, the further apart from each other they are. However, all solutions are related structurally. The variations are controlled by a set of known parameters, which are manipulated through the rules. This demands they are defined (accepted, selected, have been 2. 1

found, designed, etc.). With the generative approach to design the attention of designing is on the structural characteristics of a problem and on the manipulating rules. Each produced solution represents a valid instance from the system of all solutions conceivable. Depending upon the size of the solution space one can pursue two strategies: (1) with a large solution space (and most problems require large solution spaces) one can: - generate one solution and judge it immediately; - generate small sets of solutions at a time, judge each one or compare them to find the best one in the set. The focus of proceeding is here on the single instance, the unique piece, and if necessary on a small number. One can take the "first best" solution, or somehow produce a number of solutions, or inspect the solution space using any sort of criteria. This strategy is similar to the traditional process of designing: one tries to find a solution somehow and develops it, criticizing, changing, improving. Rather unusual (for good reasons) in the eyes of traditional designing is: (2) the complete and systematic exhaustion of the entire solution space. It is in principle impossible with real tasks of design to pursue this strategy (rationality dilemma of design) and it is not advisable for pragmatic reasons even with "small" problems (as we will see) the number of solutions residing in a solution space is very large, so large that we can not examine them all. Indeed, if not restrained artificially and with proper measures, the solution space to any design problem is of infinite magnitude. It is exactly the measures of restraining we apply which will determine the strategy which is open for the generative process. This, of course also holds for any other approach to design, but the explicit search and formulation of a generative rule forces consistently to focus on structure. The benefit is we can be certain no good solution will escape our attention. Normally, the designer is far away from such a position and applies heuristic methods to meet uncertainty. Design is afflicted in principle with such uncertainties. For the strategy under (2) there are interesting cases in literature: in the description of the "academy of Laputa" in Gulliver s Travels by Jonathan Swift [3], Gulliver is confronted with a " project on the improvement of speculative knowledge where even the most uneducated person at a reasonable charge and with some physical labour can write books in philosophy, poetry, politics, law, mathematics and theology, without the least assistance from genius or learning. The Library of Babel" of Jorge Luis Borges [4], is a further example from literature. Somewhat absurd are both, because most of the generative results produced turn out to be nonsense and obviously our capacity is not fitted to handle such tremendous number of possible events. We can interpret the machine in the academy of Laputa as a monitor screen on which each pixel can accept a certain range of values. The output of this system will then be the whole of all representable texts and pictures. 2. 2

A figure and its variations For experimental considerations, despite all objections, we now want to design a case of complete exhaustion of a solution space. For an already existing design, a logo [5], designed by the office of Graphic Designers Stankowski + Duschek, (see Fig.1), a solution space will be designed containing all related instances, following the structural properties of the input figure. Figure 1 Top: Original Fig. Row2: Structural System Row3: Examples using 3 strokes Row 4: Enhanced We strictly follow the matrix of these structural properties and only use as variational parameters the short strokes located in defined positions. It seems they represent a substantial characteristic 2. 3

of this logo. Some of the variations are shown in Fig: 2, Fig. 3 is a collection of all possible figures using 3 strokes only (like the initial figure). The structural "system", which defines the logo and all its variations, is a square that is subdivided into nine smaller squares (see Fig.1). In order to construct the solution space to which the figure and its variations belong, we analyse the structural system of the figure and we select the following list of parameters: geometry of figure:. square structure of matrix:. orthogonal number of cells vertical / horizontal:.. 3 / 3 number of stokes per cell: 2 subdivision:. two vertical divisions positions of strokes (angles):.. 45 degrees, (+/-) variation in line thickness:.. none trimming of edges: sharp, no offset line type: straight line etc. We can now try to design a solution space for the generation of all figures related to the input figure. There are 2 18 possible instances, see Fig. 2 for a fraction of them. With a relatively simple program one can draw them all (for which 10 sheets of size A0 are needed if each figure occupies somewhat less than a square centimetre). We imagine a systematically working designer, who, before making a choice, wants to know all of the possible variations and has constructed them. He must now device rules of evaluation (selection, judgement), by which all but one of the instances may be rejected. In a design process we normally assume a limited number of alternatives has been developed by the designer from which the best is selected. Two fundamental problems arise, which are characteristic for all design processes: How does one arrive at a solution space? (generation of variety); and: Which selection (decision) rules to use? (reduction of variety). It is hardly possible to imagine a more dramatic contrast between the procedure of complete exhaustion of a solution space and the traditional way of designing. I do not know, how the logo in Fig.1 was developed, but it is safe to assume, the designer did not survey the entire solution space suggested by the structural system, which of course was chosen quite deliberately. Questions that arise: How would one have to change the generative rules, in order to produce few "useless" solutions? Which changes in the structural system would open further "meaningful" solution spaces? With respect to the suggested figure, are there still figures remaining in the constructed solution space which would be classified by an expert as "better"? Some examples to changes in the structural properties of the initial figure are listed in Fig. 4, where each entry is suggesting an own and differently structured solution space compared with the described one. Could we formulate guiding statements, agreeable for the majority of the design community, to control the generative process? For the figure under consideration here, some candidates for such statements may be: - simplicity is good - a diagonal from bottom left to top right is dynamic, optimistic - order is preferable over disorder - geometry generates order - etc. 2. 4

Fig. 2 Fraction of the solution space for logo 2. 5

If we obey such rules, they can provide constraints in generative process like: - strokes in a few positions only - no crossing of strokes - combine two diagonal strokes of same tilt to a double stroke - occupy only diagonal squares - etc. The value of the approach to completely exhaust a solution space may be questionable. But there is also an aesthetic to the produced results, that is quite unique. Fig. 3 All figures out of 2 18, which occupy 3 positions 2. 6

References [1] Soddu, C., Generative Art. Proceedings of the 1999 Milan International Conference Generative Art «99. Generative Design Lab, Milan Polytechnic, Milan 1999 [2] Zwicky, Fritz: Entdecken, Erfinden, Forschen im Morphologischen Weltbild, Verlag Baeschlin, Glarus [3] Swift, Jonathan: Gullivers Reisen, Reclam Universal Bibliothek Nr. 651, p. 237, Stuttgart 1998 [4] Borges, Jose Luis: Labyrinths; Selected Stories and Other Writings, ed. By Donald A. Yates and James E. Irby; New Directions Publishing Corporation, New York, 1964 [5] design report 3 / 2002 2. 7