Perception of Order and Ambiguity in Leonardo’s Design Concepts

Leonardo da Vinci used geometry to give his design concepts both structural and visual balance. The paper examines aesthetic order in Leonardo’s structural design, and reflects on his belief in analogy between structure and anatomy. Leonardo’s drawings of grids and roof systems are generated from processes best known from ornamentation and can be developed into spatial structures assembled from loose elements with no need for binding elements. His architectural plans are patterns based on principles of tessellation, tiling and recursion, also characteristic of the reversible, ambiguous structures which led to Leonardo’s further inventions in structural and mechanical design as well as dynamic representations of space in his painting. In recent times, the ambiguous structures in the art of Joseph Albers, the reversible and impossible structures of M. C. Escher, the recurring patterns and spherical geometry of Buckminster Fuller and the reciprocal grids in structural design of Cecil Balmond display a similar interest. Computer models and animations have been used to simulate processes of perceiving and creating ambiguity in structures.     

Using OWL ontologies for adaptive patient information modelling and preoperative clinical decision support

We here present our research and experience regarding the design and implementation of a knowledge-based preoperative assessment decision support system. We discuss generic design considerations as well as the practical system implementation. We developed the system using semantic web technology, including modular ontologies developed in the OWL web ontology language, the OWL Java application programming interface and an automated logic reasoner. We discuss how the system enables to tailor patient information collection according to personalized medical context. The use of ontologies at the core of the system’s architecture permits to efficiently manage a vast repository of preoperative assessment domain knowledge, including classification of surgical procedures, classification of morbidities and guidelines for routine preoperative tests. Logical inference on the domain knowledge according to individual patient’s medical context enables personalized patients’ reports consisting of a risk assessment and clinical recommendations such as relevant preoperative tests.     

Towards an industrial grade IVE for Java and next generation research platform for JML

Tool support for the Java Modeling Language (JML) is a very pressing problem. A main issue with current tools is their architecture; the cost of keeping up with the evolution of Java is prohibitively high, e.g., Java 5 has yet to be fully supported. This paper presents JmlEclipse, an Integrated Verification Environment (IVE) for JML that builds upon Eclipse’s support for Java, enhancing it with preliminary versions of Runtime Assertion Checking (RAC), Extended Static Checking (ESC), Full Static Program Verification (FSPV), and symbolic execution. To our knowledge, JmlEclipse is the first IVE to support such a full range of verification techniques for a mainstream language. We present the original tool architecture as well as an improved design based on use of the JML Intermediate Representation (JIR), which helps decouple JmlEclipse from the internals of its base compiler. As a result, we believe that JmlEclipse is easier to maintain and extend. Use of JIR as a tool exchange format is also described.     

Preserving architectural decisions through architectural patterns

Architectural decisions have emerged as a means to maintain the quality of the architecture during its evolution. One of the most important decisions made by architects are those about the design approach such as the use of patterns or styles in the architecture. The structural nature of this type of decisions give them the potential to be controlled systematically. In the literature, there are some works on the automation of architectural decision violation checking. In this paper we show that these works do not allow to detect all possible architectural decision violations. To solve this problem we propose an approach which: (i) describes architectural patterns that hold the architectural decision definition, (ii) integrates architectural decisions into an architectural model and, (iii) automates the architectural decision conformance checking. The approach is implemented using Eclipse modeling framework and its accompanying technologies. Starting from well-known architectural patterns, we show that we can formalize all those related to the structural aspect. Through two evaluations, we show that our approach can be adapted to different architecture paradigms and allows to detect more violations comparing to the existing approaches.     

Zipf’s and Bradford’s laws and universal models

Zipf’s and Bradford’s laws are empirical laws that were derived by the processing and analysis of so-called rank distributions. In this paper, they are treated as special cases of generalized (universal) continuous distributions that can accurately describe a wide variety of statistical distributions, including rank. We present the universal laws of the diffusion and aging of publications.     

Deliberative discourse and reasoning from generic argument structures

In this article a dialectical model for practical reasoning within a community, based on the Generic/Actual Argument Model (GAAM) is advanced and its application to deliberative dialogue discussed. The GAAM, offers a dynamic template for structuring knowledge within a domain of discourse that is connected to and regulated by a community. The paper demonstrates how the community accepted generic argument structure acts to normatively influence both admissible reasoning and the progression of dialectical reasoning between participants. It is further demonstrated that these types of deliberation dialogues supported by the GAAM comply with criteria for normative principles for deliberation, specifically, Alexy’s rules for discourse ethics and Hitchcock’s Principles of Rational Mutual Inquiry. The connection of reasoning to the community in a documented and transparent structure assists in providing best justified reasons, principles of deliberation and ethical discourse which are important advantages for reasoning communities.     

Assessment of wheelchair skills based on analysis of driving style

In this paper, we propose a learning assessment method based on the analysis of learner’s behavioural style. This method was first applied for wheel-chair driving tasks because it is simple and risk-free, but unusual for users. Seven classic performance indicators based on joystick control were used to characterise the users’ driving style. We assumed that the learning effectiveness of the users can be evaluated by comparing their driving style with the reference ones, which could be extracted from experienced users. The evaluation was carried out for six novice users and eight experienced users. The users were asked to carry out several typical driving tasks for seven trials at first. The fuzzy C-means clustering method was used with the data of the experienced users to obtain the reference driving styles. Next, an evaluation was performed for novice users by comparing their driving styles with the reference ones. The results showed that, for all of the experienced users, their driving styles could be classified into two reference types. In addition, there was no significant difference in their driving styles from one trial to another, even for a user with disabilities, which means that their driving style was stable. On the other hand, novice users had switching behaviours during the learning phase; however, after eight additional trials, each novice user’s driving style converged to one of the two identified reference types, meaning that the novice users could achieve a stable performance after learning, which was also validated by an expert therapist.     

Is Evolution Algorithmic?

In Darwin’s Dangerous Idea, Daniel Dennett claims that evolution is algorithmic. On Dennett’s analysis, evolutionary processes are trivially algorithmic because he assumes that all natural processes are algorithmic. I will argue that there are more robust ways to understand algorithmic processes that make the claim that evolution is algorithmic empirical and not conceptual. While laws of nature can be seen as compression algorithms of information about the world, it does not follow logically that they are implemented as algorithms by physical processes. For that to be true, the processes have to be part of computational systems. The basic difference between mere simulation and real computing is having proper causal structure. I will show what kind of requirements this poses for natural evolutionary processes if they are to be computational.     

Architecture, Patterns, and Mathematics

Nikos Salingaros posits the importance of architectural pattern in man’s intellectual development, examining how twentieth century architectural attitudes towards decoration and pattern have impoverished man’s experience of both mathematics and the built environment.     

Using affective parameters in a content-based recommender system for images

There is an increasing amount of multimedia content available to end users. Recommender systems help these end users by selecting a small but relevant subset of items for each user based on her/his preferences. This paper investigates the influence of affective metadata (metadata that describe the user’s emotions) on the performance of a content-based recommender (CBR) system for images. The underlying assumption is that affective parameters are more closely related to the user’s experience than generic metadata (e.g. genre) and are thus more suitable for separating the relevant items from the non-relevant. We propose a novel affective modeling approach based on users’ emotive responses. We performed a user-interaction session and compared the performance of the recommender system with affective versus generic metadata. The results of the statistical analysis showed that the proposed affective parameters yield a significant improvement in the performance of the recommender system.     

Indistinguishable from Magic: Computation is Cognitive Technology

This paper explains how mathematical computation can be constructed from weaker recursive patterns typical of natural languages. A thought experiment is used to describe the formalization of computational rules, or arithmetical axioms, using only orally-based natural language capabilities, and motivated by two accomplishments of ancient Indian mathematics and linguistics. One accomplishment is the expression of positional value using versified Sanskrit number words in addition to orthodox inscribed numerals. The second is Pāṇini’s invention, around the fifth century BCE, of a formal grammar for spoken Sanskrit, expressed in oral verse extending ordinary Sanskrit, and using recursive methods rediscovered in the twentieth century. The Sanskrit positional number compounds and Pāṇini’s formal system are construed as linguistic grammaticalizations relying on tacit cognitive models of symbolic form. The thought experiment shows that universal computation can be constructed from natural language structure and skills, and shows why intentional capabilities needed for language use play a role in computation across all media. The evolution of writing and positional number systems in Mesopotamia is used to transfer the thought experiment of “oral arithmetic” to inscribed computation. The thought experiment and historical evidence combine to show how and why mathematical computation is a cognitive technology extending generic symbolic skills associated with language structure, usage, and change.     

A study on the effect of morphological filters on computer-aided medical image diagnosis

We have developed several morphological image filters that can be useful for computer-aided medical image diagnosis. Several computer-aided diagnosis (CAD) systems for lung cancer and breast cancer have been developed to assist the radiologist’s diagnostic work. The CAD systems for lung cancer can automatically detect pathological changes (pulmonary nodules) with a high true-positive rate (TP) even under low false-positive rate (FP) conditions. On the other hand, the conventional CAD systems for breast cancer can automatically detect some pathological changes (calcifications and masses), but the TP for other changes, such as architectural distortion, is still very low. Motivated by the radiologist’s cognitive processes to increase TP for breast cancer, we propose new methods to extract novel morphological features from X-ray mammography. Simulation results demonstrate the effectiveness of the morphological methods for detecting tumor shadows.     

Decision Making and Management of Dynamic Risk

Managing dynamic environments often requires decision making under uncertainty and risk. Two types of uncertainty are involved: uncertainty about the state and the evolution of the situation, and ‘openness’ of the possible actions to face possible consequences. In an experimental study on risk management in dynamic situations, two contrasted ‘ecological’ scenarios – transposed from effective situations of emergency management – were compared in order to identify the impact of their ‘openness’ in the subjects’ strategies for decision making. The ‘Lost Child’ scenario presented qualitative and irreversible consequences (child’s death) and high uncertainty; it exerted high demands both in risk assessment (risk representation) and action elaboration and choice. A less open situation (‘Hydrocarbon Fire’) required a main choice between two contrasted actions, with quantitative computable consequences. The strategies of ‘experimental subjects’ (university students) and ‘operative subjects’ (professional fire-fighter officers) were compared in order to evaluate the ecological validity of experimental research in this field, from the point of view of the subjects themselves. The two scenarios appeared to be independent, so that quite different models of decision making have to be hypothesised, differing by the importance of assessing risk and defining possible actions on the one hand, and by the process of choice on the other. ‘Experimental’ subjects dramatically differed from ‘operative’ subjects when confronted with the same scenario, particularly for the less technical but more demanding scenario. It is hypothesised that three components might account for the effect of the situations and for the differences between and within groups of subjects: importance of situation assessment, spatial abilities, and global orientation of activity in managing dynamic risk.     

Historical perception as a complementary framework for understanding the usability of mobile computers

This paper suggests a social-psychological framework for understanding the usability of mobile computers. This framework complements and extends extant sociological explanations of mobile computing. Sociological explanations satisfy principles of pragmatism and ubiquity in judging the usability of mobile computers. The paper argues that sociological explanations are inadequate, and draws upon the historical epistemology of perception to propose social-psychological explanations to complement them. By this epistemology, a user’s perception is deemed as a mode of action that is mediated by historical or functional representations. These issues are illustrated in an empirical case of the use of personal digital assistants (PDAs) in hospitals of the British National Health Service. The historical epistemology of perception suggests the principle of representation to complement the existing principles of ubiquity and pragmatism. This suggestion is derived from an analysis of the complementation between the user’s perception, work and movement which are conscious actions enacted concurrently during the use of mobile computers. Implications for the implementation and evaluation of mobile computing projects are provided.     

Study on IAC networks models: learning and stability

This paper presents a methodology that uses evolutionary learning in training ‘A’ model networks, a topology based on Interactive Activation and Competition (IAC) neural networks. IAC networks show local knowledge and processing units clustered in pools. The connections among units may assume only 1, 0 or −1. On the other hand, ‘A’ model network uses values in interval [−1, 1]. This feature provides a wider range of applications for this network, including problems which do not show mutually exclusive concepts. However, there is no algorithm to adjust the network weights and still preserve the desired characteristics of the original network. Accordingly, we propose the use of genetic algorithms in a new methodology to obtain the correct weight set for this network. Two examples are used to illustrate the proposed method. Findings are considered consistent and generic enough to allow further applications on similar classes of problems suitable for ‘A’ model IAC Networks.     

Logical considerations on default semantics

We consider a reinterpretation of the rules of default logic. We make Reiter’s default rules into a constructive method of building models, not theories. To allow reasoning in first‐order systems, we equip standard first‐order logic with a (new) Kleene 3‐valued partial model semantics. Then, using our methodology, we add defaults to this semantic system. The result is that our logic is an ordinary monotonic one, but its semantics is now nonmonotonic. Reiter’s extensions now appear in the semantics, not in the syntax. As an application, we show that this semantics gives a partial solution to the conceptual problems with open defaults pointed out by Lifschitz [V. Lifschitz, On open defaults, in: Proceedings of the Symposium on Computational Logics (1990)], and Baader and Hollunder [F. Baader and B. Hollunder, Embedding defaults into terminological knowledge representation formalisms, in: Proceedings of Third Annual Conference on Knowledge Representation (Morgan‐Kaufmann, 1992)]. The solution is not complete, chiefly because in making the defaults model‐theoretic, we can only add conjunctive information to our models. This is in contrast to default theories, where extensions can contain disjunctive formulas, and therefore disjunctive information. Our proposal to treat the problem of open defaults uses a semantic notion of nonmonotonic entailment for our logic, related to the idea of “only knowing”. Our notion is “only having information” given by a formula. We discuss the differences between this and “minimal‐knowledge” ideas. Finally, we consider the Kraus–Lehmann–Magidor [S. Kraus, D. Lehmann and M. Magidor, Nonmonotonic reasoning, preferential models, and cumulative logics, Artificial Intelligence 44 (1990) 167–207] axioms for preferential consequence relations. We find that our consequence relation satisfies the most basic of the laws, and the Or law, but it does not satisfy the law of Cut, nor the law of Cautious Monotony. We give intuitive examples using our system, on the other hand, which on the surface seem to violate these two laws. We make some comparisons, using our examples, to probabilistic interpretations for which these laws are true, and we compare our models to the cumulative models of Kraus, Lehmann, and Magidor. We also show sufficient conditions for the laws to hold. These involve limiting the use of disjunction in our formulas in one way or another. We show how to make use of the theory of complete partially ordered sets, or domain theory. We can augment any Scott domain with a default set. We state a version of Reiter’s extension operator on arbitrary domains as well. This version makes clear the basic order‐theoretic nature of Reiter’s definitions. A three‐variable function is involved. Finding extensions corresponds to taking fixed points twice, with respect to two of these variables. In the special case of precondition‐free defaults, a general relation on Scott domains induced from the set of defaults is shown to characterize extensions. We show how a general notion of domain theory, the logic induced from the Scott topology on a domain, guides us to a correct notion of “affirmable sentence” in a specific case such as our first‐order systems. We also prove our consequence laws in such a way that they hold not only in first‐order systems, but in any logic derived from the Scott topology on an arbitrary domain. This revised version was published online in June 2006 with corrections to the Cover Date.     

The Golden Section in Architectural Theory

The never-ending—but always young—discussion about the Golden Section in architecture never lacks a hint at Luca Pacioli and architectural theory. But what it always lacks is a thorough study of the Golden Section in architectural theory. This paper aims to present this analysis. Marcus Frings traces the Golden Section from the mathematical and rather theoretical character of Pacioli’s concept, the the treatises of Alberti, Serlio, and Palladio, to Adolf Zeising in the nineteenth century. and to theorist Matila Ghyka and the practitioners Ernst Neufert and Le Corbusier in the twentieth. In the latter’s writings and designs the Golden Section seems to play the role of a scholarly element which shows the master’s theoretical erudition, leading to contemporary architects such as Ricardo Bofill.