A Stylometric Analysis of Ya?ar Kemal’s ? nce Memed Tetralogy

We analyze four nce Memed novels of Yaar Kemal using six style markers: most frequent words, syllable counts, word type – or part of speech – information, sentence length in terms of words, word length in text, and word length in vocabulary. For analysis we divide each novel into five thousand word text blocks and count the frequencies of each style marker in these blocks. The style markers showing the best separation are most frequent words and sentence lengths. We use stepwise discriminant analysis to determine the best discriminators of each style marker. We then use these markers in cross validation based discriminant analysis. Further investigation based on multiple analysis of variance (MANOVA) reveals how the attributes of each style marker group distinguish among the volumes.     

A Philosophical Approach to the Concept of Data Model: Is a Data Model, in Fact, a Model?

The design of the database is crucial to the process of designing almost any Information System (IS) and involves two clearly identifiable key concepts: schema and data model, the latter allowing us to define the former. Nevertheless, the term model is commonly applied indistinctly to both, the confusion arising from the fact that in Software Engineering (SE), unlike in formal or empirical sciences, the notion of model has a double meaning of which we are not always aware. If we take our idea of model directly from empirical sciences, then the schema of a database would actually be a model, whereas the data model would be a set of tools allowing us to define such a schema.The present paper discusses the meaning of model in the area of Software Engineering from a philosophical point of view, an important topic for the confusion arising directly affects other debates where model is a key concept. We would also suggest that the need for a philosophical discussion on the concept of data model is a further argument in favour of institutionalizing a new area of knowledge, which could be called: Philosophy of Engineering.     

Choosing reference classes and building provisional models

A well-known problem in default logic is the ability of naive reasoners to explain bothg and ¬g from a set of observations. This problem is treated in at least two different ways within that camp.One approach is examination of the various explanations and choosing among them on the basis of various explanation comparators. A typical comparator is choosing the explanation that depends on the most specific observation, similar to the notion of narrowest reference class.Others examine default extensions of the observations and choose whatever is true in any extension, or what is true in all extensions or what is true in preferred extensions. Default extensions are sometimes thought of as acceptable models of the world that are discarded as more knowledge becomes available.We argue that the notions of specificity and extension lack clear semantics. Furthermore, we show that the problems these ideas were supposed to solve can be handled easily within a probabilistic framework.     

A model for pattern perception with musical applications part I: Pitch structures as order-preserving maps

The initial five papers of this series on pattern perception treat first, the perception of pitch in musical contexts and then, the perception of timbre and speech. Each sound is considered to be embedded in a context consisting of those sounds which surround it or coincide with it. The apprehension of a musical pattern depends upon the perceptibility of certain relations between, and properties of, its parts (e.g. motifA is similar to motifB or G is the tonic). It is hypothesized that, because of the limitations of short term memory, the perception of specific relations and properties requires that certain mental reference frames be extracted from the various contexts. However, a reference frame which supports the perception of any specified relation may be extracted from only very few of all possible contexts. The choices of musical materials in both Western and non-Western music are shown to avoid precisely such difficulties. When they are not avoided, distortions of perception are predicted and methods for experimental verification are suggested. This theory is then applied to suggest new materials for the composition of both microtonal and tonecolor music. This is done in a manner which exposes the correspondence between each choice of musical materials and those musical properties and relations whose perception is (or is not) thereby supported.This first paper discusses the relation between the ability to perceive relative sizes of musical intervals and the choice of reference frame from a given musical context.     

Complexity and computability of solutions to linear programming systems

Through key examples and constructs, exact and approximate, complexity, computability, and solution of linear programming systems are reexamined in the light of Khachian's new notion of (approximate) solution. Algorithms, basic theorems, and alternate representations are reviewed. It is shown that the Klee-Minty example hasnever been exponential for (exact) adjacent extreme point algorithms and that the Balinski-Gomory (exact) algorithm continues to be polynomial in cases where (approximate) ellipsoidal centered-cutoff algorithms (Levin, Shor, Khachian, Gacs-Lovasz) are exponential. By model approximation, both the Klee-Minty and the new J. Clausen examples are shown to be trivial (explicitly solvable) interval programming problems. A new notion of computable (approximate) solution is proposed together with ana priori regularization for linear programming systems. New polyhedral constraint contraction algorithms are proposed for approximate solution and the relevance of interval programming for good starts or exact solution is brought forth. It is concluded from all this that the imposed problem ignorance of past complexity research is deleterious to research progress on computability or efficiency of computation.This research was partly supported by Project NR047-071, ONR Contract N00014-80-C-0242, and Project NR047-021, ONR Contract N00014-75-C-0569, with the Center for Cybernetic Studies, The University of Texas at Austin.     

Regions-of-Interest and Spatial Layout for Content-Based Image Retrieval

To date most content-based image retrieval (CBIR) techniques rely on global attributes such as color or texture histograms which tend to ignore the spatial composition of the image. In this paper, we present an alternative image retrieval system based on the principle that it is the user who is most qualified to specify the query content and not the computer. With our system, the user can select multiple regions-of-interest and can specify the relevance of their spatial layout in the retrieval process. We also derive similarity bounds on histogram distances for pruning the database search. This experimental system was found to be superior to global indexing techniques as measured by statistical sampling of multiple users' satisfaction ratings.     

The informed neuron: Issues in the use of information theory in the behavioral sciences

The concept of information is virtually ubiquitous in contemporary cognitive science. It is claimed to be processed (in cognitivist theories of perception and comprehension), stored (in cognitivist theories of memory and recognition), and otherwise manipulated and transformed by the human central nervous system. Fred Dretske's extensive philosophical defense of a theory of informational content (semantic information) based upon the Shannon-Weaver formal theory of information is subjected to critical scrutiny. A major difficulty is identified in Dretske's equivocations in the use of the concept of a signal bearing informational content. Gibson's alternative conception of information (construed as analog by Dretske), while avoiding many of the problems located in the conventional use of signal, raises different but equally serious questions. It is proposed that, taken literally, the human CNS does not extract or process information at all; rather, whatever information is construed as locatable in the CNS is information only for an observer-theorist and only for certain purposes.Blood courses through our veins, andinformation through our central nervous system.— A Neuropsychology Textbook.     

Data encodings and their costs

Summary This paper is devoted to developing and studying a precise notion of the encoding of a logical data structure in a physical storage structure, that is motivated by considerations of computational efficiency. The development builds upon the notion of an encoding of one graph in another. The cost of such an encoding is then defined so as to reflect the structural compatibility of the two graphs, the (externally specified) costs of implementing the host graph, and the (externally specified) set of intended usage patterns of the guest graph. The stability of the constructed framework is demonstrated in terms of a number of results; the faithfulness of the formalism is argued in terms of a number of examples from the literature; and the tractability of the model is hinted at by several results and by further references to the literature.     

Prequential and Cross-Validated Regression Estimation

Prequential model selection and delete-one cross-validation are data-driven methodologies for choosing between rival models on the basis of their predictive abilities. For a given set of observations, the predictive ability of a model is measured by the model's accumulated prediction error and by the model's average-out-of-sample prediction error, respectively, for prequential model selection and for cross-validation. In this paper, given i.i.d. observations, we propose nonparametric regression estimators—based on neural networks—that select the number of hidden units (or neurons) using either prequential model selection or delete-one cross-validation. As our main contributions: (i) we establish rates of convergence for the integrated mean-squared errors in estimating the regression function using off-line or batch versions of the proposed estimators and (ii) we establish rates of convergence for the time-averaged expected prediction errors in using on-line versions of the proposed estimators. We also present computer simulations (i) empirically validating the proposed estimators and (ii) empirically comparing the proposed estimators with certain novel prequential and cross-validated mixture regression estimators.     

The role of “craft language” in learning “Waza”

The role of craft language in the process of teaching (learning) Waza (skill) will be discussed from the perspective of human intelligence.It may be said that the ultimate goal of learning Waza in any Japanese traditional performance is not the perfect reproduction of the teaching (learning) process of Waza. In fact, a special metaphorical language (craft language) is used, which has the effect of encouraging the learner to activate his creative imagination. It is through this activity that the he learns his own habitus (Kata).It is suggested that, in considering the difference of function between natural human intelligence and artificial intelligence, attention should be paid to the imaginative activity of the learner as being an essential factor for mastering Kata.This article is a modified English version of Chapter 5 of my bookWaza kara shiru (Learning from Skill), Tokyo University Press, 1987, pp. 93–105.     

Modelling structures in generic space, a condition for adaptiveness of monitoring cognitive agent

The adaptiveness of agents is one of the basic conditions for the autonomy. This paper describes an approach of adaptiveness forMonitoring Cognitive Agents based on the notion of generic spaces. This notion allows the definition of virtual generic processes so that any particular actual process is then a simple configuration of the generic process, that is to say a set of values of parameters. Consequently, generic domain ontology containing the generic knowledge for solving problems concerning the generic process can be developed. This lead to the design of Generic Monitoring Cognitive Agent, a class of agent in which the whole knowledge corpus is generic. In other words, modeling a process within a generic space becomes configuring a generic process and adaptiveness becomes genericity, that is to say independence regarding technology. In this paper, we present an application of this approach on Sachem, a Generic Monitoring Cognitive Agent designed in order to help the operators in operating a blast furnace. Specifically, the NeuroGaz module of Sachem will be used to present the notion of a generic blast furnace. The adaptiveness of Sachem can then be noted through the low cost of the deployment of a Sachem instance on different blast furnaces and the ability of NeuroGaz in solving problem and learning from various top gas instrumentation.     

Approximate syllogisms – on the logic of everyday life

Since Aristotle it is recognised that a valid syllogism cannot have two particular premises. However, that is not how a lay person sees it; at least as long as the premises read many, most etc, instead of a plain some. The lay people are right if one considers that these syllogisms do not have strict but approximate (Zadeh) validity. Typically there are only particular premises available in everyday life and one is dependent on such syllogisms. – Some rules on the usage of particular premises are given below.     

Modular visions: Referents, context and strategies for database open media works

The processes of constructing meaning in digital database environments entail a paradigm shift from previous models of audio-visual communication. Media emerging from the Electro-mechanical era (film/TV/video) present fixed spatio-temporal linearity and material conditions which objectify and render passive viewer and process. The problematic aspects of cinematic communication were addressed by Latin American filmmakers of the Third Cinema movement. Their concerns and approach presaged and assisted an understanding of the radical redefinition of audio-visual communication possible with digital databases. The conceptual and aesthetic aspirations of Third Cinema artists such as Julio Garcia Espinosa and Fernando Solanas were ultimately contradictory to linear media and find their fitting medium in digital modular construction. The materiality of database expression lacks an intrinsic temporal or spatial state and permits a more dynamic and multidirectional set of power relationships between author/s, piece, viewer/s. Other important referents for contextualising database art are modern art practitioners that rejected linear representational space and fractured the centrality of authorship. The author's own work, ...two, three, many Guevaras, an exploratory database environment, embraces the redefinition of process as artistic expression, the empowerment of interacting generative forces, and serves to illustrate the revolutionary potential of the new media.     

A Note on the Ohya-Masuda Quantum Algorithm

We analyze the Ohya-Masuda quantum algorithm that solves the so-called satisfiability problem, which is an NP-complete problem of the complexity theory. We distinguish three steps in the algorithm, and analyze the second step, in which a coherent superposition of states (a pure state) transforms into an incoherent mixture presented by a density matrix. We show that, if nonideal (in analogy with nonideal quantum measurement), this transformation can make the algorithm to fail in some cases. On this basis we give some general notions on the physical implementation of the Ohya-Masuda algorithm.     

Recognition of handwritten musical notes by a modified Neocognitron

A neural network for recognition of handwritten musical notes, based on the well-known Neocognitron model, is described. The Neocognitron has been used for the what pathway (symbol recognition), while contextual knowledge has been applied for the where (symbol placement). This way, we benefit from dividing the process for dealing with this complicated recognition task. Also, different degrees of intrusiveness in learning have been incorporated in the same network: More intrusive supervised learning has been implemented in the lower neuron layers and less intrusive in the upper one. This way, the network adapts itself to the handwriting of the user. The network consists of a 13×49 input layer and three pairs of simple and complex neuron layers. It has been trained to recognize 20 symbols of unconnected notes on a musical staff and was tested with a set of unlearned input notes. Its recognition rate for the individual unseen notes was up to 93%, averaging 80% for all categories. These preliminary results indicate that a modified Neocognitron could be a good candidate for identification of handwritten musical notes.     

Crypt-equivalent algebraic specifications

Summary Equivalence is a fundamental notion for the semantic analysis of algebraic specifications. In this paper the notion of crypt-equivalence is introduced and studied w.r.t. two loose approaches to the semantics of an algebraic specification T: the class of all first-order models of T and the class of all term-generated models of T. Two specifications are called crypt-equivalent if for one specification there exists a predicate logic formula which implicitly defines an expansion (by new functions) of every model of that specification in such a way that the expansion (after forgetting unnecessary functions) is homologous to a model of the other specification, and if vice versa there exists another predicate logic formula with the same properties for the other specification. We speak of first-order crypt-equivalence if this holds for all first-order models, and of inductive crypt-equivalence if this holds for all term-generated models. Characterizations and structural properties of these notions are studied. In particular, it is shown that first order crypt-equivalence is equivalent to the existence of explicit definitions and that in case of positive definability two first-order crypt-equivalent specifications admit the same categories of models and homomorphisms. Similarly, two specifications which are inductively crypt-equivalent via sufficiently complete implicit definitions determine the same associated categories. Moreover, crypt-equivalence is compared with other notions of equivalence for algebraic specifications: in particular, it is shown that first-order cryptequivalence is strictly coarser than abstract semantic equivalence and that inductive crypt-equivalence is strictly finer than inductive simulation equivalence and implementation equivalence.     

Solution of trim-loss problem by an integrated simulated annealing and ordinal optimization approach

This work presents a novel optimization method capable of integrating ordinal optimization (OO) and simulated annealing (SA). A general regression neural network (GRNN) is trained using available data to generate a rough model that approximates the response surface in the feasible domain. A set of good enough candidates are generated by conducting a (SA) search on this rough model. Only candidates accepted by the SA search are actually tested by evaluating their true objective functions. The GRNN model is then updated using these new data. The procedure is repeated until a specified number of tests have been performed. The method (SAOO+GRNN) is tested the well-known paper trim loss problem. SAOO+GRNN approach can substantially reduce the number of function calls and the computing time far below those of simple ordinal optimization method with such as horse race selection rule, as well as straightforward simulated annealing.     

Rapid Concept Learning for Mobile Robots

Concept learning in robotics is an extremely challenging problem: sensory data is often high dimensional, and noisy due to specularities and other irregularities. In this paper, we investigate two general strategies to speed up learning, based on spatial decomposition of the sensory representation, and simultaneous learning of multiple classes using a shared structure. We study two concept learning scenarios: a hallway navigation problem, where the robot has to induce features such as opening or wall. The second task is recycling, where the robot has to learn to recognize objects, such as a trash can. We use a common underlying function approximator in both studies in the form of a feedforward neural network, with several hundred input units and multiple output units. Despite the high degree of freedom afforded by such an approximator, we show the two strategies provide sufficient bias to achieve rapid learning. We provide detailed experimental studies on an actual mobile robot called PAVLOV to illustrate the effectiveness of this approach.     

Continuous reductions among combinatorial optimization problems

Summary Many reductions among combinatorial problems are known in the context of NP-completeness. These reductions preserve the optimality of solutions. However, they may change the relative error of approximative solutions dramatically. In this paper, we apply a new type of reductions, called continuous reductions. When one problem is continuously reduced to another, any approximation algorithm for the latter problem can be transformed into an approximation algorithm for the former. Moreover, the performance ratio is preserved up to a constant factor. We relate the problem Minimum Number of Inverters in CMOS-Circuits, which arises in the context of logic synthesis, to several classical combinatorial problems such as Maximum Independent Set and Deletion of a Minimum Number of Vertices (Edges) in Order to Obtain a Bipartite (Partial) Subgraph.     

The Structure of Locally Orderless Images

We propose a representation of images in which a global, but not a local topology is defined. The topology is restricted to resolutions up to the extent of the local region of interest (ROI). Although the ROI's may contain many pixels, there is no spatial order on the pixels within the ROI, the only information preserved is the histogram of pixel values within the ROI's. This can be considered as an extreme case of a textel (texture element) image: The histogram is the limit of texture where the spatial order has been completely disregarded. We argue that locally orderless images are ubiquitous in perception and the visual arts. Formally, the orderless images are most aptly described by three mutually intertwined scale spaces. The scale parameters correspond to the pixellation (inner scale), the extent of the ROI's (outer scale) and the resolution in the histogram (tonal scale). We describe how to construct locally orderless images, how to render them, and how to use them in a variety of local and global image processing operations.