Characterization of desirable properties of general database decompositions

The classical theory of acyclicity of universal relational schemata identifies a set of desirable properties of such schemata, and then shows that all of these properties are equivalent to one another, and in turn equivalent to certain acyclicity characterizations of a hypergraph underlying the schema. The desirable properties include the simplicity of constraints, the correctness of certain efficient query evaluation algorithms, and the complexity of maintaining the integrity of a decomposed database. The principal result of this paper is to show that the essence of this result may be extended to a much more general setting; namely, that in which database schemata are just sets and database mappings just functions. Rather than identifying a single desirability class, our work shows that there are several, all of which collapse to a common group when restricted to the universal relational setting. Particularly, the classical notions of pairwise consistency implies global consistency and hypergraph acyclicity are not equivalent in the general case, but rather are independent of each other, and may be considered separately or in combination, to yield varying strengths of desirability.     

Real-time Collision-free Path Planning of Robot Manipulators using Neural Network Approaches

In this paper, a novel neural network approach to real-time collision-free path planning of robot manipulators in a nonstationary environment is proposed, which is based on a biologically inspired neural network model for dynamic trajectory generation of a point mobile robot. The state space of the proposed neural network is the joint space of the robot manipulators, where the dynamics of each neuron is characterized by a shunting equation or an additive equation. The real-time robot path is planned through the varying neural activity landscape that represents the dynamic environment. The proposed model for robot path planning with safety consideration is capable of planning a real-time comfortable path without suffering from the too close nor too far problems. The model algorithm is computationally efficient. The computational complexity is linearly dependent on the neural network size. The effectiveness and efficiency are demonstrated through simulation studies.     

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.     

Minimization of norms and logarithmic norms by diagonal similarities

It is a commonly occurring problem to find good norms · or logarithmic norms (·) for a given matrix in the sense that they should be close to respectively the spectral radius (A) and the spectral abscissa (A). Examples may be the certification thatA is convergent, i.e. (A)A<1 or stable, i.e. (A)(A)<0. Often the ordinary norms do not suffice and one would like to try simple modifications of them such as using an ordinary norm for a diagonally transformed matrix. This paper treats this problem for some of the ordinary norms.

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Minimisierung von Normen und Logarithmischen Normen durch Diagonale Transformationen

Zusammenfassung Ein oft vorkommendes praktisches Problem ist die Konstruktion von guten Normen · und logarithmischen Normen (·) für eine gegebene MatrixA. Mit gut wird dann verstanden, daß A den Spektralradius (A)=max |₁| und (A) die Spektralabszisse (A)=max Re _i gut approximieren. Beispiele findet man für konvergente Matrizen wo (A)A<1 gewünscht ist, und für stabile Matrizen wo (A)(A)<0 zu zeigen ist. Wir untersuchen hier, wie weit man mit Diagonaltransformationen und dengewöhnlichsten Normen kommen kann.

     

A multiprocessor working as a Fault-Tolerant cellular automaton

A memory-coupled multiprocessor—well suited to bit-wise operation—can be utilized to operate as a 1024 items cellular processing unit. Each processor is working on 32 bits and 32 such processors are combined to a multiprocessor. The information is stored in vertical direction, as it is defined and described in earlier papers [1] on vertical processing. The two-dimensional array (32 times 32 bits) is composed of the 32 bit-machine-words of the coupled processors on the one hand and of 32 processors in nearest-neighbour-topology on the other hand. The bit-wise cellular operation at one of the 1024 points is realized by the program of the processor—possibly assisted by appropriate microprogam sequences.Dedicated to Professor Willard L. Miranker on the occasion of his 60th birthday     

Interpretations of open default theories in non-monotonic logics

It is shown that the translation of an open default into a modal formula x(L(x)LM ₁ (x)...LM _m (x)w(x)) gives rise to an embedding of open default systems into non-monotonic logics.     

Understanding Computer-based “Informated” Environments

The paper introduces the concept of Computer-based Informated Environments (CBIEs) to indicate an emergent form of work organisation facilitated by information technology. It first addresses the problem of inconsistent meanings of the informate concept in the literature, and it then focuses on those cases which, it is believed, show conditions of plausible informated environments. Finally, the paper looks at those factors that when found together contribute to building a CBIE. It makes reference to CBIEs as workplaces that comprise a non-technocentric perspective and questions whether CBIEs truly represent an anthropocentric route of information technology.     

Behaviour Synthesis of the Erect Stance for a Biped Control

In this paper we use free fall approach to develop a high level control/command strategy for a bipedal robot called BIPMAN, based on a multi-chain mechanical model with a general control architecture. The strategy is composed of three levels: the Legs and arms level, the Coordinator level and the Supervisor level. The Coordinator level is devoted to controlling leg movements and to ensure the stability of the whole biped. Actually perturbation effects threaten the equilibrium of the human robot and can only be compensated using a dynamic control strategy. This one is based on dynamic stability studies with a center of mass acceleration control and a force distribution on each leg and arm. Free fall in the gravity field is assumed to be deeply involved in the human locomotor control. According to studies of this specific motion through a direct dynamic model,the notion of equilibrium classes is introduced. They allow one to define time intervals in which the biped is able to maintain its posture. This notion is used for the definition of a reconfigurable high level control of the robot.     

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.     

On generators and generative capacity of EOL forms

Summary In this paper we study the generative capacity of EOL forms from two different points of view. On the one hand, we consider the generative capacity of special EOL forms which one could call linear like and context free like, establishing the existence of a rich variety of non-regular sub-EOL language families. On the other hand, we propose the notion of a generator L of a language family We mean by this that any synchronized EOL system generating L generates — if understood as an EOL form — all languages of . We characterize the generators of the family of regular languages, and prove that other well known language families do not have generators.Partially supported under NSE Research Council of Canada, grant No. A-7700     

Asymptotic Stability of Nonlinear Pulse Systems

A nonlinear pulse system and its equivalent nonlinear system derived through substitution of the pulse element by a static characteristic are studied. For high pulsation frequency, the equilibrium state of the pulse system is shown to be asymptotically stable if the equivalent linearized system is asymptotically stable.     

Directional derivatives of the maximum function

Directional differentiability of the function (x) = sup{f(x, u), u U} is proved for a class of smooth functions f. The result is applied to study the directional differentiability of the function (x) = sup{f(x, y), y F(x)}, where F is a multivalued mapping.Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 171–173, March–April, 1992.     

Constraint Propagation and Decomposition Techniques for Highly Disjunctive and Highly Cumulative Project Scheduling Problems

In recent years, constraint satisfaction techniques have been successfully applied to disjunctive scheduling problems, i.e., scheduling problems where each resource can execute at most one activity at a time. Less significant and less generally applicable results have been obtained in the area of cumulative scheduling. Multiple constraint propagation algorithms have been developed for cumulative resources but they tend to be less uniformly effective than their disjunctive counterparts. Different problems in the cumulative scheduling class seem to have different characteristics that make them either easy or hard to solve with a given technique. The aim of this paper is to investigate one particular dimension along which problems differ. Within the cumulative scheduling class, we distinguish between highly disjunctive and highly cumulative problems: a problem is highly disjunctive when many pairs of activities cannot execute in parallel, e.g., because many activities require more than half of the capacity of a resource; on the contrary, a problem is highly cumulative if many activities can effectively execute in parallel. New constraint propagation and problem decomposition techniques are introduced with this distinction in mind. This includes an O(n²) edge-finding algorithm for cumulative resources (where n is the number of activities requiring the same resource) and a problem decomposition scheme which applies well to highly disjunctive project scheduling problems. Experimental results confirm that the impact of these techniques varies from highly disjunctive to highly cumulative problems. In the end, we also propose a refined version of the edge-finding algorithm for cumulative resources which, despite its worst case complexity in O(n³) , performs very well on highly cumulative instances.     

Enhancing the performance of an agent-based manufacturing system through learning and forecasting

Agent-based technology has been identified as an important approach for developing next generation manufacturing systems. One of the key techniques needed for implementing such advanced systems will be learning. This paper first discusses learning issues in agent-based manufacturing systems and reviews related approaches, then describes how to enhance the performance of an agent-based manufacturing system through learning from history (based on distributed case-based learning and reasoning) and learning from the future (through system forecasting simulation). Learning from history is used to enhance coordination capabilities by minimizing communication and processing overheads. Learning from the future is used to adjust promissory schedules through forecasting simulation, by taking into account the shop floor interactions, production and transportation time. Detailed learning and reasoning mechanisms are described and partial experimental results are presented.     

Exact upper bounds of the probability of failure in a time interval in the case of incomplete information on the distribution function

Exact upper bounds are obtained for the probability F() - F(u), 0 < u < < , on the set of distribution functions F(x) of nonnegative random variables with unimodal density with an arbitrary mode m 0 and one or two fixed first moments.Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 72–83, September–October 2004.     

Nonblockability of Switches with the Cayley Graph Structure for Serial Transfer of Data Blocks. Generalized Hypercubes and Multidimensional Grids

A general method of conflictless arbitrary permutation of large data elements that can be divided into a multitude of smaller data blocks was considered for switches structured as the Cayley graphs. The method was specified for arbitrary permutations in the generalized hypercubes and multidimensional grids, and their characteristics were considered.     

An extension of the theory of learning systems

Summary The author's inquiry [1] on learning systems is generalized in the following respects: The process of learning, instead of coming to an end when the learning goal has been reached, is supposed to last for ever, so that the above definitive learning as well as phenomena such as forgetting, re-learning, changing the goal etc. become describable.We take over the notion of semi-uniform solvability of a set of learning problems (2.2), but now (trivial cases excluded) the whole capacity of a learning system is never s. u. solvable. Finite such sets are. The notion of a solving-basis of some is introduced and we can state necessary conditions that possess such a basis (2.14), so that examples of sets without a basis can be provided. On the other hand, any s. u. solvable has as basis. The notion of uniform solvability (3.1) reinforces that of s. u. solvability, and there are given sufficient conditions for to be uniformly solvable (3.6). In some finite cases, s. u. solvability, existence of a basis and uniform solvability coincide (3.7–3.9). At last we give the construction for the weakest learning system solving a uniformly solvable problem set (3.12–3.19).Eine deutsche Fassung wurde am 30. Mai 1972 eingereicht.     

Paramorphisms

Catamorphisms are functions on an initial data type (an inductively defined domain) whose inductive definitional pattern mimics that of the type. These functions have powerful calculation properties by which inductive reasoning can be replaced by equational reasoning. This paper introduces a generalisation of catamorphisms, dubbed paramorphisms. Paramorphisms correspond to a larger class of inductive definition patterns; in fact, we show that any function defined on an initial type can be expressed as a paramorphism. In spite of this generality, it turns out that paramorphisms have calculation properties very similar to those of catamorphisms. In particular, we prove a Unique Extension Property and a Promotion Theorem for paramorphisms.     

A model implementation for protective domains

A combination hardware/software mechanism is presented which supports very general capabilities for the protection of and controlled access to sharable information structures. It is defined through symbolic algorithms in terms of the dedicated model hardware. The model centers on two key concepts, that of thetenant, who is a storage holding entity, and that of thedomain, which is an information accessing entity. The domain, defined as a capsular collection of mutually accessible information structures having a single common external protective interface, is an integral part of the hardware logic. It is contended that the definition of a mechanism to enforce access authorizations must include an underlying philosophy specifying the conditions under which such access authorizations may be granted. Such a philosophy is suggested. It is based on theprinciple of ownership according to which any area of storage is at all times held by a single tenant who has the exclusive right to grant/revoke access privileges to his proprietary information structures, i.e., information residing in proprietary storage.This is an extensively revised version of a paper presented under the title A Computer System Model for Controlled Sharing of Information at ONLINE72, September 1972, Brunel University, Uxbridge, Middlesex, England. Republished by permission of ONLINE72.Work reported in this paper is of a theoretical nature and may not be construed to imply any product commitment by the Digital Equipment Corporation, Maynard, Massachusetts.     

Probabilistic Tracking with Exemplars in a Metric Space

A new, exemplar-based, probabilistic paradigm for visual tracking is presented. Probabilistic mechanisms are attractive because they handle fusion of information, especially temporal fusion, in a principled manner. Exemplars are selected representatives of raw training data, used here to represent probabilistic mixture distributions of object configurations. Their use avoids tedious hand-construction of object models, and problems with changes of topology.Using exemplars in place of a parameterized model poses several challenges, addressed here with what we call the Metric Mixture (M²) approach, which has a number of attractions. Principally, it provides alternatives to standard learning algorithms by allowing the use of metrics that are not embedded in a vector space. Secondly, it uses a noise model that is learned from training data. Lastly, it eliminates any need for an assumption of probabilistic pixelwise independence.Experiments demonstrate the effectiveness of the M² model in two domains: tracking walking people using chamfer distances on binary edge images, and tracking mouth movements by means of a shuffle distance.