New Bounds for Multidimensional Packing

Abstract. New upper and lower bounds are presented for a multidimensional generalization of bin packing called box packing. Several variants of this problem, including bounded space box packing, square packing, variable-sized box packing and resource augmented box packing are also studied. The main results, stated for d=2 , are as follows: a new upper bound of 2.66013 for online box packing, a new 14/9 + ɛ polynomial time offline approximation algorithm for square packing, a new upper bound of 2.43828 for online square packing, a new lower bound of 1.62176 for online square packing, a new lower bound of 2.28229 for bounded space online square packing and a new upper bound of 2.32571 for online two-sized box packing.     

Compact disc standards: an introductory overview

The success of the compact disc (CD) as a storage medium for digital audio has, over the last ten years, resulted in a number of initiatives to use the CD for other applications as well, e.g., as read-only memory for computers, as a storage medium for audio-visual material for multimedia applications, and as a storage medium for photographs. Each of these applications poses additional requirements on how the corresponding information is stored and retrieved, resulting in a range of different CD standards. The functional specifications of these standards are each given a specific color for ease of reference: the Red Book for CD-DA, the Yellow Book for CD-ROM, the Green Book for CD-I, etc. This paper aims at giving an overview of the various CD standards by explaining what is specified in each of the colored books and by indicating how they relate to one another.     

Local path planning using a new artificial potential function composition and its analytical design guidelines

This paper presents a new framework for path planning based on artificial potential functions (APFs). In this scheme, the APFs for path planning have a multiplicative and additive composition between APFs for goal destination and APFs for obstacle avoidance, unlike conventional composition where the APF for obstacle avoidance is added to the APF for goal destination. In particular, this paper presents a set of analytical guidelines for designing potential functions to avoid local minima for a number of representative scenarios based on the proposed framework for path planning. Specifically the following cases are addressed: (i) a non-reachable goal problem (a case in which the potential of the goal is overwhelmed by the potential of an obstacle), (ii) an obstacle collision problem (a case in which the potential of the obstacle is overwhelmed by the potential of the goal) and (iii) a narrow passage problem (a case in which the potential of the goal is overwhelmed by the potential of two obstacles). The example results for each case show that the proposed scheme can effectively construct a path-planning system with the capability of reaching a goal and avoiding obstacles despite possible local minima.     

Binorm—a fortran subroutine to calculate the percentiles of a standardized binormal distribution

BINORM is a FORTRAN subroutine for calculating the percentiles of a standardized binormal distribution. By using a linear transformation, the percentiles of a binormal distribution can be obtained. The percentiles of a binormal distribution are useful for plotting purposes, for establishing confidence intervals, and for sampling from a mixed population that consists of two normal distributions.     

Database design with user-definable modelling concepts

Modelling is an integral part of engineering processes. Consequently, database design for engineering applications should take into account the modelling concepts used by engineers. On the other hand, these applications exhibit a wide diversity of modelling concepts. Rather than consolidating these into one single semantic data model one should aim for correspondingly specialized semantic models. This paper takes a constructive approach to developing such specialized models by proposing an Extensible Semantic Model (ESM) as the basis for declaring specialized semantic data models. The paper introduces a computerized environment for database design based on an ESM, and discusses the consequences of the ESM for a number of design tools: the need for a formal definition of the notion of modelling concept in order to have reliable and precise foundation for the extensions, declarative techniques for quickly introducing graphical representations for new concepts and for using them during schema design, conceptual-level test data generation for a designer-oriented evaluation of designs, and optimization techniques to control the wide latitude in mapping a conceptual schema to a logical schema. First experiences seem to point to considerable productivity gains during database design.     

Automating Test Case Selection in Model-Based Software Product Line Development

We address the problem of how to select test cases for products in a controlled model-based software product line development process. CVL, the common variability language, gives a framework for materialisation of product models from a given base model, variability model and resolution model. From such product models, software products can be derived. In practise, test case development for the product line often is independent from the product development. Therefore, the problem arises which test cases can be applied to which products. In particular, the question is whether a test case for one speci c product can be also used for a "similar" product. In this paper, we show how the expected outcome of a test case to a product in a model-based software product line development can be determined. That is, we give a procedure for assigning the outcome of a given test case on an arbitrary member of a software product line. We recall the relevant de nitions for software product line engineering, describe our approach, and demonstrate it with the example of a product line of super-automatic espresso machines.     

A systemic approach to integrated E-maintenance of large engineering plants

Large engineering plants (LEPs) have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance. Although this requirement is appreciated to varying degrees by asset owners, applied research leading to a systematic development of such a maintenance strategy is the need of the day. Such a strategy should also adopt a wholesome ``systemic' approach so that the realization of the overall objectives of maintenance is maximized. E-maintenance has several potential benefits for large engineering plants. In this paper, a three pronged strategy is suggested for the successful implementation of e-maintenance for LEPs. Firstly, an integrated condition and time based maintenance framework is proposed for LEPs. Secondly, reference is drawn to models for condition and time based maintenance at systemic levels. As a part of the ab initio development of a condition monitoring system for a LEP, one of the characteristics of the condition monitoring system, namely, predictability, is discussed in detail as a sample for a systemic study. Thirdly, emphasis is laid on the information and expertise available in the domain of plant design, operation and maintenance and the same is tapped for incorporation in maintenance decision making.     

Reusing Primitive and Acquired Motion Knowledge for Gait Generation of a Six-legged Robot Using Genetic Programming

There has been growing interest in motion planning problems for mobile robots. In this field, the main research is to generate a motion for a specific robot and task without previously acquired motions. However it is too wasteful not to use hard-earned acquired motions for other tasks. Here, we focus on a mechanism of reusing acquired motion knowledge and study a motion planning system able to generate and reuse motion knowledge. In this paper, we adopt a tree-based representation for expressing knowledge of motion, and propose a hierarchical knowledge for realizing a reuse mechanism. We construct a motion planning system using hierarchical knowledge as motion knowledge and using genetic programming as a learning method. We apply a proposed method for the gait generation task of a six-legged locomotion robot and show its availability with computer simulation.     

LIY: learn-it-yourself software interfaces

An increasing number of people are becoming users of unfamiliar software. They can be genuinely "new" computer users or part of a growing group who are transferring skills and knowledge from a familiar product such as a word processor to a functionally similar, but different, unfamiliar one. The problem for users in this position is that they do not have access to training courses to teach them how to use such software and are usually forced to rely on text-based documentation. LIY is a method for producing computer-based tutorials to teach the user ofasoftware product.This paper describes how LIY is, in turn, (1) a method for application system design which recognizes the need for tutorial design (a task analysis and user interface specification provide information structures that are passed to the tutorial designer); (2) a support environment for the tutorial designer (in addition to prompting for courseware for nodes in the task analysis, LIY provides a ready-made rule base for constraining the degree of learner control available while the tutorial is in use. The designer is able to tailor this rule base for a specific tutorial); and (3) a tutorial delivery environment (the tutorial adapts to individual learners and offers a degree of learner control).     

Nonparametric estimation of pair-copula constructions with the empirical pair-copula

A pair-copula construction is a decomposition of a multivariate copula into a structured system, called regular vine, of bivariate copulae or pair-copulae. The standard practice is to model these pair-copulae parametrically, inducing a model risk, with errors potentially propagating throughout the vine structure. The empirical pair-copula provides a nonparametric alternative, which is conjectured to still achieve the parametric convergence rate. Its main advantage for the user is that it does not require the choice of parametric models for each of the pair-copulae constituting the construction. It can be used as a basis for inference on dependence measures, for selecting an appropriate vine structure, and for testing for conditional independence.     

Classification of electroencephalogram signal for the detection of epilepsy using Innovative Genetic Programming

Epilepsy, sometimes called seizure disorder, is a neurological condition that justifies itself as a susceptibility to seizures. A seizure is a sudden burst of rhythmic discharges of electrical activity in the brain that causes an alteration in behaviour, sensation, or consciousness. It is essential to have a method for automatic detection of seizures, as these seizures are arbitrary and unpredictable. A profound study of the electroencephalogram (EEG) recordings is required for the accurate detection of these epileptic seizures. In this study, an Innovative Genetic Programming framework is proposed for classification of EEG signals into seizure and nonseizure. An empirical mode decomposition technique is used for the feature extraction followed by genetic programming for the classification. Moreover, a method for intron deletion, hybrid crossover, and mutation operation is proposed, which are responsible for the increase in classification accuracy and a decrease in time complexity. This suggests that the Innovative Genetic Programming classifier has a potential for accurately predicting the seizures in an EEG signal and hints on the possibility of building a real‐time seizure detection system.     

Robust image registration by increment sign correlation

A novel and robust statistic as a similarity measure for robust image registration is proposed. The statistic is named as increment sign correlation because it is based on the average evaluation of incremental tendency of brightness in adjacent pixels. It is formalized to be a binary distribution or a Gaussian distribution for a large image size through statistical analysis and modeling. By utilizing the proposed statistical model, for example, we can theoretically determine a reasonable value of threshold for verification of matching. This sign correlation can also be proved to expectedly have the constant value 0.5 for any uncorrelated images to a template image, and then the property of the constancy can be utilized to analyze the high robustness for occlusion. The good performance for the case of saturation or highlight can also be proved through theoretical analysis and fundamental experiments. A basic algorithm for image scanning, search and registration over a large scene is represented with a technique for a fast version by the branch-and-bound approach. Many experimental evidences with real images are provided and discussed.     

Reliable detection and separation of components for solid objects defined with scalar fields

The detection of the number of disjoint components is a well-known procedure for surface objects. However, this problem has not been solved for solid models defined with scalar fields in the so-called implicit form. In this paper, we present a technique which allows for detection of the number of disjoint components with a predefined tolerance for an object defined with a single scalar function. The core of the technique is a reliable continuation of the spatial enumeration based on the interval methods. We also present several methods for separation of components using set-theoretic operations for further handling these components individually in a solid modelling system dealing with objects defined with scalar fields.     

Necessary and sufficient condition for stabilizability of discrete-time linear switched systems: A set-theory approach

In this paper, the stabilizability of discrete-time linear switched systems is considered. Several sufficient conditions for stabilizability are proposed in the literature, but no necessary and sufficient. The main contributions are the necessary and sufficient conditions for stabilizability based on the set-theory and the characterization of a universal class of Lyapunov functions. An algorithm for computing the Lyapunov functions and a procedure to design the stabilizing switching control law are provided, based on such conditions. Moreover, a sufficient condition for non-stabilizability for switched system is presented. Several academic examples are given to illustrate the efficiency of the proposed results. In particular, a Lyapunov function is obtained for a system for which the Lyapunov–Metzler condition for stabilizability does not hold.     

Scalable distributed on-the-fly symbolic model checking

This paper presents a scalable method for parallel symbolic on-the-fly model checking in a distributed memory environment. Our method combines a scheme for on-the-fly model checking for safety properties with a scheme for scalable reachability analysis. We suggest an efficient, BDD-based algorithm for a distributed construction of a counterexample. The extra memory requirement for counterexample generation is evenly distributed among the processes by a memory balancing procedure. At no point during computation does the memory of a single process contain all the data. This enhances scalability. Collaboration between the parallel processes during counterexample generation reduces memory utilization for the backward step. We implemented our method on a standard, loosely- connected environment of workstations, using a high-performance model checker. Our initial performance evaluation, carried out on several large circuits, shows that our method can check models that are too large to fit in the memory of a single node. Our on-the-fly approach may find counterexamples even when the model is too large to fit in the memory of the parallel system.     

A formal framework for connective stability of highly decentralized cooperative negotiations

Multiagent cooperative negotiation is a promising technique for modeling and controlling complex systems. Effective and flexible cooperative negotiations are especially useful for open complex systems characterized by high decentralization (which implies a low amount of exchanged information) and by dynamic connection and disconnection of agents. Applications include ad hoc network management, vehicle formation, and physiological model combination. To obtain an effective control action, the stability of the negotiation, namely the guarantee that an agreement will be eventually reached, is of paramount importance. However, the techniques usually employed for assessing the stability of a negotiation can be hardly applied in open scenarios. In this paper, whose nature is mainly theoretical, we make a first attempt towards engineering stable cooperative negotiations proposing a framework for their analysis and design. Specifically, we present a formal protocol for cooperative negotiations between a number of agents and we propose a criterion for negotiation stability based on the concept of connective stability. This is a form of stability that accounts for the effects of structural changes on the composition of a system and that appears very suitable for multiagent cooperative negotiations. To show its possible uses, we apply our framework for connective stability to some negotiations taken from literature.     

Statically safe program generation with SafeGen

SafeGen is a meta-programming language for writing statically safe generators of Java programs. If a program generator written in SafeGen passes the checks of the SafeGen compiler, then the generator will only generate well-formed Java programs, for any generator input. In other words, statically checking the generator guarantees the correctness of any generated program, with respect to static checks commonly performed by a conventional compiler (including type safety, existence of a superclass, etc.). To achieve this guarantee, SafeGen supports only language primitives for reflection over an existing well-formed Java program, primitives for creating program fragments, and a restricted set of constructs for iteration, conditional actions, and name generation. SafeGen’s static checking algorithm is a combination of traditional type checking for Java, and a series of calls to a theorem prover to check the validity of first-order logical sentences, constructed to represent well-formedness properties of the generated program under all inputs. The approach has worked quite well in our tests, providing proofs for correct generators or pointing out interesting bugs.     

Intrinsic Random Fields and Image Deformations

The stochastic structure of images, especially individual medical images as they are reconstructed nowadays from arrays of medical imaging sensors, is becoming steadily better understood. Less attention has been paid to the parallel notion of estimation error for the deformations that convey relations among these images, such as localized abnormality or growth prediction. The dominant current formalism for the biostatistics of deformations deals solely with the shape of a set of landmarks parameterizing the deformation, not otherwise with its behaviour inbetween the landmarks. This paper attempts to fit a rigorous stochastic model for a deformation between landmarks and to assess the error of the fitted deformation. The relation between two images is modelled as a stochastic deformation, i.e. as an identity map plus a stochastic process whose value at every point is a vector-valued displacement. There are two common strategies for fitting deformations given information at a set of landmarks. One involves minimizing a roughness penalty, e.g. for a thin-plate spline, and another involves prediction for a stochastic process, e.g. for a self-similar intrinsic random field. The stochastic approach allows parameter estimation and confidence limits for the predicted deformation. An application is presented from a study of breast images and how they deform as a function of the imaging procedure.     

A Scalable Toolkit for Designing Multimedia Authoring Environments

This paper introduces Kaomi, a scalable toolkit for designing authoring environments of multimedia documents. The underlying concept is to provide the designer of multimedia applications with a fast method to get an authoring system based on a set of synchronized views (the presentation view for displaying the document, the scenario view for showing the temporal organization of the document, ...) so that each view is the support of editing actions. Kaomi is flexible enough to support a variety of multimedia documents declarative formats. It is indeed a scalable toolkit since it provides facilities for extending and/or for modifying the resulting authoring environment. In addition, cross-platform portability is provided which allows operation in the heterogenous Internet environment. The use of Kaomi is mainly described through the design of two authoring environments: one for authoring a sub-set of the Smil standard of the W3C and the other one for Madeus, a constraint based multimedia language.