Design of phononic materials/structures for surface wave devices using topology optimization

We develop a topology optimization approach to design two- and three-dimensional phononic (elastic) materials, focusing primarily on surface wave filters and waveguides. These utilize propagation modes that transmit elastic waves where the energy is contained near a free surface of a material. The design of surface wave devices is particularly attractive given recent advances in nano- and micromanufacturing processes, such as thin-film deposition, etching, and lithography, which make it possible to precisely place thin film materials on a substrate with submicron feature resolution. We apply our topology optimization approach to a series of three problems where the layout of two materials (silicon and aluminum) is sought to achieve a prescribed objective: (1) a grating to filter bulk waves of a prescribed frequency in two and three dimensions, (2) a surface wave device that uses a patterned thin film to filter waves of a single or range of frequencies, and (3) a fully three-dimensional structure to guide a wave generated by a harmonic input on a free surface to a specified output port on the surface. From the first to the third example, the resulting topologies increase in sophistication. The results demonstrate the power and promise of our computational framework to design sophisticated surface wave devices.     

Machine scheduling with job class setup and delivery considerations

We study machine scheduling problems in which the jobs belong to different job classes and they need to be delivered to customers after processing. A setup time is required for a job if it is the first job to be processed on a machine or its processing on a machine follows a job that belongs to another class. Processed jobs are delivered in batches to their respective customers. The batch size is limited by the capacity of the delivery vehicles and each shipment incurs a transport cost and takes a fixed amount of time. The objective is to minimize the weighted sum of the last arrival time of jobs to customers and the delivery (transportation) cost. For the problem of processing jobs on a single machine and delivering them to multiple customers, we develop a dynamic programming algorithm to solve the problem optimally. For the problem of processing jobs on parallel machines and delivering them to a single customer, we propose a heuristic and analyze its performance bound.     

A superscalar simulation employing poisson distributed stalls

This paper presents a statistical approach to estimating the performance of a superscalar processor. Traditional trace-driven simulators can take a large amount time to conduct a performance evaluation of a machine, especially as the number of instructions increases. The result of this type of simulation is typically tied to the particular trace that was run. Elements such as dependencies, delays, and stalls are all a direct result of the particular trace being run, and can differ from trace to trace. This paper describes a model designed to separate simulation results from a specific trace. Rather than running a trace-driven simulation, a statistical model is employed, more specifically a Poisson distribution, to predict how these types of delay affects performance. Through the use of this statistical model, a performance evaluation can be conducted using a general code model, with specific stall rates, rather than a particular code trace. This model allows simulations to quickly run tens of millions of instructions and evaluate the performance of a particular micro-architecture while at the same time, allowing the flexibility to change the structure of the architecture.     

Holarchy formation and optimization in holonic manufacturing systems with contract net

Holonic manufacturing systems (HMS) is based on the notion of holon, an autonomous, cooperative and intelligent entity to provide a econfigurable, flexible and decentralized manufacturing environment to respond to changing needs and opportunities. A set of holons that cooperate to achieve a goal forms a holarchy. How to design a mechanism to form a holarchy to achieve a goal while minimizing the overall cost is a challenge. The objectives of this paper are to propose models and develop collaborative algorithms to guide the holons to form a holarchy to coherently move toward the desired goal state ultimately. We adopt contract net protocol (CNP) to model mutual selection of holons in forming a holarchy. We formulate a holarchy optimization problem to minimize the cost subject to the feasibility constraints. To analyze the feasibility of a holarchy, a Petri net (PN) model is proposed. As classical PN models do not take into account the cost involved in firing transitions, we augment the PN model with cost functions in the problem formulation. Due to the distributed architecture of HMS, the internal structure of each potential holarchy that acts as bidder in CNP is not available to the manager. A key issue is to determine the feasibility of a holarchy without constructing the whole PN model of the given hierarchy. We study the feasible conditions for a holarchy and propose a collaborative algorithm to analyze the feasibility and award contracts to holons without constructing the whole model of a holarchy.     

A self-adaptation scheme for workflow management in multi-agent systems

Business processes, operational environment, variability of resources and user needs may change from time to time. An effective workflow management software system must be able to accommodate these changes. The ability to dynamically adapt to changes is a key success factor for workflow management systems. Holonic multi-agent systems (HMS) provide a flexible and reconfigurable architecture to accommodate changes based on dynamic organization and collaboration of autonomous agents. Although HMS provides a potential architecture to accommodate changes, the dynamic organization formed in HMS poses a challenge in the development of a new software development methodology to dynamically compose the services and adapt to changes as needed. This motivates us to study and propose a methodology to design self-adaptive software systems based on the HMS architecture. In this paper, we formulate a workflow adaptation problem (WAP) and propose an interaction mechanism based on contract net protocol (CNP) to find a solution to WAP to compose the services based on HMS. The interaction mechanism relies on a service publication and discovery scheme to find a set of task agents and a set of actor agents to compose the required services in HMS. We propose a viable self-adaptation scheme to reconfigure the agents and the composed services based on cooperation of agents in HMS to accommodate the changes in workflow and capabilities of actors. We propose architecture for our design methodology and present an application scenario to illustrate our idea.     

Learning criterion and inductive behaviour

Inductive behaviours may be classified according to their aim. We intend to show that there are at least two kinds of inductive behaviours. Most of the publications seem to take into consideration only one of these: to copy as exactly as possible the behaviour of a probability process. After a brief discussion to explain the necessity of a learning criterion and a recall about one criterion, representative of most of them, we shall define a new criterion, and show why it is better fitted to learn the laws of a deterministic process from a set of observations.This criterion has been used to implement a program which builds an acceptor of natural language sentences in a CAI environment using a tutorial strategy, and then for a question answering device. As attractive as the results are, their improvement requires a semantic model. We give the basic principles of a model which we currently develop, and whose main feature is approximation.     

A kernel language for programmed rewriting of (hyper)graphs

The paper presents a formalism for rewriting (hyper)graphs in a controlled manner. This formalism is essentially a simple programming language with productions, that is rewriting rules, playing the role of basic instructions. Programs in this language are built from productions by means of rather standard constructors, including a parallel composition. They may contain parameters to point to specific elements of graphs to which they are supposed to be applied. Programs are intended to describe how to transform a graph and a valuation of parameters in this graph in order to reach a resulting graph and a resulting valuation of parameters.     

Distant Collision Response in Rigid Body Simulations

We use a finite element model to predict the vibration response of objects in a rigid body simulation, such that rigid objects are augmented to provide a plausible elastic collision response between distant objects due to vibration. We start with a generalized eigenvalue decomposition of the elastic model to precompute a response to an impact at any point on an elastic object with fixed boundary conditions. Then, given a collision between objects, we generate an approximate response impulse to distribute to other objects already in contact with the colliding bodies. This can lead to distant impacts causing an object to slip, or a delicate stack of objects to fall. We also use a geodesic distance based spatial attenuation approximation for travelling waves in objects to respond to an impact at one contact with an impulse at other locations. This response ultimately allows a long distance relationship between contacts, both across a single object being struck, but also traversing the contact graph of a larger collection of objects. We qualitatively validate our approach with a ground truth simulation, and demonstrate a number of scenarios where a long distance relationship between contacts is valuable.     

Analysis of dimensions and tolerances in computer-aided mechanical design

The paper sets forth a theory to explain how dimensions and views combine to specify the shape of a mechanical component. It provides a method to determine whether a component is under, over, or exactly defined by a given dimensioning scheme. Measures for assessing the quality of a scheme are proposed. A solution is offered to a problem of tolerancing: given a toleranced dimensioning scheme, find the resulting tolerances between undimensioned parts of a component.     

Using machine-learning methods for musical style modeling

The ability to construct a musical theory from examples presents a great intellectual challenge that, if successfully met, could foster a range of new creative applications. Inspired by this challenge, we sought to apply machine-learning methods to the problem of musical style modeling. Our work so far has produced examples of musical generation and applications to a computer-aided composition system. Machine learning consists of deriving a mathematical model, such as a set of stochastic rules, from a set of musical examples. The act of musical composition involves a highly structured mental process. Although it is complex and difficult to formalize, it is clearly far from being a random activity. Our research seeks to capture some of the regularity apparent in the composition process by using statistical and information theoretic tools to analyze musical pieces. The resulting models can be used for inference and prediction and, to a certain extent, to generate new works that imitate the style of the great masters.     

Pipelined parallelisation of automatic face inspection

A parallel pipeline is shown to be a natural method of speeding up a typical computer vision application, face inspection using `eigenfaces'. Faces within a stream of video images are continuously surveyed in a manner akin to a `conveyor belt' inspection process. The parallelisation is a new exemplar of a scheme for the rapid prototyping of large-scale, multi-algorithm applications suitable for transfer to a message-passing multicomputer. A general solution, pipelined processor farms, is preferred to a customised solution. This paper gives details of the software tools and software engineering methods employed to tackle this class of problem.     

Elimination of artifacts due to occlusion and discretization problems in image space blurring techniques

Traditional computer graphics methods render images that appear sharp at all depths. Adding blur can add realism to a scene, provide a sense of scale, and draw a viewer’s attention to a particular region of a scene. Our image-based blur algorithm needs to distinguish whether a portion of an image is either from a single object or is part of more than one object. This motivates two approaches to identify objects after an image has been rendered. We illustrate how these techniques can be used in conjunction with our image space method to add blur to a scene.     

Checkpointing and Rollback-Recovery for Distributed Systems

We consider the problem of bringing a distributed system to a consistent state after transient failures. We address the two components of this problem by describing a distributed algorithm to create consistent checkpoints, as well as a rollback-recovery algorithm to recover the system to a consistent state. In contrast to previous algorithms, they tolerate failures that occur during their executions. Furthermore, when a process takes a checkpoint, a minimal number of additional processes are forced to take checkpoints. Similarly, when a process rolls back and restarts after a failure, a minimal number of additional processes are forced to roll back with it. Our algorithms require each process to store at most two checkpoints in stable storage. This storage requirement is shown to be minimal under general assumptions.     

Semantic constraint specification and verification of ebXML business process specifications

Electronic Business using eXtensible Markup Language (ebXML) Business Process Specification Schema (BPSS) supports the specification of the set of elements required to configure a runtime system in order to execute a set of ebXML business transactions. The BPSS is available in two stand-alone representations; a UML version and an XML version. Due to the limitations of UML notations and XML syntax, however, the current ebXML BPSS specification is insufficient to formally specify semantic constraints of modeling elements. In this study, we propose a classification scheme for BPSS semantic constraints, and describe how to represent those semantic constraints formally using Object Constraint Language. As a way to verify a particular Business Process Specification (BPS) with formal semantic constraint modeling, we suggest a rule-based approach to represent the formal semantic constraints, and describe a detail mechanism to apply the rule-based specified constraints to the BPS in a prototype implementation.     

Upgrading a Granular Computing Based Data Mining Framework to a Relational Case

One of the popular methods to develop an algorithm for mining data stored in a relational structure is to upgrade an existing attribute‐value algorithm to a relational case. Current approaches to this problem have some shortcomings such as (1) a dependence on the upgrading process of the algorithm to be extended, (2) complicated redefinitions of crucial notions (e.g., pattern generality, pattern refinement), and (3) a tolerant limitation of the search space for pattern discovery. In this paper, we propose and evaluate a general methodology for upgrading a data mining framework to a relational case. This methodology is defined in a granular computing environment. Thanks to our relational extension of a granular computing based data mining framework, the three above problems can be overcome.     

Incorporating Time-Varying Perturbations Into the Dynamic Inoperability Input–Output Model

This paper introduces a methodology to extend the capabilities of the dynamic inoperability input-output model (DIIM) to account for perturbations to sectors of the economy that are time varying and probabilistic. The DIIM accounts for the interdependent nature of the economy in determining the impact of a disruption on the ability of each economic sector to satisfy the prevailing demand. While the original formulation of the DIIM only allows for a single perturbation vector, this paper extends the DIIM to allow a perturbation matrix to be utilized as inputs to the model. The underlying motivation for this paper is understanding the impact of a pandemic on a regional economy. As such, idiosyncrasies associated with a pandemic are also accounted for in the model formulation. These include translating workforce absenteeism into a measure of sector inoperability and accounting for the impact of long-term absenteeism on a sector's ability to deliver its as-planned production output.     

A distributed learning model for Freshwater Ecology practical classes

Abstract This paper describes a case study where a distributed learning model was used to enhance the traditional teaching of a freshwater ecology practical class by providing students with a student-centred constructivist environment. Prior to the practical session, a website was created and students were encouraged to think about the morphological adaptations of stream organisms. They were then divided into groups and taken to a real stream to collect specimens and bring them back to the laboratory for further examination and discussion. After the practical, each student group was required to produce a web page concerning the adaptations of the stream organisms to answer a set of online tutorial questions, and to participate in web-based discussion. Feedback by questionnaire showed that the great majority of students enjoyed working with the website and found the content very useful. More than half of the students preferred this type of web-assisted, student-centred practical to conventional practicals, while about a third showed no special preference between the two approaches.     

Position estimation using principal components of range data

This paper describes a new approach to mobile robot position estimation, based on principal component analysis of laser range data. An eigenspace is constructed from the principal components of a large number of range data sets. The structure of an environment, as seen by a range sensor, is represented as a family of surfaces in this space. Subsequent range data sets from the environment project as a point in this space. Associating this point to the family of surfaces gives a set of candidate positions and orientations (poses) for the sensor. These candidate poses correspond to positions and orientations in the environment which have similar range profiles. A Kalman filter can be used to select the most likely candidate pose based on coherence with small movements.

The first part of this paper describes how a relatively small number of depth profiles of an environment can be used to generate a complete eigenspace. This space is used to build a representation of the range scan profiles obtained from a regular grid of positions and orientations (poses). This representation has the form of a family of surface (a manifold). This representation converts the problem of associating a range profile to possible positions and orientations into a table lookup. As a side benefit, the method provides a simple means to detect obstacles in a range profile. The final section of the paper reviews the use of estimation theory to determine the correct pose hypothesis by tracking.     

A hybrid system approach for supporting digital libraries

A digital library (DL) consists of a database which contains library information and a user interface which provides a visual window for users to search relevant information stored in the database. Thus, an abstract structure of a digital library can be defined as a combination of a special purpose database and a user-friendly interface. This paper addresses one of the fundamental aspects of such a combination. This is the formal data structure for linking an object oriented database with hypermedia to support digital libraries. It is important to establish a formal structure for a digital library in order to efficiently maintain different types of library information. This article discusses how to build an object oriented hybrid system to support digital libraries. In particular, we focus on the discussion of a general purpose data model for digital libraries and the design of the corresponding hypermedia interface. The significant features of this research are, first, a formalized data model to define a digital library system structure; second, a practical approach to manage the global schema of a library system; and finally, a design strategy to integrate hypermedia with databases to support a wide range of application areas. Received: 15 December 1997 / Revised: June 1999     

Particle swarm algorithm with adaptive constraint handling and integrated surrogate model for the management of petroleum fields

This paper deals with the development of effective techniques to automatically obtain the optimum management of petroleum fields aiming to increase the oil production during a given concession period of exploration. The optimization formulations of such a problem turn out to be highly multimodal, and may involve constraints. In this paper, we develop a robust particle swarm algorithm coupled with a novel adaptive constraint-handling technique to search for the global optimum of these formulations. However, this is a population-based method, which therefore requires a high number of evaluations of an objective function. Since the performance evaluation of a given management scheme requires a computationally expensive high-fidelity simulation, it is not practicable to use it directly to guide the search. In order to overcome this drawback, a Kriging surrogate model is used, which is trained offline via evaluations of a High-Fidelity simulator on a number of sample points. The optimizer then seeks the optimum of the surrogate model.