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.     

Voices that cannot be heard: Can shyness explain how we communicate on Facebook versus face-to-face?

Social networking sites have gained popularity among all populations, especially young adults. Personality traits were found to be predictive of how individuals use social media. Therefore, this study sought to examine the association between shyness and self-disclosure to a Facebook friend as well as self-disclosure to a face-to-face friend. Two studies were conducted. The first study tested how shyness and social loneliness are related to self-disclosure to a Facebook friend to whom an individual talks most often. The second, follow-up study tested how shyness is related to self-disclosure to a Facebook friend to whom a person speaks to only though Facebook, and also to a face-to-face friend to whom the participants talk only face-to-face and never through Facebook. Participants were college students from a large research university in the United States. Study 1 found a negative association between shyness and self-disclosure to a Facebook friend. Study 2 found a negative association between shyness and self-disclosure to a face-to-face friend. The theoretical implications and limitations are discussed.     

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 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.     

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.     

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.     

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.     

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.     

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.     

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.     

A scalable interest-oriented peer-to-peer pub/sub network

There has been a big challenge in structured peer-to-peer overlay network research area. Generally, a structured overlay network involves nodes evenly or based on their resource availabilities, and gathers nodes?? resources to achieve some bigger tasks. The challenge here is to gather resources based on nodes?? interests, and only interested nodes are involved in a certain task. Toward this challenge, we propose a new scheme to a peer-to-peer publish/subscribe network. Publish/subscribe represents a new paradigm for distributed content delivery. It provides an alternative to address-based communication due to its ability to decouple communication between the source and the destination. We propose a Bloom filter based mapping scheme to map IDs to nodes?? interests in addition to new interest proximity metric to forward events and to build nodes?? routing tables. We also propose a new approach called ??shared interest approach?? for network discovery. To evaluate the algorithms proposed in this work, we conducted simulations in both static and dynamic settings, and found a low false positive rate. We also discuss about a well-known application called Twitter, and show how our scheme would work in a real environment.     

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.     

Pervasive computing: a paradigm for the 21st century

Pervasive computing promises to make life simpler via digital environments that sense, adapt, and respond to human needs. Yet we still view computers as machines that run programs in a virtual environment. Pervasive computing presumes a different vision. A device can be a portal into an application-data space, not just a repository of custom software a user must manage. An application is a means by which a user performs a task, not software written to exploit a device's capabilities. And a computing environment is an information-enhanced physical space, not a virtual environment that exists to store and run software. Pervasive computing is close to technical and economic viability.     

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.     

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.     

A novel threshold changeable secret sharing scheme

A(t,n)threshold secret sharing scheme is a fundamental tool in many security applications such as cloud computing and multiparty computing.In conventional threshold secret sharing schemes,like Shamir’s scheme based on a univariate polynomial,additional communication key share scheme is needed for shareholders to protect the secrecy of their shares if secret reconstruction is performed over a network.In the secret reconstruction,the threshold changeable secret sharing(TCSS)allows the threshold to be a dynamic value so that if some shares have been compromised in a given time,it needs more shares to reconstruct the secret.Recently,a new secret sharing scheme based on a bivariate polynomial is proposed in which shares generated initially by a dealer can be used not only to reconstruct the secret but also to protect the secrecy of shares when the secret reconstruction is performed over a network.In this paper,we further extend this scheme to enable it to be a TCSS without any modification.Our proposed TCSS is dealer-free and non-interactive.Shares generated by a dealer in our scheme can serve for three purposes,(a)to reconstruct a secret;(b)to protect the secrecy of shares if secret reconstruction is performed over a network;and(c)to enable the threshold changeable property.     

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.     

Learning and interacting in human-robot domains

We focus on a robotic domain in which a human acts both as a teacher and a collaborator to a mobile robot. First, we present an approach that allows a robot to learn task representations from its own experiences of interacting with a human. While most approaches to learning from demonstration have focused on acquiring policies (i.e., collections of reactive rules), we demonstrate a mechanism that constructs high-level task representations based on the robot's underlying capabilities. Next, we describe a generalization of the framework to allow a robot to interact with humans in order to handle unexpected situations that can occur in its task execution. Without using explicit communication, the robot is able to engage a human to aid it during certain parts of task execution. We demonstrate our concepts with a mobile robot learning various tasks from a human and, when needed, interacting with a human to get help performing them     

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.     

Interacting with team oriented plans in multi-robot systems

Team oriented plans have become a popular tool for operators to control teams of autonomous robots to pursue complex objectives in complex environments. Such plans allow an operator to specify high level directives and allow the team to autonomously determine how to implement such directives. However, the operators will often want to interrupt the activities of individual team members to deal with particular situations, such as a danger to a robot that the robot team cannot perceive. Previously, after such interrupts, the operator would usually need to restart the team plan to ensure its success. In this paper, we present an approach to encoding how interrupts can be smoothly handled within a team plan. Building on a team plan formalism that uses Colored Petri Nets, we describe a mechanism that allows a range of interrupts to be handled smoothly, allowing the team to efficiently continue with its task after the operator intervention. We validate the approach with an application of robotic watercraft and show improved overall efficiency. In particular, we consider a situation where several platforms should travel through a set of pre-specified locations, and we identify three specific cases that require the operator to interrupt the plan execution: (i) a boat must be pulled out; (ii) all boats should stop the plan and move to a pre-specified assembly position; (iii) a set of boats must synchronize to traverse a dangerous area one after the other. Our experiments show that the use of our interrupt mechanism decreases the time to complete the plan (up to 48 % reduction) and decreases the operator load (up to 80 % reduction in number of user actions). Moreover, we performed experiments with real robotic platforms to validate the applicability of our mechanism in the actual deployment of robotic watercraft.