Data-based dynamic haptic interaction model with deformable 3D objects

The data-based modeling of the haptic interaction simulation is a growing trend in research. These techniques offer a quick alternative to parametric modeling of the simulation. So far, most of the use of the data-based techniques was applied to static simulations. This paper introduces how to use data-based model in dynamic simulations. This ensures realistic behavior and produce results that are very close to parametric modeling. The results show that a quick and accurate response can be achieved using the proposed methods.

The domain layer for mixed-initiative interaction in generative design

The design space exploration formalism has developed data structures and algorithms of sufficient complexity and scope to support conceptual layout, massing, and enclosure configurations. However, design remains a human enterprise. To support the user in designing with the formalism, we have developed an interaction model that addresses the interleaving of user actions with the formal operations of design space exploration. The central feature of our interaction model is the modeling of control based on mixed-initiative. Initiative is sometimes taken by the designer and sometimes by the formalism in working on a shared design task. The model comprises three layers, domain, task, and dialogue. In this paper we describe the formulation of the domain layer of our mixed-initiative interaction model for design space exploration. We present the view of the domain as understood in the formalism in terms of the three abstract concepts of state, move, and structure. In order to support mixed initiative, it is necessary to develop a shared view of the domain. The domain layer addresses this problem by mapping the designer's view onto the symbol substrate. First, we present the designer's view of the domain in terms of problems, solutions, choices, and history. Second, we show how this view is interleaved with the symbol-substrate through four domain layer constructs, problem state, solution state, choice, and exploration history. The domain layer presents a suitable foundation for integrating the role of the designer with a description formalism. It enables the designer to maintain exploration freedom in terms of formulating and reformulating problems, generating solutions, making choices, and navigating the history of exploration.

Psychopathology in police custody: The role of importation, deprivation and interaction models

People experiencing mental illness are over-represented among police cell detainees, however limited work has sought to investigate the occurrence of psychopathology in police custody. The present study sought to examine the predictive power of personal factors (e.g., history of psychiatric hospitalisation), situational factors (e.g., police cell conditions), and their interactive effects to explain the occurrence of psychopathology in police custody. A total of 150 detainees were recruited from two metropolitan police stations in Melbourne, Australia. Personal factors were significantly associated with psychiatric symptomatology, with situational factors and interaction terms yielding no association. Detainees with preexisting vulnerabilities and those unsatisfied with police cell conditions demonstrated the highest levels of psychopathology. While all detainees experience some difficulties in police cells, it is those with pre-existing vulnerabilities that suffer the most. This may be due to the exacerbation of vulnerabilities by police cell conditions. The implications of these findings for provision of health care services in police cells are discussed.

Touch it, feel it and experience it: developing professional IS skills using interview-style experiential simulations

The IS education field has made increasing use of computerised experiential simulations, but few attempts have been made to create an authentic learning environment that combines and balances elements of video-based computer simulation with real-life learning activities. This paper explores the design principles used to develop a CD-ROM simulation where learners use interviewing skills to elicit system requirements from simulated employees in an authentic context. The employees are videoed actors who converse with each other and with learners within a dynamic interaction model. The paper also describes how we combined this simulation with other teaching approaches such as in-class discussions, student team work, formal presentations, etc.

Agent-based hybrid framework for decision making on complex problems

Electronic commerce and the Internet have created demand for automated systems that can make complex decisions utilizing information from multiple sources. Because the information is uncertain, dynamic, distributed, and heterogeneous in nature, these systems require a great diversity of intelligent techniques including expert systems, fuzzy logic, neural networks, and genetic algorithms. However, in complex decision making, many different components or sub-tasks are involved, each of which requires different types of processing. Thus multiple such techniques are required resulting in systems called hybrid intelligent systems. That is, hybrid solutions are crucial for complex problem solving and decision making. There is a growing demand for these systems in many areas including financial investment planning, engineering design, medical diagnosis, and cognitive simulation. However, the design and development of these systems is difficult because they have a large number of parts or components that have many interactions. From a multi-agent perspective, agents in multi-agent systems (MAS) are autonomous and can engage in flexible, high-level interactions. MASs are good at complex, dynamic interactions. Thus a multi-agent perspective is suitable for modeling, design, and construction of hybrid intelligent systems. The aim of this thesis is to develop an agent-based framework for constructing hybrid intelligent systems which are mainly used for complex problem solving and decision making. Existing software development techniques (typically, object-oriented) are inadequate for modeling agent-based hybrid intelligent systems. There is a fundamental mismatch between the concepts used by object-oriented developers and the agent-oriented view. Although there are some agent-oriented methodologies such as the Gaia methodology, there is still no specifically tailored methodology available for analyzing and designing agent-based hybrid intelligent systems. To this end, a methodology is proposed, which is specifically tailored to the analysis and design of agent-based hybrid intelligent systems. The methodology consists of six models - role model, interaction model, agent model, skill model, knowledge model, and organizational model. This methodology differs from other agent-oriented methodologies in its skill and knowledge models. As good decisions and problem solutions are mainly based on adequate information, rich knowledge, and appropriate skills to use knowledge and information, these two models are of paramount importance in modeling complex problem solving and decision making. Follow the methodology, an agent-based framework for hybrid intelligent system construction used in complex problem solving and decision making was developed. The framework has several crucial characteristics that differentiate this research from others. Four important issues relating to the framework are also investigated. These cover the building of an ontology for financial investment, matchmaking in middle agents, reasoning in problem solving and decision making, and decision aggregation in MASs. The thesis demonstrates how to build a domain-specific ontology and how to access it in a MAS by building a financial ontology. It is argued that the practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. It is proposed to consider service provider agents' track records in matchmaking. A way to provide initial values for the track records of service provider agents is also suggested. The concept of ‘reasoning with multimedia information’ is introduced, and reasoning with still image information using symbolic projection theory is proposed. How to choose suitable aggregation operations is demonstrated through financial investment application and three approaches are proposed - the stationary agent approach, the token-passing approach, and the mobile agent approach to implementing decision aggregation in MASs. Based on the framework, a prototype was built and applied to financial investment planning. This prototype consists of one serving agent, one interface agent, one decision aggregation agent, one planning agent, four decision making agents, and five service provider agents. Experiments were conducted on the prototype. The experimental results show the framework is flexible, robust, and fully workable. All agents derived from the methodology exhibit their behaviors correctly as specified.

The use of public transport in coastal Australia : modes of travel to work and greenhouse emissions

Commuting to work is one of the most important and regular routines of transportation in towns and cities. From a geographic perspective, the length of people’s commute is influenced, to some degree, by the spatial separation of their home and workplace and the transport infrastructure. The rise of car ownership in Australia from the 1950s to the present was accompanied by a considerable decrease of public transport use. Currently there is an average of 1.4 persons per car in Australia, and private cars are involved in approximately 90% of the trips, and public transportation in only 10%. Increased personal mobility has fuelled the trend of decentralised housing development, mostly without a clear planning for local employment, or alternative means of transportation. Transport sector accounts for 14% of Australia’s net greenhouse gas emissions. Without further policy action, Australia’s emissions are projected to continue to increase. The Australian Federal Government and the new Department of Climate Change have recently published a set of maps showing that rising seas would submerge large parts of Victoria coastal region. Such event would lead to major disruption in planned urban growth areas in the next 50 years with broad scale inundation of dwellings, facilities and road networks. The Greater Geelong Region has well established infrastructure as a major urban centre and tourist destination and hence attracted the attention of federal and state governments in their quest for further development and population growth. As a result of its natural beauty and ecological sensitivity, scenarios for growth in the region are currently under scrutiny from local government as well as development agencies, scientists, and planners. This paper is part of a broad research in the relationship between transportation system, urban form, trip demand, and emissions, as a paramount in addressing the challenges presented by urban growth. Progressing from previous work focused on private cars, this present paper investigates the use of public transport as a mode for commuting in the Greater Geelong Region. Using a GIS based interaction model, it characterises the current use of the existing public transportation system, and also builds a scenario of increased use of the existing public transportation system, estimating potencial reductions in CO2 emissions. This study provides an improved understanding of the extent to which choices of transport mode and travel activity patterns, affect emissions in the context of regional networks. The results indicate that emissions from commuting by public transportation are significantly lower than those from commuting by private car, and emphasise that there are opportunities for large abatment in the greenhouse emissions from the transportation sector related to efforts in increasing the use of existing public transportation system.

Damage identification scheme based on compressive sensing

Civil infrastructures are critical to every nation, due to their substantial investment, long service period, and enormous negative impacts after failure. However, they inevitably deteriorate during their service lives. Therefore, methods capable of assessing conditions and identifying damage in a structure timely and accurately have drawn increasing attention. Recently, compressive sensing (CS), a significant breakthrough in signal processing, has been proposed to capture and represent compressible signals at a rate significantly below the traditional Nyquist rate. Due to its sound theoretical background and notable influence, this methodology has been successfully applied in many research areas. In order to explore its application in structural damage identification, a new CS-based damage identification scheme is proposed in this paper, by regarding damage identification problems as pattern classification problems. The time domain structural responses are transferred to the frequency domain as sparse representation, and then the numerical simulated data under various damage scenarios will be used to train a feature matrix as input information. This matrix can be used for damage identification through an optimization process. This will be one of the first few applications of this advanced technique to structural engineering areas. In order to demonstrate its effectiveness, numerical simulation results on a complex pipe soil interaction model are used to train the parameters and then to identify the simulated pipe degradation damage and free-spanning damage. To further demonstrate the method, vibration tests of a steel pipe laid on the ground are carried out. The measured acceleration time histories are used for damage identification. Both numerical and experimental verification results confirm that the proposed damage identification scheme will be a promising tool for structural health monitoring.

A field test of the diversity-openness moderator model in newly formed groups: openness to diversity affects group decision effectiveness and interaction patterns

Detrimental effects of diversity in workgroups has frequently been observed but research identifying the factors that lead to negative or positive effects in heterogeneous groups is lacking. The perceived dissimilarity openness moderator model provides one explanation of the process by which diversity influences group affective, behavioral, and cognitive outcomes. Specifically the model identifies individual, group, and organizational openness as moderating the effects of diversity in workgroups. In this paper evidence is provided from a field study that increased openness to perceived dissimilarity leads to better outcomes in newly formed groups. This study also constitutes a significant building block toward the development of theory concerning the moderating variables of the relationship between diversity and group processes, and outcomes of organizations.

Customer-product interaction : a model for new product development in entrepreneurial firms

Use of New Product Development (NPD) methods may benefit New Zealand SMEs and entrepreneurial firms in gaining greater market share. In this paper we review the literature on New Product Development, NPD theory and methods for early stage product design and development. Our reading suggests that product design has greater success when the customer is involved in the design effort. It also recommends methods of approach to new markets in the (NPD) life cycle. The literature further elucidates methods for identification of product design criteria based on customer needs identification. In essence, customer-product interaction in the early stages of product development is important to product success in new markets for entrepreneurial firms and SMEs. Of particular interest are early-stage NPD research methods and their influence on the company’s marketing strategy.

A formal model of mixed-initiative interaction in design exploration

Computer-based environments for supporting design are complex software artifacts. These tools need to use sound computational formalisms as well as address issues of human usability. The development of interactive and usable generative systems is a significant research area in design computation. Though classical search techniques play a central role in the generative kernels of these "closed-world" systems, the open-ended exploration of design spaces is the desirable goal. In this paper, we present a formal model of exploration that combines search with user driven exploration. We describe the role of interaction and agency in an experimental mixed-initiative design support system.

A neuro-immune model of myalgic encephalomyelitis/chronic fatigue syndrome

This paper proposes a neuro-immune model for Myalgic Encephalomyelitis/Chronic fatigue syndrome (ME/CFS). A wide range of immunological and neurological abnormalities have been reported in people suffering from ME/CFS. They include abnormalities in proinflammatory cytokines, raised production of nuclear factor-κB, mitochondrial dysfunctions, autoimmune responses, autonomic disturbances and brain pathology. Raised levels of oxidative and nitrosative stress (O&NS), together with reduced levels of antioxidants are indicative of an immuno-inflammatory pathology. A number of different pathogens have been reported either as triggering or maintaining factors. Our model proposes that initial infection and immune activation caused by a number of possible pathogens leads to a state of chronic peripheral immune activation driven by activated O&NS pathways that lead to progressive damage of self epitopes even when the initial infection has been cleared. Subsequent activation of autoreactive T cells conspiring with O&NS pathways cause further damage and provoke chronic activation of immuno-inflammatory pathways. The subsequent upregulation of proinflammatory compounds may activate microglia via the vagus nerve. Elevated proinflammatory cytokines together with raised O&NS conspire to produce mitochondrial damage. The subsequent ATP deficit together with inflammation and O&NS are responsible for the landmark symptoms of ME/CFS, including post-exertional malaise. Raised levels of O&NS subsequently cause progressive elevation of autoimmune activity facilitated by molecular mimicry, bystander activation or epitope spreading. These processes provoke central nervous system (CNS) activation in an attempt to restore immune homeostatsis. This model proposes that the antagonistic activities of the CNS response to peripheral inflammation, O&NS and chronic immune activation are responsible for the remitting-relapsing nature of ME/CFS. Leads for future research are suggested based on this neuro-immune model.