Sensory interactive robot trajectory control using a real-time world model

A major consideration in the design of sensory interactive trajectory generation software for a Flight Telerobotic Servicer (FTS) is the availability and maintenance of a current model of the manipulator's world. The NASA/NBS Standard Reference Model for Telerobot Control System Architecture (NASREM), which has been adopted by NASA for control of the FTS, provides a logical computing architecture for telerobotics. It defines a hierarchical control system in which complex tasks are decomposed into progressively simpler subtasks, or objectives. It contains a hierarchy of world modeling modules which maintain the system's internal model of the manipulator and its world by continuously updating the model based upon sensory data. Each world modeling module contains support processes or functions which simultaneously and asynchronously support sensory processing and task decomposition. This paper discusses the role of world modeling in support of trajectory generation and execution. For sensory interactive robot motion control, the world modeling modules must operate rapidly so that the model of the world remains in registration with the real world.This paper discusses the world modeling modules of a hierarchical control system which facilitate sensory interactive trajectories by decoupling and supporting the sensory and manipulator planning processes. We define the types of information which should be included in the interfaces to the modules, as well as the modules' structure and function. Finally, we discuss the real-time implementation and experimental results of a particular sensory interactive algorithm performed in our laboratory.     

Interpreting and extracting fuzzy decision rules from fuzzy information systems and their inference

Information systems, which contain only crisp data, precise and unique attribute values for all objects, have been widely investigated. Due to the fact that in realworld applications imprecise data are abundant, uncertainty is inherent in real information systems. In this paper, information systems are called fuzzy information systems, and formalized by (objects; attributes; f), in which f is a fuzzy set and expresses some uncertainty between an object and its attribute values. To interpret and extract fuzzy decision rules from fuzzy information systems, the meta-theory based on modal logic proposed by Resconi et al. is modified. The modified meta-theory not only expresses uncertainty between objects and their attributes, but also uncertainty in the process of recognizing fuzzy information systems. In addition, according to perception computing (proposed by Zadeh), granules of fuzzy information systems can be represented by fuzzy decision rules, so that, fuzzy inference methods can be used to obtain the decision attribute of a new object. Finally, a novel way of combining evidences based on the modified meta-theory is introduced, which extends the concept of combining evidences based on Dempster-Shafer theory.     

Interactive computations: toward risk management in interactive intelligent systems

Understanding the nature of interactions is regarded as one of the biggest challenges in projects related to complex adaptive systems. We discuss foundations for interactive computations in interactive intelligent systems (IIS), developed in the Wistech program and used for modeling complex systems. We emphasize the key role of risk management in problem solving by IIS. The considerations are based on experience gained in real-life projects concerning, e.g., medical diagnosis and therapy support, control of an unmanned helicopter, fraud detection algorithmic trading or fire commander decision support.     

Measuring users' performance with interactive information systems

Abstract The purpose of this study was to investigate the discrete forms of knowledge required for successful use of interactive information systems (IIS). Using an existing framework, an instrument was created to measure the achievement of three discrete forms of knowledge among novice users of an CD-ROM encyclopedia. The instrument included tasks designed to measure users' knowledge and skills in managing and controlling the system, navigating between information nodes and selecting appropriate search strategies given information related problems. The study examined hierarchical knowledge and compared the development of these forms of knowledge and skills among novices using two different IIS. The results found significant differences in the user performances between two systems in tasks that measured navigation skills and an understanding of the information organisation. It is suggested that these differences were due to differences in the interface design of the two systems and suggestions are made for selecting and implementing IIS systems in school and educational settings.     

Failure analysis of engineering systems with preventive maintenance and failure interactions

Optimal operation and maintenance of engineering systems heavily rely on the accurate prediction of their failures. Most engineering systems, especially mechanical systems, are susceptible to failure interactions. These failure interactions can be estimated for repairable engineering systems when determining optimal maintenance strategies for these systems. An extended Split System Approach is developed in this paper. The technique is based on the Split System Approach and a model for interactive failures. The approach was applied to simulated data. The results indicate that failure interactions will increase the hazard of newly repaired components. The intervals of preventive maintenance actions of a system with failure interactions, will become shorter compared with scenarios where failure interactions do not exist.     

An abstract framework for globalising interactive systems

We present an abstract framework for designing and developing globalised interactive systems from simple components viewed as games [1] (K. Stathis, M.J. Sergot, Games as a Metaphor for Interactive Systems, in: M.A. Sasse, R.J. Cunningham, R.L. Winder (Eds.), People and Computers XI (Proceedings of HCI′96), August 1996, London, UK, BCS Conference Series, Springer-Varlag, pp. 19–33). We identify a set of concepts required to specify and implement interactions, in such a way whereby instantiating the specifications and implementations of games we obtain components that correspond to localised instances of an interactive system. Localisation is also obtained by either customising the specification or the implementation of the interactive system, or both. The framework also caters for complex interactive systems which are interpreted as compound games built-up from sub-games. In this case, coordination of sub-games is the main issue that we must address at the global level. This is resolved by specifying and implementing sub-games as active components of the more complex games, and, as a result, we localise the coordination of components in the interactive system. The framework lends itself towards a methodology that is suitable for globalising the development of interactive systems.     

Computational modeling of human performance in multiple monitor environments with ACT-R cognitive architecture

Much research on modeling human performance associated with visual perception is formulated by schematic models based on neural mechanisms or cognitive architectures. But, these two modeling paradigms are limited in the domains of multiple monitor environments. Although the schematic model based on neural mechanisms can represent human visual systems in multiple monitor environments by providing a detailed account of eye and head movements, these models cannot easily be applied in complex cognitive interactions. On the other hand, the cognitive architectures can model the interaction of multiple aspects of cognition, but these architectures have not focused on modeling the visual orienting behavior of eye and head movements. Thus, in this study, a specific cognitive architecture, which is ACT-R, is extended by an existing schematic model of human visual systems based on neural mechanisms in order to model human performance in multiple monitor environments more accurately. And, this study proposes a method of modeling human performance using the extended ACT-R. The proposed method is validated by an experiment, confirming that the proposed method is able to predict human performance more accurately in multiple monitor environments.Relevance to industryPredicting human performance with a computational model can be used as an alternative method to implementing iterative user testing for developing a system interface. The computational model in this study can predict human performance in multiple monitor environments, so that the model can be applied early on in the design phase, to evaluate the system interface in multiple monitor environments.     

关于多通道系统的动太递阶镇定

研究镇定多通道系统的一种新策略--动态递阶控制.对线性时不变确定型通道强关 联系统,得到了在给定信息结构下采用动态递阶控制可任置极点(镇定)的一个充分必要条 件,解决了分散循环系统采用动态递阶控制时的最小信息结构问题,并讨论了动态协同控铋 器的最小阶数,最后给出了一个数值例子.     

Modeling rough granular computing based on approximation spaces

The results reported in this paper create a step toward the rough set-based foundations of data mining and machine learning. The approach is based on calculi of approximation spaces. In this paper, we present the summarization and extension of our results obtained since 2003 when we started investigations on foundations of approximation of partially defined concepts (see, e.g., [2], [3], [7], [37], [20], [21], [5], [42], [39], [38], [40]). We discuss some important issues for modeling granular computations aimed at inducing compound granules relevant for solving problems such as approximation of complex concepts or selecting relevant actions (plans) for reaching target goals. The problems discussed in this article are crucial for building computer systems that assist researchers in scientific discoveries in many areas such as biology. In this paper, we present foundations for modeling of granular computations inside of system that is based on granules called approximation spaces. Our approach is based on the rough set approach introduced by Pawlak [24], [25]. Approximation spaces are fundamental granules used in searching for relevant complex granules called as data models, e.g., approximations of complex concepts, functions or relations. In particular, we discuss some issues that are related to generalizations of the approximation space introduced in [33], [34]. We present examples of rough set-based strategies for the extension of approximation spaces from samples of objects onto a whole universe of objects. This makes it possible to present foundations for inducing data models such as approximations of concepts or classifications analogous to the approaches for inducing different types of classifiers known in machine learning and data mining. Searching for relevant approximation spaces and data models are formulated as complex optimization problems. The proposed interactive, granular computing systems should be equipped with efficient heuristics that support searching for (semi-)optimal granules.     

粗糙集理论的分层递阶约简算法及其信息理论基础

本文模拟人类认知的分层递阶原则,提出一种粗糙集理论的分层递阶约简算法.该算法首先将信息系统或决策系统的知识在由部分属性所构成的多种层次和多种粒度上表示出来,然后分别对各个属性层次进行递阶约简.因此,该算法具有较强的实用性和较好的动态特性,并且能并行运算.同时,本文从信息理论的角度证明了分层递阶约简的理论基础.文章的最后将该算法应用于某水泥窑炉控制决策的获取中,证实了其有效性.     

QUESTO: Interactive Construction of Objective Functions for Classification Tasks

Building effective classifiers requires providing the modeling algorithms with information about the training data and modeling goals in order to create a model that makes proper tradeoffs. Machine learning algorithms allow for flexible specification of such meta-information through the design of the objective functions that they solve. However, such objective functions are hard for users to specify as they are a specific mathematical formulation of their intents. In this paper, we present an approach that allows users to generate objective functions for classification problems through an interactive visual interface. Our approach adopts a semantic interaction design in that user interactions over data elements in the visualization are translated into objective function terms. The generated objective functions are solved by a machine learning solver that provides candidate models, which can be inspected by the user, and used to suggest refinements to the specifications. We demonstrate a visual analytics system QUESTO for users to manipulate objective functions to define domain-specific constraints. Through a user study we show that QUESTO helps users create various objective functions that satisfy their goals.     

Parallelization of entanglement-resistant multi-prover interactive proofs

Multi-prover interactive proof systems are said to be entanglement-resistant if the soundness holds even when provers are allowed to share an arbitrary quantum state before the interaction starts. This letter proves that every entanglement-resistant multi-prover interactive proof system can be parallelized to two rounds without ruining its entanglement resistance at the expense of adding one prover.     

Interactive volumetric information visualization for document corpus management

This paper describes aminimally immersive three-dimensional volumetric interactive information visualization system for management and analysis of document corpora. The system, SFA, uses glyph-based volume rendering, enabling more complex data relationships and information attributes to be visualized than traditional 2D and surface-based visualization systems. Two-handed interaction using three-space magnetic trackers and stereoscopic viewing are combined to produce aminimally immersive interactive system that enhances the user’s three-dimensional perception of the information space. This new system capitalizes on the human visual system’s pre-attentive learning capabilities to quickly analyze the displayed information. SFA is integrated with adocument management and information retrieval engine named Telltale. Together, these systems integrate visualization and document analysis technologies to solve the problem of analyzing large document corpora. We describe the usefulness of this system for the analysis and visualization of document similarity within acorpus of textual documents, and present an example exploring authorship of ancient Biblical texts. Received: 15 December 1997 / Revised: June 1999     

Multi-layered interactive energy space modeling for near-optimal electrification of terrestrial,shipboard and aircraft systems

In this paper, we introduce a basic multi-layered modeling framework for posing the problem of safe, robust and efficient design and control that may lend itself to ripping potential benefits from electrification. The proposed framework establishes dynamic relations between physical concepts such as stored energy, useful work, and wasted energy, on one hand; and modeling, simulation, and control of interactive modular complex dynamical systems, on the other. In particular, our recently introduced energy state-space modeling approach for electric energy systems is further interpreted using fundamental laws of physics in multi-physical systems, such as terrestrial energy-systems, aircrafts and ships. The interconnected systems are modeled as dynamically interacting modules. This approach is shown to be particularly well-suited for scalable optimization of large-scale complex systems. Instead of having to use simpler models, the proposed multi-layered modeling of system dynamics in energy space offers a promising basic method for modeling and controlling inter-dependencies across multi-physics subsystems for both ensuring feasible and near-optimal operation. It is illustrated how this approach can be used for understanding fundamental physical causes of inefficiencies created either at the component level or are a result of poor matching of their interactions.     

Virtual reality simulations and animations in a web-based interactive manufacturing engineering module

This paper presents a web-based interactive teaching package that provides a comprehensive and conducive yet dynamic and interactive environment for a module on automated machine tools in the Manufacturing Division at the National University of Singapore. The use of Internet technologies in this teaching tool makes it possible to conjure visualisations that cannot be achieved using traditional teaching materials such as transparencies. Virtual reality simulations and animations were developed and appropriately placed in the teaching materials to enhance the student understanding of complex concepts. This is especially useful in teaching automated machine tools, which deals primarily with the numerical control (NC) of the motions of automated machine tools. These virtual reality simulations and animations provide the capability of training students in NC programming and operations without the need to work on actual NC machines in the laboratory. The simulations are suitably placed in the package to engage the students and enhance their concentration, while at the same time generate interactions. Customised question types were also designed and implemented with a tutorial monitoring application.     

User-controllable personalization: A case study with SetFusion

In this research we investigated the role of user controllability on personalized systems by implementing and studying a novel interactive recommender interface, SetFusion. We examined whether allowing the user to control the process of fusing or integrating different algorithms (i.e., different sources of relevance) resulted in increased engagement and a better user experience. The essential contribution of this research stems from the results of a user study (N=40) of controllability in a scenario where users could fuse different recommendation approaches, with the possibility of inspecting and filtering the items recommended. First, we introduce an interactive Venn diagram visualization, which combined with sliders, can provide an efficient visual paradigm for information filtering. Second, we provide a three-fold evaluation of the user experience: objective metrics, subjective user perception, and behavioral measures. Through the analysis of these metrics, we confirmed results from recent studies, such as the effect of trusting propensity on accepting the recommendations and also unveiled the importance of features such as being a native speaker. Our results present several implications for the design and implementation of user-controllable personalized systems.     

面向虚实融合的人机交互

面向虚实融合的人机交互涉及计算机科学、认知心理学、人机工程学、多媒体技术和虚拟现实等领域，旨在提高人机交互的效率，同时响应人类认知与情感的需求，在办公教育、机器人和虚拟/增强现实设备中都有广泛应用。本文从人机交互涉及感知计算、人与机器人交互及协同、个性化人机对话和数据可视化等4个维度系统阐述面向虚实融合人机交互的发展现状。对国内外研究现状进行对比，展望未来的发展趋势。本文认为兼具可迁移与个性化的感知计算、具备用户行为深度理解的人机协同、用户自适应的对话系统等是本领域的重要研究方向。     

An Evaluation of the Potential of Task Analysis in the Evolution of Interactive Work Systems

Developed forms of task analysis allow designers to focus on both utility and usability issues in the development of interactive work systems. The models they generate represent aspects of the human, computer and domain elements of an interactive work system. Many interactive work systems are embedded in an organisational context. Pressure for changes are present in this context and provide impetus to stakeholders to change work tasks and the supporting tools. Interactive work systems also provide evolutionary pressures of their own, changing the very task they were designed to support. One approach to coping with change has been to evolve interactive work systems. Currently none of these techniques place focus on the performance of tasks as central, and consideration of usability is minimal. However, an evolutionary design approach forces an evolutionary experience upon users, and we cannot be sure whether this approach enhances the user’s experience or degrades their performance. Given the strength of task analysis it is likely that it will be applied within evolutionary contexts. Yet, little work has been undertaken to examine whether its role will, or could be different. We ask how we can move task analysis towards being used in a principled manner in the evolution of interactive work systems. This paper examines a number of features of the approach called task knowledge structures that may be useful in evolving interactive work systems. We look at tasks and their representativeness, roles, goals, objects (their attributes, relationships, typicality and centrality) and actions. We present a developing framework for examining other task analysis approaches for their utility in supporting interactive work systems evolution. Finally, we discuss future work within the area of applying task analysis in the evolution of interactive work systems.     

Detecting flaws and intruders with visual data analysis

The task of sifting through large amounts of data to find useful information spawned the field of data mining. Most data mining approaches are based on machine-learning techniques, numerical analysis, or statistical modeling. They use human interaction and visualization only minimally. Such automatic methods can miss some important features of the data. Incorporating human perception into the data mining process through interactive visualization can help us better understand the complex behaviors of computer network systems. This article describes visual-analytics-based solutions and outlines a visual exploration process for log analysis. Three log-file analysis applications demonstrate our approach's effectiveness in discovering flaws and intruders in network systems.