Supporting scenario evolution

Scenarios have been shown to be very helpful in identifying and communicating requirements for computer-based systems (CBSs). However, they appear not to be applicable to the rest of the CBS development process. Making scenarios more useful for the entire software development lifecycle requires integrating scenarios to other representations used during CBS development. This integration is achieved with tracing technology. Having integrated scenarios into the entire software development lifecycle creates the necessity to maintain scenarios through the inevitable changes that they and other documents undergo and to subject them to configuration management. We have prototyped automated support for full-lifecycle scenario management and have applied it to some non-trivial systems.This paper is an amalgamation and extension of the conference papers numbered 8, 9, 10, and 11 in the bibliography of this paper.

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Numerical study on gas–liquid nano-flows with pseudo-particle modeling and soft-particle molecular dynamics simulation

We couple pseudo-particle modeling (PPM, Ge and Li in Chem Eng Sci 58(8):1565–1585, 2003), a variant of hard-particle molecular dynamics, with standard soft-particle molecular dynamics (MD) to study an idealized gas–liquid flow in nano-channels. The coupling helps to keep sharp contrast between gas and liquid behaviors and the simulations conducted provide a reference frame for exploring more complex and realistic gas–liquid nano-flows. The qualitative nature and general flow patterns of the flow under such extreme conditions are found to be consistent with its macro-scale counterpart.

Feature subset selection based on fuzzy entropy measures for handling classification problems

In this paper, we present a new method for dealing with feature subset selection based on fuzzy entropy measures for handling classification problems. First, we discretize numeric features to construct the membership function of each fuzzy set of a feature. Then, we select the feature subset based on the proposed fuzzy entropy measure focusing on boundary samples. The proposed method can select relevant features to get higher average classification accuracy rates than the ones selected by the MIFS method (Battiti, R. in IEEE Trans. Neural Netw. 5(4):537–550, 1994), the FQI method (De, R.K., et al. in Neural Netw. 12(10):1429–1455, 1999), the OFEI method, Dong-and-Kothari’s method (Dong, M., Kothari, R. in Pattern Recognit. Lett. 24(9):1215–1225, 2003) and the OFFSS method (Tsang, E.C.C., et al. in IEEE Trans. Fuzzy Syst. 11(2):202–213, 2003).

Does Japan really have robot mania? Comparing attitudes by implicit and explicit measures

Japan has more robots than any other country with robots contributing to many areas of society, including manufacturing, healthcare, and entertainment. However, few studies have examined Japanese attitudes toward robots, and none has used implicit measures. This study compares attitudes among the faculty of a US and a Japanese university. Although the Japanese faculty reported many more experiences with robots, implicit measures indicated both faculties had more pleasant associations with humans. In addition, although the US faculty reported people were more threatening than robots, implicit measures indicated both faculties associated weapons more strongly with robots than with humans. Despite the media’s hype about Japan’s robot ‘craze,’ response similarities suggest factors other than attitude better explain robot adoption. These include differences in history and religion, personal and human identity, economic structure, professional specialization, and government policy. Japanese robotics offers a unique reference from which other nations may learn.

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Controller design for human-robot interaction

Many robotics tasks require a robot to share the same workspace with humans. In such settings, it is important that the robot performs in such a way that does not cause distress to humans in the workspace. In this paper, we address the problem of designing robot controllers which minimize the stress caused by the robot while performing a given task. We present a novel, data-driven algorithm which computes human-friendly trajectories. The algorithm utilizes biofeedback measurements and combines a set of geometric controllers to achieve human friendliness. We evaluate the comfort level of the human using a Galvanic Skin Response (GSR) sensor. We present results from a human tracking task, in which the robot is required to stay within a specified distance without causing high stress values.

Ethical regulations on robotics in Europe

There are only a few ethical regulations that deal explicitly with robots, in contrast to a vast number of regulations, which may be applied. We will focus on ethical issues with regard to “responsibility and autonomous robots”, “machines as a replacement for humans”, and “tele-presence”. Furthermore we will examine examples from special fields of application (medicine and healthcare, armed forces, and entertainment). We do not claim to present a complete list of ethical issue nor of regulations in the field of robotics, but we will demonstrate that there are legal challenges with regard to these issues.

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Comparative analysis of simple facial features extractors

In the article a certain class of feature extractors for face recognition is presented. The extraction is based on simple approaches: image scaling with pixel concatenation into a feature vector, selection of a small number of points from the face area, face image’s spectrum, and finally pixel intensities histogram. The experiments performed on several facial image databases (BioID [4], ORL face database [27], FERET [30]) show that face recognition using this class of extractors is particularly efficient and fast, and can have straightforward implementations in software and hardware systems. They can also be used in fast face recognition system involving feature-integration, as well as a tool for similar faces retrieval in 2-tier systems (as initial processing, before exact face recognition).

Scarecrow: If I only had AI

At the 1992 AAAI robot contest one of the top finishers was Scarecrow—a robot that had no computer in the traditional sense, was built out of less than $200 of parts, and was explained and operated by a five year old. The designers sought to demonstrate the capabilities and competence that can be accomplished by using a strictly reactive architecture for well defined tasks such as that contest. This paper reexamines the Scarecrow robot and puts it into historical context. With fifteen years of perspective, we can also see what Scarecrow has to say about the perception of intelligence.

The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.

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Socializing artifacts as a half mirror of the mind

In the near future, our life will normally be surrounded with fairly complicated artifacts, enabled by the autonomous robot and brain–machine interface technologies. In this paper, we argue that what we call the responsibility flaw problem and the inappropriate use problem need to be overcome in order for us to benefit from complicated artifacts. In order to solve these problems, we propose an approach to endowing artifacts with an ability of socially communicating with other agents based on the artifact-as-a-half-mirror metaphor. The idea is to have future artifacts behave according to the hybrid intention composed of the owner’s intention and the social rules. We outline the approach and discuss its feasibility together with preliminary work.

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Invariant Signatures of Closed Planar Curves

We prove that any subset of ℝ² parametrized by a C ¹ periodic function and its derivative is the Euclidean invariant signature of a closed planar curve. This solves a problem posed by Calabi et al. (Int. J. Comput. Vis. 26:107–135, 1998). Based on the proof of this result, we then develop some cautionary examples concerning the application of signature curves for object recognition and symmetry detection as proposed by Calabi et al.

Multimodal support to group dynamics

The complexity of group dynamics occurring in small group interactions often hinders the performance of teams. The availability of rich multimodal information about what is going on during the meeting makes it possible to explore the possibility of providing support to dysfunctional teams from facilitation to training sessions addressing both the individuals and the group as a whole. A necessary step in this direction is that of capturing and understanding group dynamics. In this paper, we discuss a particular scenario, in which meeting participants receive multimedia feedback on their relational behaviour, as a first step towards increasing self-awareness. We describe the background and the motivation for a coding scheme for annotating meeting recordings partially inspired by the Bales’ Interaction Process Analysis. This coding scheme was aimed at identifying suitable observable behavioural sequences. The study is complemented with an experimental investigation on the acceptability of such a service.

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ONTRACK: Dynamically adapting music playback to support navigation

Listening to music on personal, digital devices whilst mobile is an enjoyable, everyday activity. We explore a scheme for exploiting this practice to immerse listeners in navigation cues. Our prototype, ONTRACK, continuously adapts audio, modifying the spatial balance and volume to lead listeners to their target destination. First we report on an initial lab-based evaluation that demonstrated the approach’s efficacy: users were able to complete tasks within a reasonable time and their subjective feedback was positive. Encouraged by these results we constructed a handheld prototype. Here, we discuss this implementation and the results of field-trials. These indicate that even with a low-fidelity realisation of the concept, users can quite effectively navigate complicated routes.

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Understanding and capturing people’s privacy policies in a mobile social networking application

A number of mobile applications have emerged that allow users to locate one another. However, people have expressed concerns about the privacy implications associated with this class of software, suggesting that broad adoption may only happen to the extent that these concerns are adequately addressed. In this article, we report on our work on PeopleFinder, an application that enables cell phone and laptop users to selectively share their locations with others (e.g. friends, family, and colleagues). The objective of our work has been to better understand people’s attitudes and behaviors towards privacy as they interact with such an application, and to explore technologies that empower users to more effectively and efficiently specify their privacy preferences (or “policies”). These technologies include user interfaces for specifying rules and auditing disclosures, as well as machine learning techniques to refine user policies based on their feedback. We present evaluations of these technologies in the context of one laboratory study and three field studies.

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Making SVMs Scalable to Large Data Sets using Hierarchical Cluster Indexing

Support vector machines (SVMs) have been promising methods for classification and regression analysis due to their solid mathematical foundations, which include two desirable properties: margin maximization and nonlinear classification using kernels. However, despite these prominent properties, SVMs are usually not chosen for large-scale data mining problems because their training complexity is highly dependent on the data set size. Unlike traditional pattern recognition and machine learning, real-world data mining applications often involve huge numbers of data records. Thus it is too expensive to perform multiple scans on the entire data set, and it is also infeasible to put the data set in memory. This paper presents a method, Clustering-Based SVM (CB-SVM), that maximizes the SVM performance for very large data sets given a limited amount of resource, e.g., memory. CB-SVM applies a hierarchical micro-clustering algorithm that scans the entire data set only once to provide an SVM with high quality samples. These samples carry statistical summaries of the data and maximize the benefit of learning. Our analyses show that the training complexity of CB-SVM is quadratically dependent on the number of support vectors, which is usually much less than that of the entire data set. Our experiments on synthetic and real-world data sets show that CB-SVM is highly scalable for very large data sets and very accurate in terms of classification. A preliminary version of the paper, “Classifying Large Data Sets Using SVM with Hierarchical Clusters”, by H. Yu, J. Yang, and J. Han, appeared in Proc. 2003 Int. Conf. on Knowledge Discovery in Databases (KDD'03), Washington, DC, August 2003. However, this submission has substantially extended the previous paper and contains new and major-value added technical contribution in comparison with the conference publication.

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Interacting with mobile services: an evaluation of camera-phones and visual tags

We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a user-experience study is described in which participants were both observed learning to interact with a prototype mobile service and interviewed about their experiences. Secondly, a pointing-device task is presented in which quantitative data was gathered regarding the speed and accuracy with which participants aimed and clicked on visual-tags using camera-phones. We found that participants’ attitudes to visual-tag-based applications were broadly positive, although they had several important reservations about camera-phone technology more generally. Data from our pointing-device task demonstrated that novice users were able to aim and click on visual-tags quickly (well under 3 s per pointing-device trial on average) and accurately (almost all meeting our defined speed/accuracy tradeoff of 6% error-rate). Based on our findings, design lessons for camera-phone and visual-tag applications are presented.

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A dynamically reconfigurable stereoscopic/panoramic vision mobile robot head controlled from a virtual environment

We have built a mobile robotic platform that features an Active Robotic Head (ARH) with two high-resolution cameras that can be switched during robot operation between two configurations that produce respectively panoramic and stereoscopic images. Image disparity is used for improving the quality of the texture. The robot head switches dynamically, based on robot operation between the stereoscopic configuration and the panoramic configuration.

Adaptive behavior in turning of an oscillator-driven biped robot

This paper concentrates on a biped robot’s turning behavior that consists of straight and curved walking and the transition between these two patterns. We investigate how a robot achieves adaptive walking during such turning by focusing on rhythm control and propose a locomotion control system that generates robot motions by rhythmic signals from internal oscillators and modulates signal generation based on touch sensor signals. First, we verify that the robot attains limit cycles of straight and curved walking by numerical simulations and hardware experiments. Second, we examine the transition between these walking patterns based on the basin of attraction of the limit cycles in numerical simulations. Finally, we verify whether the robot actually accomplishes transition and turning by hardware experiments. This paper clarifies that the robot establishes such turning motions by adequate modulation of walking rhythm and phase through interactions between the dynamics of its mechanical system, oscillators, and environment.

Connecting the family with awareness systems

Awareness systems have attracted significant research interest for their potential to support interpersonal relationships. Investigations of awareness systems for the domestic environment have suggested that such systems can help individuals stay in touch with dear friends or family and provide affective benefits to their users. Our research provides empirical evidence to refine and substantiate such suggestions. We report our experience with designing and evaluating the ASTRA awareness system, for connecting households and mobile family members. We introduce the concept of connectedness and its measurement through the Affective Benefits and Costs of communication questionnaire (ABC-Q). We inform results that testify the benefits of sharing experiences at the moment they happen without interrupting potential receivers. Finally, we document the role that lightweight, picture-based communication can play in the range of communication media available.

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