The Use of Macros in Atomic Force Microscopy Image Analysis and Image Processing

The public domain image analysis program NIH Image (http://rsb.info.nih.gov/nih-image) has been modified and extended to produce Image SXM (http://reg.ssci.liv.ac.uk), a program that supports many of the image file formats used by various scanning probe microscope manufacturers. This article discusses the different approaches to software customization and describes the use of two sets of macros in the analysis and processing of atomic force microscopy images.     

Negotiated Collusion: Modeling Social Language and its Relationship Effects in Intelligent Agents

Building a collaborative trusting relationship with users is crucial in a wide range of applications, such as advice-giving or financial transactions, and some minimal degree of cooperativeness is required in all applications to even initiate and maintain an interaction with a user. Despite the importance of this aspect of human–human relationships, few intelligent systems have tried to build user models of trust, credibility, or other similar interpersonal variables, or to influence these variables during interaction with users. Humans use a variety of kinds of social language, including small talk, to establish collaborative trusting interpersonal relationships. We argue that such strategies can also be used by intelligent agents, and that embodied conversational agents are ideally suited for this task given the myriad multimodal cues available to them for managing conversation. In this article we describe a model of the relationship between social language and interpersonal relationships, a new kind of discourse planner that is capable of generating social language to achieve interpersonal goals, and an actual implementation in an embodied conversational agent. We discuss an evaluation of our system in which the use of social language was demonstrated to have a significant effect on users’ perceptions of the agent’s knowledgableness and ability to engage users, and on their trust, credibility, and how well they felt the system knew them, for users manifesting particular personality traits.This revised version was published online in July 2005 with corrections to the author name Bickmore.     

‘It''s just like you talk to a friend’ relational agents for older adults

Relational agents—computational artifacts designed to build and maintain long-term social–emotional relationships with users—may provide an effective interface modality for older adults. This is especially true when the agents use simulated face-to-face conversation as the primary communication medium, and for applications in which repeated interactions over long time periods are required, such as in health behavior change. In this article, we discuss the design of a relational agent for older adults that plays the role of an exercise advisor, and report on the results of a longitudinal study involving 21 adults aged 62–84, half of whom interacted with the agent daily for 2 months in their homes and half who served as a standard-of-care control. Results indicate the agent was accepted and liked, and was significantly more efficacious at increasing physical activity (daily steps walked) than the control.     

A basic agent

A basic agent has been constructed which integrates limited natural language understanding and generation, temporal planning and reasoning, plan execution, simulated symbolic perception, episodic memory, and some general world knowledge. The agent is cast as a robot submarine operating in a two-dimensional simulated "Seaworld" about which it has only partial knowledge. It can communicate with people in a vocabulary of about 800 common English words using a medium coverage grammar. The agent maintains an episodic memory of events in its life and has a limited ability to reflect on those events. A person can make statements to the agent, ask it questions, and give it commands. In response to commands, a temporal task planner is invoked to synthesize a plan, which is then executed at an appropriate future time. A large variety of temporal references in natural language are interpreted with respect to agent time. The agent can form and retain compound future plans, and replan in response to new information or new commands. Natural language verbs are represented in a state transition semantics for compatibility with the planner. The agent is able to give terse answers to questions about its past experiences, present activities and perceptions, future intentions, and general knowledge. No other artificial intelligence artifact with this range of capabilities has previously been constructed.     

Tinker: a relational agent museum guide

A virtual museum guide agent that uses human relationship-building behaviors to engage museum visitors is described. The computer animated agent, named “Tinker”, uses nonverbal conversational behavior, empathy, social dialogue, reciprocal self-disclosure and other relational behavior to establish social bonds with users, and encourage continued interaction and repeated visits. Tinker describes exhibits in the museum, gives directions, and discusses technical aspects of her own implementation. Tinker also recognizes returning visitors through biometric analysis of their hand shapes and dialogue cues. Results from two experiments using Tinker are described. In the first, 29 returning visitors are randomized to interact with the agent with the biometric identification turned on or off. In the second experiment, 1,607 visitors are randomized to interact with versions of Tinker that have relationship-building behavior turned on or off. Results indicate that the use of relational behavior leads to significantly greater engagement by museum visitors, measured by session length, number of sessions, and self-reported attitude, as well as learning gains, as measured by a knowledge test, compared to the same agent that does not use relational behavior. Implications for museum exhibits and intelligent tutoring systems are discussed.     

Ultrafine Spinel Powders by Flame Spray Pyrolysis of a Magnesium Aluminum Double Alkoxide

Ultrafine crystalline spinel powder has been prepared using flame spray pyrolysis of alcoholic solutions of a novel double alkoxide precursor. The particles produced are spherical, dense, single crystals with diameters of 10–100 nm and specific surface areas ranging from 40 to 60 m²/g. Powder production rates of 50–100 g/h are achieved using a bench-top apparatus. Particle formation appears to occur by rapid oxidation of the organic ligands followed by nucleation and growth from oxide species.