Visualization and debugging of distributed multiagent systems

Visualizing the behavior of systems with distributed data, control, and process is a notoriously difficult task. Each component in the distributed system has only a local view of the whole setup, and the onus is on the user to integrate, into a coherent whole, the large amounts of limited information they provide. In this article, we describe an architecture and an implemented system for visualizing and controlling distributed multiagent applications. The system comprises a suite of tools, with each tool providing a different perspective of the application being visualized . Each tool interrogates the components of the distributed application, collates the returned information, and presents this information to users in an appropriate manner. This in essence, shifts the burden ofinference from the user to the visualizer. Our visualizer has been evaluated on four distributed multiagent systems: a travel management application, a telecommunications network management application, a business process management demonstrator, and an electronic commerce application. Lastly, we briefly show how the suite of tools can be used together for debugging multiagent applications - a process we refer to as debugging via corroboration.     

Culturally sanctioned secrets? Latino men's nondisclosure of HIV infection to family, friends, and lovers.

Spanish-speaking Latino men (n?=?107) were more likely than English-speaking Latinos (n?=?85) and Whites (n?=?206) to withhold their HIV-positive serostatus and their gay or bisexual orientation from significant others, especially family members. Similar effects were observed when Latinos were divided by birthplace and when analyses controlled for sociodemographic and medical factors. Reasons for revealing or concealing an HIV diagnosis varied across targets. Although both Latinos and Whites were more likely to withhold their diagnosis from their parents to prevent worrying them than to avoid personal rejection, this tendency was somewhat stronger among Latinos. Our findings suggest that some traditional values may deter Latinos from seeking HIV-related social support in times of need. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Towards an intelligent tutor for a complex mathematical domain

Abstract: The domain of mathematics has played a special part in the evolution of Intelligent Tutoring Systems (ITSs), beginning as far back as the 1950s when conventional Computer Assisted Instruction (CAI) came into being. A brief historical review of this evolutionary process is presented, followed by a selective survey of some of the intelligent tutoring systems in the mathematics domain as well as some of their shortcomings and the criticisms levelled against them. The work achieved so far towards the realisation of an intelligent tutoring system for a complex mathematical domain is presented. A major conclusion is that the 'mal-rule' methodology for developing tutoring systems may lend itself to simple 'primitive' domains, but its credibility is seriously questioned when it is applied to more 'complex' domains. An alternative methodology is proposed to solve this problem, together with an illustration.     

Self-disclosure of HIV infection: Preliminary results from a sample of Hispanic men.

Examined self-disclosure of HIV infection among 101 adult Hispanic men with HIV infection. Results indicated that disclosure was highly selective and presumably influenced by the social, psychological, and material consequences of informing others about one's medical condition. Ss tended to inform significant others (parents, friends, and lovers) rather than less significant others (employers, landlords, and religious leaders.) There was a high rate of disclosure (75%) to doctors/dentists who were not treating Ss for HIV infection. Gay and bisexual Ss were more inclined to disclose their HIV serostatus to homosexual or bisexual others than to heterosexuals, and to inform those who were aware of their sexual orientation. Disclosure increased with severity of disease independently of length of time since testing seropositive. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The evaluation of an intelligent tutoring system

Abstract

Numerous intelligent tutoring systems (ITSs) have been developed to date. However, one aspect of their development which is consistently ignored, judging from the literature, is the crucial activity of evaluation. It is also ironical that researchers generally agree that the benefits of this activity could be far-reaching. ITSs are often described to some degree of detail but an appraisal as to their (potential) usefulness is seldom given. The relative novelty of doing this was the main motivation for this paper, which starts by attempting to shed some light on why evaluation has become such a taboo activity, not only in intelligent tutoring, but in artificial intelligence (AI) research in general. It then overviews a tutor, the fractions intelligent tutoring system (FITS), and reports on how it was appraised. The approaches used are neither ideal nor generally accepted, but may well provide an adequate starting point in the belief that an attempt at an honest evaluation of any sort is better than no evaluation at all.     

An algorithm for characterizing pre-fuzzified linguistic nuance using artificial neural network

The attractiveness of artificial neural networks (ANNs) in solving many complex real world and computational demanding problems was used in characterizing linguistic nuance for harnessing malicious intent or decoding a communication trend. A set of adjectival watch lists was created a priori to serve as target convergence outputs to the ANN’s graphical user interface designed by the researchers. A set of pre-fuzzified or pre-processed speech conversation or written text was used as inputs to the neural network and represents a sub set of actual words used in the investigated two-way communication. The watch lists represents an editable set of words that represents malicious intent or key elements of conversation intent in bidirectional conversation or communication. The watch list database was generated a priori by identifying adjectives and specific nouns as used in the communication under investigation and then normalized. The pre-processed speech and text have been obtained from Recognizers utilizing the hidden Markov models and its hybrids for its processing. The algorithm showed robustness in sorting out pre-normalized and fuzzified speech that ordinarily contained certain elements of interest as conveyed by the investigated conversations. Analysis of a patient-to-healthcare provider’s bidirectional communication during malaria diagnosis and used for testing the developed algorithm showed significant accuracy when compared with the results of clinical analysis or consultation for the corresponding diagnosis.     

Effect on wettability of the topography and oxidation state of biaxially oriented poly(propylene) film

Surface topography and surface chemistry heterogeneity are widely accepted as causes of contact angle hysteresis. Contact angle hysteresis occurs on essentially all industrial polymer films. Four unmodified and flame-treated biaxially oriented poly(propylene) (BOPP) films produced from the same poly(propylene) base resin, but differing in surface topography and orientation, were characterized by measurement of the advancing and receding contact angles of water and diiodomethane, by atomic force microscopy (AFM) and by x-ray photoelectron spectroscopy (XPS). Contact angle hysteresis was much larger on flame-treated samples than on untreated samples even though some of the untreated films have significantly different topography at the nanoscale.     

User modelling and user adapted interaction in an intelligent tutoring system

User modelling and user-adapted interaction are crucial to the provision of true individualised instruction, which intelligent tutoring systems strive to achieve. This paper presents how user (student) modelling and student adapted instruction is achieved in FITS, an intelligent tutoring system for the fractions domain. Some researchers have begun questioning both the need for detailed student models as well as the pragmatic possibility of building them. The key contributions of this paper are in its attempt to rehabilitate student modelling/adaptive tutoring within ITSs and in FITS's practical use of simple techniques to realise them with seemingly encouraging results; some illustrations are given to demonstrate the latter.     

Intelligent tutoring systems: an overview

This is a non-expert overview of Intelligent Tutoring Systems (ITSs), a way in which Artificial Intelligence (AI) techniques are being applied to education. It introduces ITSs and the motivation for them. It looks at its history: its evolution from Computer-Assisted Instruction (CAI). After looking at the structure of a typical ITS, the paper further examines and discusses some other architectures. Several classic ITSs are reviewed, mainly due to their historical significance or because they best demonstrate some of the principles of intelligent tutoring. A reasonably representative list of ITSs is also provided in order to provide a better appreciation of this vibrant field as well as reveal the scope of existing tutors. The paper concludes, perhaps more appropriately, with some of the author's viewpoints on a couple of controversial issues in the intelligent tutoring domain.