This article is the fifth in a series of articles from our study examining information-seeking behavior in relation to information-retrieval (IR) interaction. This article focuses on the examination of the interaction variables within Saracevic's (1989) triadic IR model. The analysis involved an examination of the information-searching behavior of academic researchers during a mediated interaction with an IR system, particularly concentrating on the interaction between the information seeker, the search intermediary, and the IR system. To explore the variables during mediated search interaction, two smallscale studies of mediated on-line searching were conducted at the University of Sheffield. The studies involved mainly qualitative data analysis of interview transcripts and on-line search results, together with quantitative data analysis of questionnaire results. The studies specifically investigated: (1) aspects of the mediated search process, (2) relevant information sources, and (3) interaction measures derived from search logs and tape transcripts, and related interaction measures. Findings include: (1) a number of different types of interactions were identified, (2) the presearching interactions between information seeker and intermediary aided the information seeker to identify their idea and problem, and (3) most information seekers in this study were at the problem definition stage or problem resolution stage following the search process. From this research, it is clear that the interaction did affect the search process. The intermediary helped the users to identify their search terms more clearly and focus on the references obtained. In most cases, the users and intermediary considered the communication process very effective, and the interactions that took place during the on-line search were found to affect the users' perceptions of the problem, personal knowledge, and relevance judgments. The interaction process aided the users to obtain very useful results with help from the intermediary. In general, the users gave a positive evaluation of the retrieved answers in terms of focus, completeness, novelty, and degree of nonrelevancy.
The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is a synthetic imagery generation model developed at the Center for Imaging Science (CIS) at the Rochester Institute of Technology (RIT). It is a quantitative first principle based model that calculates the sensor reaching radiance from the visible through to the long wave infrared on a spectral basis. DIRSIG generates a very accurate representation of what a sensor would see by modeling all the processes involved in the imaging chain. Currently, DIRSIG only models passive sources such as the sun and blackbody radiation due to the temperature of an object. Active systems have the benefit of the user being able to control the illumination source and tailor it for specific applications. Remote sensing Laser Detection and Ranging (LADAR) systems that utilize a laser as the active source have been in existence for over 30 years. Recent advances in tunable lasers and infrared detectors have allowed much more sophisticated and accurate work to be done, but a comprehensive spectral LADAR model has yet to be developed. In order to provide a tool to assist in LADAR development, this research incorporates a first principle based elastic LADAR model into DIRSIG. It calculates the irradiance onto the focal plane on a spectral basis for both the atmospheric and topographic return, based on the system characteristics and the assumed atmosphere. The geometrical form factor, a measure of the overlap between the sensor and receiver field-of-view, is carefully accounted for in both the monostatic and bistatic cases. The model includes the effect of multiple bounces from topographical targets. Currently, only direct detection systems will be modeled. Several sources of noise are extensively modeled, such as speckle from rough surfaces. Additionally, atmospheric turbulence effects including scintillation, beam effects, and image effects are accounted for. To allow for future growth, the model and coding are modular and anticipate the inclusion of advanced sensor models and inelastic scattering.
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