As the use of virtual environments (VEs) is becoming more widespread, user needs are becoming a more significant part in those environments. In order to adapt to the needs of the user, a system should be able to infer user interests and goals. I developed an architecture for user modeling to understand users' interests in a VE by monitoring their actions. In this paper, I discussed the architecture and the virtual environment that was created to test it. This architecture employs sensors to keep track of all the users' actions, data structures that can store a record of significant events that have occurred in the environment, and a rule base. The rule base continually monitors the data collected from the sensors, world state, and event history in order to update the user goal inferences. These inferences can then be used to modify the flow of events within a VE.

Due to the growing need of the Internet and networking technologies, simple, powerful, easily maintained distributed applications needed to be developed. These kinds of applications can benefit greatly from distributed computing concepts. Despite its powerful mechanisms, Jini has yet to be accepted in mainstream Java development. Until that happens, we need to find better Remote Method Invocation (RMI) solutions. Feasibility of implementation of Multicasting in RMI is worked in this paper. Multicasting capability can be used in RMI using Jini-like technique. Support of Multicast over Unicast reference layer is also studied. A piece of code explaining how it can be done, is added.

Content-based image retrieval (CBIR) is the retrieval of images from a collection by means of internal feature measures of the information content of the images. In CBIR systems, text media is usually used only to retrieve exemplar images for further searching by image feature content. This research work describes a new method for integrating multimedia text and image content features to increase the retrieval performance of the system. I am exploring the content-based features of an image extracted from a video to build a storyboard for search retrieval of images. Metadata encoded multimedia features include extracting primitive features like color, shape and text from an image. Histograms are built for all the features extracted and stored in a database. Images are searched based on comparing these histogram values of the extracted image with the stored values. These histogram values are used for extraction of keyframes from a collection of images parsed from a video file. Individual shots of images are extracted from a video clip and run through processes that extract the features and build the histogram values. A keyframe extraction algorithm is run to get the keyframes from the collection of images to build a storyboard of images. In …

The FrameNet database is being used in a variety of NLP research and applications such as word sense disambiguation, machine translation, information extraction and question answering. The database is currently available in XML format. The XML database though a wholesome way of distributing data in its entireness, is not practical for use unless converted to a more application friendly database. In light of this we have successfully converted the XML database to a relational MySQL™ database. This conversion reduced the amount of data storage amount to less than half. Most importantly the new database enables us to perform fast complex querying and facilitates use by applications and research. We show the steps taken to ensure relational integrity of the data during the refactoring process and a simple demo application demonstrating ease of use.

Agent-based architecture explains the rationale and basis for developing agents that can interact with users through natural language query/answer patterns developed systematically using AIML (artificial intelligence mark-up language) scripts. This thesis research document also explains the architecture for VISTA (virtual interactive story-telling agents), which is used for interactive querying in educational and recreational purposes. Agents are very effective as conversational interfaces when used along side with graphical user interface (GUI) in applications and Web pages. This architecture platform can support multiple agents with or with out sharing of knowledgebase. They are very useful as chat robots for recreational purposes, customer service and educational purposes. This platform is powered by Java servlet implementation of Program D and contained in Apache Tomcat server. The AIML scripting language defined here in is a generic form of XML language and forms the knowledgebase of the bot. Animation is provided with Microsoft® Agent technology and text-to-speech support engine.

Due to the rapid growth of wireless networking, the fallible security issues of the 802.11 standard have come under close scrutiny. Nowadays most of the organizations are eager to setup wireless local area networks to reduce the hassles of limited mobility provided by conventional wired network. There are serious security issues that need to be sorted out before everyone is willing to transmit valuable corporate information on a wireless network. This report documents the inherent flaws in wired equivalent privacy protocol used by the 802.11 standard and the ensuing security breaches that can occur to a wireless network due to these flaws. The solutions suggested in this report might not actually make the 802.11 standard secure, but will surely help in the lead up to a secure wireless network standard.

This software is aimed at providing user-friendly, easy-to-use environment for the user to scrub (de-identify/modify) the DICOM header information. Some tools either anonymize or default the values without the user interaction. The user doesn't have the flexibility to edit the header information. One cannot scrub set of images simultaneously (batch scrubbing). This motivated to develop a tool/utility that can scrub a set of images in a single step more efficiently. This document also addresses security issues of the patient confidentiality to achieve protection of patient identifying information and some technical requirements

Machine Learning is the ability of a machine to perform better at a given task, using its previous experience. Various algorithms like decision trees, Bayesian learning, artificial neural networks and instance-based learning algorithms are used widely in machine learning systems. Current applications of machine learning include credit card fraud detection, customer service based on history of purchased products, games and many more. The application of machine learning techniques to natural language processing (NLP) has increased tremendously in recent years. Examples are handwriting recognition and speech recognition. The problem we tackle in this Problem in Lieu of Thesis is applying machine-learning techniques to improve the performance of a conversational agent. The OpenMind repository of common sense, in the form of question-answer pairs is treated as the training data for the machine learning system. WordNet is interfaced with to capture important semantic and syntactic information about the words in the sentences. Further, k-closest neighbors algorithm, an instance based learning algorithm is used to simulate a case based learning system. The resulting system is expected to be able to answer new queries with knowledge gained from the training data it was fed with.

This paper describes the general architecture and function of a Case-Based Reasoning (CBR) system implemented with ASP.NET and C#. Microsoft Visual Studio .NET and XML Web Services provide a flexible, standards-based model that allows clients to access data. Web Form Pages offer a powerful programming model for Web-enabled user interface. The system provides a variety of mechanisms and services related to story retrieval and adaptation. Users may browse and search a library of text stories. More advanced CBR capabilities were also implemented, including a multi-factor distance-calculation for matching user interests with stories in the library, recommendations on optimizing search, and adaptation of stories to match user interests.

World Wide Web caching is widely used through today's Internet. When correctly deployed, Web caching systems can lead to significant bandwidth savings, network load reduction, server load balancing, and higher content availability. A document replacement algorithm that can lower retrieval latency and yield high hit ratio is the key to the effectiveness of proxy caches. More than twenty cache algorithms have been employed in academic studies and in corporate communities as well. But there are some drawbacks in the existing replacement algorithms. To overcome these shortcomings, we developed a new page replacement strategy named as Benchmark-Based Page Replacement (BBPR) strategy, in which a HTTP benchmark is used as a tool to evaluate the current network load and the server load. By our simulation model, the BBPR strategy shows better performance than the LRU (Least Recently Used) method, which is the most commonly used algorithm. The tradeoff is a reduced hit ratio. Slow pages benefit from BBPR.