Among the early applications of computers, one can find frequent mention of intelligent instructional systems. Such intelligent instructional systems represent a new generation of learner-based computer aided instruction, preceded in time by the original frame-based systems and an intervening generation of expert-based CAI. The history of CAI is characterized by three generations: Frame-based CAI, Expert-based CAI and Learner-based CAI.

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.

The C Navigational System (CNS) is a proposed programming environment for the C programming language. The introduction covers the major influences of programming environments and the components of a programming environment. The system is designed to support the design, coding and maintenance phases of software development. CNS provides multiple views to both the source and documentation for a programming project. User-defined and system-defined links allow the source and documentation to be hierarchically searched. CNS also creates a history list and function interface for each function in a module. The final chapter compares CNS and several other programming environments (Microscope, Rn, Cedar, PECAN, and Marvel).

Server load balancing technology has obtained much attention as much business proceeded towards e-commerce. The idea behind is to have set of clustered servers that share the load as against a single server to achieve better performance and throughput. In this problem in lieu of thesis, I propose and evaluate an implementation of a prototype scalable server. The prototype consists of a load-balanced cluster of hosts that collectively accept and service TCP connections. The host IP addresses are advertised using the Round Robin DNS technique, allowing any host to receive requests from any client. Once a client attempts to establish a TCP connection with one of the hosts, a decision is made as to whether or not the connection should be redirected to a different host namely, the host with the lowest number of established connections. This problem in lieu of thesis outlines the history of load balancing, various options available today and finally approach for implementing the prototype and the corresponding findings.

The spread of infectious diseases has been a public concern throughout human history. Historic recorded data has reported the severity of infectious disease epidemics in different ages. Ancient Greek physician Hippocrates was the first to analyze the correlation between diseases and their environment. Nowadays, health authorities are in charge of planning strategies that guarantee the welfare of citizens. The simulation of contagion scenarios contributes to the understanding of the epidemic behavior of diseases. Computational models facilitate the study of epidemics by integrating disease and population data to the simulation. The use of detailed demographic and geographic characteristics allows researchers to construct complex models that better resemble reality and the integration of these attributes permits us to understand the rules of interaction. The interaction of individuals with similar characteristics forms synthetic structures that depict clusters of interaction. The synthetic environments facilitate the study of the spread of infectious diseases in diverse scenarios. The characteristics of the population and the disease concurrently affect the local and global epidemic progression. Every cluster’ epidemic behavior constitutes the global epidemic for a clustered population. By understanding the correlation between structured populations and the spread of a disease, current dissertation research makes possible to identify risk …

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.

The history of mitigation programs to contain vector-borne diseases is a story of successes and failures. Due to the complex interplay among multiple factors that determine disease dynamics, the general principles for timely and specific intervention for incidence reduction or eradication of life-threatening diseases has yet to be determined. This research discusses computational methods developed to assist in the understanding of complex relationships affecting vector-borne disease dynamics. A computational framework to assist public health practitioners with exploring the dynamics of vector-borne diseases, such as malaria and dengue in homogenous and heterogeneous populations, has been conceived, designed, and implemented. The framework integrates a stochastic computational model of interactions to simulate horizontal disease transmission. The intent of the computational modeling has been the integration of stochasticity during simulation of the disease progression while reducing the number of necessary interactions to simulate a disease outbreak. While there are improvements in the computational time reducing the number of interactions needed for simulating disease dynamics, the realization of interactions can remain computationally expensive. Using multi-threading technology to improve performance upon the original computational model, multi-threading experimental results have been tested and reported. In addition, to the contact model, the modeling of biological processes specific to …

Many calamities in history like hurricanes, tornado and flooding are proof to the large scale impact they cause to the life and economy. Computer simulation and GIS helps in modeling a real world scenario, which assists in evacuation planning, damage assessment, assistance and reconstruction. For achieving computer simulation and modeling there is a need for accurate classification of ground objects. One of the most significant aspects of this research is that it achieves improved classification for regions within which light detection and ranging (LiDAR) has low spatial resolution. This thesis describes a method for accurate classification of bare ground, water body, roads, vegetation, and structures using LiDAR data and aerial Infrared imagery. The most basic step for any terrain modeling application is filtering which is classification of ground and non-ground points. We present an integrated systematic method that makes classification of terrain and non-terrain points effective. Our filtering method uses the geometric feature of the triangle meshes created from LiDAR samples and calculate the confidence for every point. Geometric homogenous blocks and confidence are derived from TIN model and gridded LiDAR samples. The results from two representations are used in a classifier to determine if the block belongs ground or …

This is a brief survey of some of the popular computer systems. As many features as possible have been covered in order to get an overview of the systems under consideration.

This research establishes the feasibility and potential utility of a software mechanism which employs artificial intelligence techniques to enhance the capabilities of standard discrete event simulators. As background, current methods of integrating artificial intelligence with simulation and relevant research are briefly reviewed.

The author's primary goal is to begin research leading ot the attainment of a low cost computer/music system which will allow the composer to write polyphonic music of up to eight voices into a computer through a terminal, and have the music played back by means of computer synthesized sound or by means of a conventional synthesizer controlled by a computer via digital-to-analog converters. The goal system will allow the composer to retreat and hear his product objectively as the painter steps back to review his canvas.

Numerical methods are usually necessary in solving Hamiltonian systems since there is often no closed-form solution. By utilizing a general property of Hamiltonians, namely the symplectic property, all of the qualities of the system may be preserved for indefinitely long integration times because all of the integral (Poincare) invariants are conserved. This allows for more reliable results and frequently leads to significantly shorter execution times as compared to conventional methods. The resonant triad Hamiltonian with one degree of freedom will be focused upon for most of the numerical tests because of its difficult nature and, moreover, analytical results exist whereby useful comparisons can be made.

This research explores the concepts of defensive programming as currently defined in the literature. Then these concepts are extended and more explicitly defined. The relationship between defensive programming, as presented in this research, and current programming practices is discussed and several benefits are observed. Defensive programming appears to benefit the entire software life cycle. Four identifiable phases of the software development process are defined, and the relationship between these four phases and defensive programming is shown. In this research, defensive programming is defined as writing programs in such a way that during execution the program itself produces communication allowing the programmer and the user to observe its dynamic states accurately and critically. To accomplish this end, the use of defensive programming snap shots is presented as a software development tool.

I start with a brief introduction to the graphics processing unit (GPU) as well as general-purpose computation on modern graphics hardware (GPGPU). Next, I explore the motivations for GPGPU programming, and the capabilities of modern GPUs (including advantages and disadvantages). Also, I give the background required for further exploring GPU programming, including the terminology used and the resources available. Finally, I include a comprehensive survey of previous and current GPGPU work, and end with a look at the future of GPU programming.

Two applications of a binary tree data type based on a simple pairing function (a bijection between natural numbers and pairs of natural numbers) are explored. First, the tree is used to encode natural numbers, and algorithms that perform basic arithmetic computations are presented along with formal proofs of their correctness. Second, using this "canonical" representation as a base type, algorithms for encoding and decoding additional isomorphic data types of other mathematical constructs (sets, sequences, etc.) are also developed. An experimental application to a memory management system is constructed and explored using these isomorphic types. A practical analysis of this system's runtime complexity and space savings are provided, along with a proof of concept framework for both applications of the binary tree type, in the Java programming language.

Email connects 85% of the world. This paper explores the pattern of information overload encountered by majority of email users and examine what steps key email providers are taking to combat the problem. Besides fighting spam, popular email providers offer very limited tools to reduce the amount of unwanted incoming email. Rather, there has been a trend to expand storage space and aid the organization of email. Storing email is very costly and harmful to the environment. Additionally, information overload can be detrimental to productivity. We propose a simple solution that results in drastic reduction of unwanted mail, also known as graymail.

In response to the recent intensive needs for civilian security surveillance, both full and compact versions of a Multimedia Security Surveillance (MSS) system have been built up. The new Microsoft DirectShow technology was applied in implementing the multimedia stream-processing module. Through Microsoft Windows Driver Model interface, the chosen IEEE1394 enabled Fire-i cameras as external sensors are integrated with PC based continuous storage unit. The MSS application also allows multimedia broadcasting and remote controls. Cost analysis is included.

Guiding navigation in virtual environments (VEs) is a challenging task. A key issue in the navigation of a virtual environment is to be able to strike a balance between the user's need to explore the environment freely and the designer's need to ensure that the user experiences all the important events in the VE. This thesis reports on a study aimed at comparing the effectiveness of various navigation cues that are used to motivate users towards a specific target location. The results of this study indicate some significant differences in how users responded to the various cues.

Efficient unification is considered within the context of logic programming. Unification is explained in terms of equivalence classes made up of terms, where there is a constraint that no equivalence class may contain more than one function term. It is demonstrated that several well-known "efficient" but nonlinear unification algorithms continually maintain the said constraint as a consequence of their choice of data structure for representing equivalence classes. The linearity of the Paterson-Wegman unification algorithm is shown largely to be a consequence of its use of unbounded lists of pointers for representing equivalences between terms, which allows it to avoid the nonlinearity of "union-find".

There have been a number of different versioning models proposed. The research in this area can be divided into two categories: object versioning and schema versioning. In this dissertation, both problem domains are considered as a single unit. This dissertation describes a unifying version model (UVM) for maintaining changes to both objects and schema. UVM handles schema versioning operations by using object versioning techniques. The result is that the UVM allows the OODBMS to be much smaller than previous systems. Also, programmers need know only one set of versioning operations; thus, reducing the learning time by half. This dissertation shows that UVM is a simple but semantically sound and powerful version model for both objects and schema.

No matter how extended the use of the computer is, the printed document is still the primary medium for the presentation information, and will continue to be for some time. The use of computing facilities for preparation and production of the document is becoming as prevalent as their use for numeric computation. Commercially, document preparation systems are now a standard facility at research institution, and they have become quite common on each computer program. A conventional document preparation system usually contains two parts: a text editor used to create, enter, update, and maintain the text and control words that comprise the document in its "input" form, and a text formatter used to process that input and produce the final document.

Consumer's opinions and sentiments on products can reflect the performance of products in general or in various aspects. Analyzing these data is becoming feasible, considering the availability of immense data and the power of natural language processing. However, retailers have not taken full advantage of online comments. This work is dedicated to a solution for automatically analyzing and summarizing these valuable data at both product and category levels. In this research, a system was developed to retrieve and analyze extensive data from public online resources. A parallel framework was created to make this system extensible and efficient. In this framework, a star topological network was adopted in which each computing unit was assigned to retrieve a fraction of data and to assess sentiment. Finally, the preprocessed data were collected and summarized by the central machine which generates the final result that can be rendered through a web interface. The system was designed to have sound performance, robustness, manageability, extensibility, and accuracy.

Our generation has experienced one of the most dramatic changes in how society communicates. Today, we have online information on almost any imaginable topic. However, most of this information is available in only a few dozen languages. In this thesis, I explore the use of parallel texts to enable cross-language information retrieval (CLIR) for languages with scarce resources. To build the parallel text I use the Bible. I evaluate different variables and their impact on the resulting CLIR system, specifically: (1) the CLIR results when using different amounts of parallel text; (2) the role of paraphrasing on the quality of the CLIR output; (3) the impact on accuracy when translating the query versus translating the collection of documents; and finally (4) how the results are affected by the use of different dialects. The results show that all these variables have a direct impact on the quality of the CLIR system.

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.