Communication net of modular processors for a multiprocessor computer /

"This work was submitted in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering, June 1967, and was supported in part by the AEC under Contract No. USAEC AT(11-1)1018.

RASCEL: a programmable analog computer based on a regular array of stochastic computing element logic

Thesis--University of Illinois.

Computer design study : access time /

"1-10-1955"

A computer simulation of a large scale academic computer system.

Thesis (M.S.)--University of Illinois.

CADS*: Computer-Aided Development of self-* systems

We present the prototype tool CADS* for the computer-aided development of an important class of self-* systems, namely systems whose components can be modelled as Markov chains. Given a Markov chain representation of the IT components to be included into a self-* system, CADS* automates or aids (a) the development of the artifacts necessary to build the self-* system; and (b) their integration into a fully-operational self-* solution. This is achieved through a combination of formal software development techniques including model transformation, model-driven code generation and dynamic software reconfiguration.

Signal processing of physiological signals for automated assessment of stress in computer users

The need to provide computers with the ability to distinguish the affective state of their users is a major requirement for the practical implementation of affective computing concepts. This dissertation proposes the application of signal processing methods on physiological signals to extract from them features that can be processed by learning pattern recognition systems to provide cues about a person's affective state. In particular, combining physiological information sensed from a user's left hand in a non-invasive way with the pupil diameter information from an eye-tracking system may provide a computer with an awareness of its user's affective responses in the course of human-computer interactions. In this study an integrated hardware-software setup was developed to achieve automatic assessment of the affective status of a computer user. A computer-based "Paced Stroop Test" was designed as a stimulus to elicit emotional stress in the subject during the experiment. Four signals: the Galvanic Skin Response (GSR), the Blood Volume Pulse (BVP), the Skin Temperature (ST) and the Pupil Diameter (PD), were monitored and analyzed to differentiate affective states in the user. Several signal processing techniques were applied on the collected signals to extract their most relevant features. These features were analyzed with learning classification systems, to accomplish the affective state identification. Three learning algorithms: Naïve Bayes, Decision Tree and Support Vector Machine were applied to this identification process and their levels of classification accuracy were compared. The results achieved indicate that the physiological signals monitored do, in fact, have a strong correlation with the changes in the emotional states of the experimental subjects. These results also revealed that the inclusion of pupil diameter information significantly improved the performance of the emotion recognition system. ^

Detecting stealthy attacks: Efficient monitoring of suspicious activities on computer networks

Stealthy attackers move patiently through computer networks - taking days, weeks or months to accomplish their objectives in order to avoid detection. As networks scale up in size and speed, monitoring for such attack attempts is increasingly a challenge. This paper presents an efficient monitoring technique for stealthy attacks. It investigates the feasibility of proposed method under number of different test cases and examines how design of the network affects the detection. A methodological way for tracing anonymous stealthy activities to their approximate sources is also presented. The Bayesian fusion along with traffic sampling is employed as a data reduction method. The proposed method has the ability to monitor stealthy activities using 10-20% size sampling rates without degrading the quality of detection.

A model for computer profiling

This paper discusses the use of models in automatic computer forensic analysis, and proposes and elaborates on a novel model for use in computer profiling, the computer profiling object model. The computer profiling object model is an information model which models a computer as objects with various attributes and inter-relationships. These together provide the information necessary for a human investigator or an automated reasoning engine to make judgements as to the probable usage and evidentiary value of a computer system. The computer profiling object model can be implemented so as to support automated analysis to provide an investigator with the information needed to decide whether manual analysis is required.

Facilitating learning in a real time strategy computer game

The aim of this project was to implement a just-in-time hints help system into a real time strategy (RTS) computer game that would deliver information to the user at the time that it would be of the most benefit. The goal of this help system is to improve the user’s learning in terms of their rate of learning, retention and avoidance of stagnation. The first stage of this project was implementing a computer game to incorporate four different types of skill that the user must acquire, namely motor, perceptual, declarative knowledge and strategic. Subsequently, the just-in-time hints help system was incorporated into the game to assess the user’s knowledge and deliver hints accordingly. The final stage of the project was to test the effectiveness of this help system by conducting two phases of testing. The goal of this testing was to demonstrate an increase in the user’s assessment of the helpfulness of the system from phase one to phase two. The results of this testing showed that there was no significant difference in the user’s responses in the two phases. However, when the results were analysed with respect to several categories of hints that were identified, it became apparent that patterns in the data were beginning to emerge. The conclusions of the project were that further testing with a larger sample size would be required to provide more reliable results and that factors such as the user’s skill level and different types of goals should be taken into account.

Hybrid-Game Strategies for multi-objective design optimization in engineering

A number of Game Strategies (GS) have been developed in past decades. They have been used in the fields of economics, engineering, computer science and biology due to their efficiency in solving design optimization problems. In addition, research in multi-objective (MO) and multidisciplinary design optimization (MDO) has focused on developing robust and efficient optimization methods to produce a set of high quality solutions with low computational cost. In this paper, two optimization techniques are considered; the first optimization method uses multi-fidelity hierarchical Pareto optimality. The second optimization method uses the combination of two Game Strategies; Nash-equilibrium and Pareto optimality. The paper shows how Game Strategies can be hybridised and coupled to Multi-Objective Evolutionary Algorithms (MOEA) to accelerate convergence speed and to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid-Game Strategies are clearly demonstrated

Computer-intensive simulations for cellular models

-

Pedagogy of introductory computer programming : a people-first approach

Students struggle with learning to program. In recent years, not only has there been a dramatic drop in the number of students enrolling in IT and Computer Science courses, but attrition from these courses continues to be significant. Introductory programming subjects traditionally have high failure rates and as they tend to be core to IT and Computer Science courses can be a road block for many students to their university studies. Is programming really that difficult — or are there other barriers to learning that have a serious and detrimental effect on student progression? In-class experiments were conducted in introductory programming units to confirm our hypothesis that that pair-programming would benefit students' learning to program. We investigated the social and cultural barriers to learning programming by questioning students' perceptions of confidence, difficulty and enjoyment of programming. The results of paired and non-paired students were compared to determine the effect of pair-programming on learning outcomes. Both the empirical and anecdotal results of our experiments strongly supported our hypothesis.

Efficient hybrid-game strategies coupled to evolutionary algorithms for robust multidisciplinary design optimization in aerospace engineering

A number of game strategies have been developed in past decades and used in the fields of economics, engineering, computer science, and biology due to their efficiency in solving design optimization problems. In addition, research in multiobjective and multidisciplinary design optimization has focused on developing a robust and efficient optimization method so it can produce a set of high quality solutions with less computational time. In this paper, two optimization techniques are considered; the first optimization method uses multifidelity hierarchical Pareto-optimality. The second optimization method uses the combination of game strategies Nash-equilibrium and Pareto-optimality. This paper shows how game strategies can be coupled to multiobjective evolutionary algorithms and robust design techniques to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid and non-Hybrid-Game strategies are demonstrated.

Quality metrics for assessing security-critical computer programs

Existing secure software development principles tend to focus on coding vulnerabilities, such as buffer or integer overflows, that apply to individual program statements, or issues associated with the run-time environment, such as component isolation. Here we instead consider software security from the perspective of potential information flow through a program’s object-oriented module structure. In particular, we define a set of quantifiable "security metrics" which allow programmers to quickly and easily assess the overall security of a given source code program or object-oriented design. Although measuring quality attributes of object-oriented programs for properties such as maintainability and performance has been well-covered in the literature, metrics which measure the quality of information security have received little attention. Moreover, existing securityrelevant metrics assess a system either at a very high level, i.e., the whole system, or at a fine level of granularity, i.e., with respect to individual statements. These approaches make it hard and expensive to recognise a secure system from an early stage of development. Instead, our security metrics are based on well-established compositional properties of object-oriented programs (i.e., data encapsulation, cohesion, coupling, composition, extensibility, inheritance and design size), combined with data flow analysis principles that trace potential information flow between high- and low-security system variables. We first define a set of metrics to assess the security quality of a given object-oriented system based on its design artifacts, allowing defects to be detected at an early stage of development. We then extend these metrics to produce a second set applicable to object-oriented program source code. The resulting metrics make it easy to compare the relative security of functionallyequivalent system designs or source code programs so that, for instance, the security of two different revisions of the same system can be compared directly. This capability is further used to study the impact of specific refactoring rules on system security more generally, at both the design and code levels. By measuring the relative security of various programs refactored using different rules, we thus provide guidelines for the safe application of refactoring steps to security-critical programs. Finally, to make it easy and efficient to measure a system design or program’s security, we have also developed a stand-alone software tool which automatically analyses and measures the security of UML designs and Java program code. The tool’s capabilities are demonstrated by applying it to a number of security-critical system designs and Java programs. Notably, the validity of the metrics is demonstrated empirically through measurements that confirm our expectation that program security typically improves as bugs are fixed, but worsens as new functionality is added.