Gautam Biswas

Learn More
The complexity of present day embedded systems (continuous processes controlled by digital processors), and the increased demands on their reliability motivate the need for monitoring and fault isolation capabilities in the embedded processors. This paper develops monitoring, prediction, and fault isolation methods for abrupt faults in complex dynamic(More)
This paper discusses Betty’s Brain, a teachable agent in the domain of river ecosystems that combines learning by teaching with self-regulation mentoring to promote deep learning and understanding. Two studies demonstrate the effectiveness of this system. The first study focused on components that define student-teacher interactions in the learning by(More)
The idea that teaching others is a powerful way to learn is intuitively compelling and supported in the research literature. We have developed computer-based, domain-independent Teachable Agents that students can teach using a visual representation. The students query their agent to monitor their learning and problem solving behavior. This motivates the(More)
ÐThis paper presents a Similarity-Based Agglomerative Clustering (SBAC) algorithm that works well for data with mixed numeric and nominal features. A similarity measure, proposed by Goodall for biological taxonomy [15], that gives greater weight to uncommon feature value matches in similarity computations and makes no assumptions of the underlying(More)
This paper addresses the problem of tracking and diagnosing complex systems with mixtures of discrete and continuous variables. This problem is a difficult one, particularly when the system dynamics are nondeterministic, not all aspects of the system are directly observed, and the sensors are subject to noise. In this paper, we propose a new approach to(More)
|The data exploration task can be divided into three interrelated subtasks: (i) feature selection, (ii) discovery, and (iii) interpretation. This paper describes an unsupervised discovery method with biases geared toward partitioning objects into clusters that improve interpretability. The algorithm, ITERATE, employs: (i) a data ordering scheme and (ii) an(More)
BACKGROUND In its first 8 years, the Global Programme to Eliminate Lymphatic Filariasis (GPELF) achieved an unprecedentedly rapid scale-up: >1.9 billion treatments with anti-filarial drugs (albendazole, ivermectin, and diethylcarbamazine) were provided via yearly mass drug administration (MDA) to a minimum of 570 million individuals living in 48 of the 83(More)
Autonomous agents that sense, reason, and act in real-world environments for extended periods often need to solve streams of incoming problems. Traditionally, effort is applied only to problems that have already arrived and have been noted. We examine continual computation methods that allow agents to ideally allocate time to solving current as well as(More)
We have developed a learning environment where students teach a computer agent, using visual representations, and can monitor the agent’s learning progress by asking her questions and having her take quizzes. The system provides self-regulated learning and metacognitive support via dialogembedded prompts from Betty, the teachable agent, and Mr. Davis, the(More)
The geographical distribution of human infection with Wuchereria bancrofti was investigated in four West African countries (Benin, Burkina Faso, Ghana and Togo), using a commercial immunochromatographic test for filarial antigen. Efforts were made to cover each health-system implementation unit and to ensure no sampling point was >50 km from another, but(More)