We introduce a new approach to multivariate polynomial factorisation which incorporates ideas from polyhedral geometry, and generalises Hensel lifting. Our main contribution is to present an algorithm for factoring bivariate polynomials which is able to exploit to some extent the sparsity of polynomials. We give details of an implementation which we used to factor randomly chosen sparse and composite polynomials of high degree over the binary field.

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A capstone project is a culminating experience that entails creativity, critical thinking, and advanced problem-solving skills. To that end, capstone projects enable students to prove their abilities, demonstrate their attained skills, and carry out a significant project in their field. In Computer Science Bachelor programs, there is a strong mapping between learning outcomes of capstone projects and all student learning outcomes. This paper presents an assessment framework for capstone courses that allows for sound evaluations of the performance of students and project qualities; besides assessing the student outcomes of the program. The developed framework comprises criteria, indicators, extensive analytic rubrics, and a summative statistical formulation. The presented course and framework are supported by the results, analysis, and evaluation of a pilot study for a single institution to explore the effectiveness of the proposed tool.

Background: As the world's population ages, the prevalence of cognitive decline, dementia and Alzheimer's disease is on the increasing trend. From a public health perspective and the absence of a cure, the early identification of individuals at risk of dementia becomes of paramount importance for proper early prevention. We developed a ML application for dementia diagnosis that is based on the 10/66 one stage dementia diagnostic algorithm.