16,159 research outputs found
Summer of Code: Assisting Distance-Learning Students with Open-Ended Programming Tasks
A significant difficulty in teaching programming lies in the transition from novice to intermediate programmer, characterised by the assimilation and use of schemas of standard programming approaches. A significant factor assisting this transition is practice with tasks which develop this schema use. We describe the Summer of Code, a two-week activity for part-time, distance-learning students which gave them some additional programming practice. We analysed their submissions, forum postings, and results of a terminal survey. We found learners were keen to share and discuss their solutions and persevered with individual problems and the challenge overall. 93% respondents rated the activity 3 or better on a 5-point Likert scale (n=58). However, a quarter of participants, mainly those who described themselves as average or poor programmers, felt less confident in their abilities after the activity, though half of these students liked the activity overall. 54% of all participants said the greatest challenge was developing a general approach to the problems, such as selecting appropriate data structures. This is corroborated by forum comments, where students greatly appreciated “think aloud” presentations by faculty tackling the problems. These results strongly suggest that students would benefit from more open-ended practice, where they have to select and design their own solutions to a range of problems
Problem solving in ID-logic with aggregates: some experiments
The goal of the LP+ project at the K.U.Leuven is to design an expressive
logic, suitable for declarative knowledge representation, and to develop
intelligent systems based on Logic Programming technology for solving
computational problems using the declarative specifications. The ID-logic is an
integration of typed classical logic and a definition logic. Different
abductive solvers for this language are being developed. This paper is a report
of the integration of high order aggregates into ID-logic and the consequences
on the solver SLDNFA.Comment: 9 pages conference: NMR2000, special track on abductive reasonin
JigsawNet: Shredded Image Reassembly using Convolutional Neural Network and Loop-based Composition
This paper proposes a novel algorithm to reassemble an arbitrarily shredded
image to its original status. Existing reassembly pipelines commonly consist of
a local matching stage and a global compositions stage. In the local stage, a
key challenge in fragment reassembly is to reliably compute and identify
correct pairwise matching, for which most existing algorithms use handcrafted
features, and hence, cannot reliably handle complicated puzzles. We build a
deep convolutional neural network to detect the compatibility of a pairwise
stitching, and use it to prune computed pairwise matches. To improve the
network efficiency and accuracy, we transfer the calculation of CNN to the
stitching region and apply a boost training strategy. In the global composition
stage, we modify the commonly adopted greedy edge selection strategies to two
new loop closure based searching algorithms. Extensive experiments show that
our algorithm significantly outperforms existing methods on solving various
puzzles, especially those challenging ones with many fragment pieces
A collection of arithmetic exercises designed particularly for the superior child in grade three of four to supplement the standard program at those grade levels
Thesis (Ed.M.)--Boston Universit
Solving sudoku's by evolutionary algorithms with pre-processing
This paper handles the popular Sudoku puzzle and studies how to improve evolutionary algorithm solving by first pre-processing Sudoku solving with the most common known solving methods. We found that the pre-processing solves some of the easiest Sudoku’s so we do not even need other methods. With more difficult Sudoku’s the pre-processing reduce the positions needed to solve dramatically, which means that evolutionary algorithm finds the solution much faster than without the pre-processing.fi=vertaisarvioitu|en=peerReviewed
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