Learning basic programming concepts in computerscience-related fields poses a challenge for students, to the extent that it becomes an academic-social problem, resulting in high failure and dropout rates. Proposed so...
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As an outstanding representative of traditional Chinese garden art, Suzhou gardens are treasures of human culture. However, its interaction width and depth of dissemination in the international arena still need to be ...
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ISBN:
(纸本)9783031619496;9783031619502
As an outstanding representative of traditional Chinese garden art, Suzhou gardens are treasures of human culture. However, its interaction width and depth of dissemination in the international arena still need to be improved. As a medium widely accepted by the public, digital media can help global cross-cultural audiences understand and appreciate the deep aesthetic and cultural values of gardens and become a link between different cultures. Currently, the integration and innovation of digital media in traditional garden art still need further development, and this revolutionary technology has yet to realize its full potential. Therefore, the main purpose of this paper is to generate artworks such as interactive installations and dynamic images using programming and sound visualization in digital media to address the shortcomings and challenges faced by interactive and generative digital technologies in the application of traditional garden art. This project began with the field trip research method. Initially, we conducted extensive fieldwork in Suzhou gardens, including taking photos and collecting data on different elements within the gardens to capture the gardens' natural landscapes and culture lag in the application of digital media in the culture of classical Chinese gardens and fully utilizing the carrying capacity and dissemination capacity of information technology to breathe new life into the precious cultural heritage of Suzhou garden art.
Joint object matching, also known as multi-image matching, namely, the problem of finding consistent partial maps among all pairs of objects within a collection, is a crucial task in many areas of computer vision. Thi...
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Joint object matching, also known as multi-image matching, namely, the problem of finding consistent partial maps among all pairs of objects within a collection, is a crucial task in many areas of computer vision. This problem subsumes bipartite graph matching and graph partitioning as special cases and is NP-hard, in general. We develop scalable linear programming (LP) relaxations with theoretical performance guarantees for joint object matching. We start by proposing a new characterization of consistent partial maps;this in turn enables us to formulate joint object matching as an integer linear programming (ILP) problem. To construct strong LP relaxations, we study the facial structure of the convex hull of the feasible region of this ILP, which we refer to as the joint matching polytope. We present an exponential family of facet-defining inequalities that can be separated in strongly polynomial time, hence obtaining a partial characterization of the joint matching polytope that is both tight and cheap to compute. To analyze the theoretical performance of the proposed LP relaxations, we focus on permutation group synchronization, an important special case of joint object matching. We show that under the random corruption model for the input maps, a simple LP relaxation, that is, an LP containing only a very small fraction of the proposed facet-defining inequalities, recovers the ground truth with high probability if the corruption level is below 40%. Finally, via a preliminary computational study on synthetic data, we show that the proposed LP relaxations outperform a popular SDP relaxation both in terms of recovery and tightness.
More and more introductory programming courses are being held online, using Automated programming Assessment Systems (APASs). Some APASs provide online editors where students can solve and submit their exercises, beca...
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This paper proposes a novel circuit framework of zeroing neural network for time-varying equality constrained quadratic programming problems (TEQPPs). It is proved that the designed circuit can not only parallel solve...
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ISBN:
(纸本)9789819743988;9789819743995
This paper proposes a novel circuit framework of zeroing neural network for time-varying equality constrained quadratic programming problems (TEQPPs). It is proved that the designed circuit can not only parallel solve TEQPPs in a fixed time, but also cost less hardware resources to be implemented by virtue of its simple structure. Rigorous analysis derives the convergence time upper bound of this novel circuit framework in noiseless and bounded noise polluted condition respectively. Moreover, this circuit can also avoid calculating the pseudoinverse of coefficient matrix when solving TEQPPs. Several circuit experiments are simulated to validate those conclusions.
We introduce and study a two-stage stochastic stable matching problem between students and schools. A decision maker chooses a stable matching in a marriage instance;then, after some agents enter or leave the market f...
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ISBN:
(纸本)9783031598340;9783031598357
We introduce and study a two-stage stochastic stable matching problem between students and schools. A decision maker chooses a stable matching in a marriage instance;then, after some agents enter or leave the market following a probability distribution D, chooses a stable matching in the new instance. The goal is, roughly speaking, to maximize the expected quality of the matchings across the two stages and minimize the expected students' discontent for being downgraded to a less preferred school in the second-stage. We consider both the case when D is given explicitly and when it is accessed via a sampling oracle. In the former case, we give a polynomial time algorithm. In the latter case, we show that, unless P = NP, no algorithm can find the optimal value or the optimal solution of the problem in polynomial-time. On the positive side, we give a pseudopolynomial algorithm that computes a solution of arbitrarily small additive error. Our techniques include the use of a newly defined poset of stable pairs, which may be of independent interest.
The rise of Large Language Models (LLMs) has sparked discussion in computerscience Education (CSE) due to their ability to generate code from text prompts. Students may rely on these tools, neglecting core skills lik...
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ISBN:
(纸本)9798400710384
The rise of Large Language Models (LLMs) has sparked discussion in computerscience Education (CSE) due to their ability to generate code from text prompts. Students may rely on these tools, neglecting core skills like computational thinking and program design. Thus, it's crucial to responsibly integrate them into computerscience courses. To address this, we integrated an open-source Automatic Assessment Tool with GPT, enabling students to receive LLM assistance on their programming assignments. This tool can be adopted and improved by educators, promoting more responsible integration of LLMs in CSE.
Point set registration, crucial in computer vision and robotics applications, encounters challenges, such as noise, outliers, and misalignment. Current methods often struggle with these issues, leading to suboptimal r...
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Point set registration, crucial in computer vision and robotics applications, encounters challenges, such as noise, outliers, and misalignment. Current methods often struggle with these issues, leading to suboptimal registration accuracy. This article proposes a novel graph correspondence-based algorithm to address these challenges in rigid point set registration. We model point sets as graphs, transforming the registration problem into a graph isomorphism problem. This approach is enhanced with probabilistic linear programming heuristics to efficiently establish correspondences between point sets. Our method significantly improves robustness against common registration errors and does not require initial pose estimation, a notable advantage over existing algorithms. Extensive experiments on various datasets, including applications in intelligent vehicle mapping and localization, demonstrate superior performance in correspondence establishment and registration accuracy compared to state-of-the-art methods, particularly under conditions of noise, outliers, and misalignment.
Game design is often considered a motivational approach to get young children interested in programming and computational thinking. However, while the idea of game programming may be compelling from an educational poi...
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ISBN:
(纸本)9798400710056
Game design is often considered a motivational approach to get young children interested in programming and computational thinking. However, while the idea of game programming may be compelling from an educational point of view, creating games with interesting interactions that are actually fun to play remains challenging. Modern tools aimed at novice programmers should empower their users to create games, such as Pac-Man, that approach or even exceed the gameplay of 1980's arcade games. By adding a high-level AI pathfinding block to the *** tool, 13 students in grades 1-4 attempted to build Pac-Man-like games. The findings suggest that all students were able to create Pac-Man-like games with compelling gameplay interactions, including ghosts finding the shortest path through complex mazes to Pac-Man, multiple ghosts collaborating with each other, and sophisticated game world topologies featuring toroidal portals.
Introducing component-based programming to high school students can stimulate their interest in pursuing computerscience studies at the university level. In this contribution, we explore the potential of using mobile...
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