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关键词： 数字游戏   中华优秀传统文化   黑神话:悟空   国际传播  

摘要： 数字游戏是新兴的文化传播载体,在促进中华优秀传统文化国际传播、增强青年群体民族文化自信方面,扮演着愈加重要的角色。本文以《黑神话:悟空》游戏为例,探究游戏中的中华优秀传统文化的表征模式,总结游戏推动中华优秀传统文化国际传播的实践进路。研究发现,《黑神话:悟空》利用游戏媒介所具备的技术性、互动性与社群性特征,打造出具有中式美学风格与中式哲学思想的游戏文化空间,为玩家提供了沉浸式的文化体验。通过深入挖掘文化IP,符码转译与破圈传播,《黑神话:悟空》在国际传播中取得显著效果,为后续基于游戏的“文化出海”提供了有益借鉴。

关键词： Costs   Vehicle dynamics   Urban areas   Docking stations   Deep reinforcement learning   Scalability   Optimization   Electronic mail   Computer science   Shared transport   Dynamic bike repositioning   reinforcement learning   resource allocation  

摘要： Bike Sharing Systems (BSS) represent a sustainable and efficient urban transportation solution. A major challenge in BSS is repositioning bikes to avoid shortage events when users encounter empty or full bike lockers. Existing algorithms unrealistically rely on precise demand forecasts and tend to overlook substantial operational costs associated with reallocations. This paper introduces a novel Cost-aware Adaptive Bike Repositioning Agent (CABRA), which harnesses advanced deep reinforcement learning techniques in dock-based BSS. By analyzing demand patterns, CABRA learns adaptive repositioning strategies aimed at reducing shortages and enhancing truck route planning efficiency, significantly lowering operational costs. We perform an extensive experimental evaluation of CABRA utilizing real-world data from Dublin, London, Paris, and New York. The reported results show that CABRA achieves operational efficiency that outperforms or matches very challenging baselines, obtaining a significant cost reduction. Its performance on the largest city comprising 1765 docking stations highlights the efficiency and scalability of the proposed solution even when applied to BSS with a great number of docking stations.

关键词： Artificial intelligence   Computer science education   Ethics   Teaching and learning  

摘要： Emerging systems using artificial intelligence (AI) including the complexities of deep learning leading to decision-making outcomes pose challenge, risk alongside opportunities to revolutionize business sectors and thus, human life. Building AI that impact on critical decision-making must be entwined with ethical questioning from the initial conception of design. As academics educating future technologists, we must lead on embedding the importance of ethical thinking for equitable designed systems. Currently, it is unclear across UK Higher Education how widely ethics is taught across programmes of study within computer science disciplines, their importance within the curriculum plus the confidence of academics for its delivery. This paper carries out a survey analysis to identify gaps, measures of engagement, expertise and knowledgebase of topics through both quantitative and qualitative questioning. The survey was distributed to 15 member universities of the Council for Professors and Heads of Computing (CPHC) randomly selected across the UK for which 32 academics engaged in the study. Results show ethics was noted as being important although one-third reported it was not widely embedded across the curriculum. Just less than half of participants schedule the teaching of ethics regularly either across one or several modules. Interestingly, 91% of respondents stated that they have not received any instruction or training and that 62% felt that they require more training on the subject matter. This paper is inspired by wider research from European studies however, this study provides a specific novel focus on a broad range of UK universities, providing comparative analysis and unique findings from the UK perspective. The significance of these findings suggest academics perspectives vary with specific training needs. This demonstrates that this early-stage research requires further exploration of the wider computer science curriculum, sharing of good practice and colla

关键词： Codes   Error correction codes   Vectors   Codecs   Linear codes   Upper bound   Instruments   Hamming distances   Computer science   Nearly perfect codes   perfect codes   sphere-covering bound   weight distribution  

摘要： Nearly perfect packing codes are those codes that meet the Johnson upper bound on the size of error-correcting codes. This bound is an improvement to the sphere-packing bound. A related bound for covering codes is known as the van Wee bound. Codes that meet this bound will be called nearly perfect covering codes. This work studies such codes with covering radius 1. It is shown that the set of these codes can be partitioned into three families, depending on the distribution of the Hamming distances between neighboring codewords. General properties of these code families are presented, including a characterization of their weight and distance distributions. Constructions of codes for each of the families are presented. Finally, extended perfect covering codes are considered. Their punctured codes yield a variety of nearly perfect covering codes.

关键词： Education   Technological innovation   Recruitment   Particle measurements   Data collection   Atmospheric measurements   Servers   STEM   Mathematics   Information and communication technology   Academic self-efficacy   computer science (CS)   diversity   gender   sense of belonging  

摘要： Background: The motivation behind this study stems from the gender disparity observed within undergraduate CS programs. This gender gap undermines diversity within the tech industry and hampers its potential for innovation. Research Questions: Do female CS students exhibit lower levels of school belonging and academic self-efficacy? Are there gender differences in academic achievement? What is the predictive power of prior academic performance, academic self-efficacy, and sense of belonging on first-semester grades? Methodology: In this study, 113 undergraduate students (82 males) were surveyed. The questionnaire was administered midway through the semester, in early November. High school math exam scores were assessed along with self-reported measures of academic self-efficacy and sense of belonging. Findings: The findings revealed several noteworthy observations: Female students exhibited a statistically significant higher grade point average (GPA) at the end of the first semester despite reporting lower levels of academic self-efficacy. Regression analysis identified gender, academic self-efficacy, and high school math exam scores as significant predictors of first-semester GPA. Implications: The implications of the study underscore the importance of fostering a supportive learning environment within CS education. Specifically, this study advocates for implementing teaching practices that prioritize social aspects and help enhance field-specific self-efficacy for all students.

关键词： Estimation   Imputation   Training data   IP networks   Accuracy   Supervised learning   Recommender systems   Noise   Data models   Computer science   Recommender system   collaborative filtering   debias   noise-robust learning   pairwise ranking loss  

摘要： Recommender systems have been widely employed on various online platforms to improve user experience. In these systems, recommendation models are often learned from the users' historical behaviors that are automatically collected. Notably, recommender systems differ slightly from ordinary supervised learning tasks. In recommender systems, there is an exposure mechanism that decides which items could be presented to each specific user, which breaks the i.i.d assumption of supervised learning and brings biases into the recommendation models. In this paper, we focus on unbiased ranking loss weighted by inversed propensity scores (IPS), which are widely used in recommendations with implicit feedback labels. More specifically, we first highlight the fact that there is a gap between theory and practice in IPS-weighted unbiased loss. The existing pairwise loss could be theoretically unbiased by adopting an IPS weighting scheme. Unfortunately, the propensity scores are hard to estimate due to the inaccessibility of each user-item pair's true exposure status. In practical scenarios, we can only approximate the propensity scores. In this way, the theoretically unbiased loss would be still practically biased. To solve this problem, we first construct a theoretical framework to obtain a generalization upper bound of the current theoretically unbiased loss. The bound illustrates that we can ensure the theoretically unbiased loss's generalization ability if we lower its implementation loss and practical bias at the same time. To that aim, we suggest treating feedback label Y-ui as a noisy proxy for exposure result for O-ui each user-item pair (u,i). Here we assume the noise rate meets the condition that (P) over cap O-ui=1, Y-ui not equal O-ui) < 1/2. According to our analysis, this is a mild assumption that can be satisfied by many real-world applications. Based on this, we could train an accurate propensity model directly by leveraging a noise-resistant loss function. Then we c

关键词： Computational thinking   Computer science   Game design   Block-based programming   Middle school   Attitudes  

摘要： Middle school students often enter Computer Science (CS) classes without previous CS or Computational Thinking (CT) instruction. This study evaluated how ***'s block-based programming curriculum affects middle school students' CT skills and attitudes toward CT and CS. Sixteen students participated in the study. This was a mixed methods action research study that used pre- and post-tests, surveys, artifacts, and interviews as data sources. Descriptive statistics, paired samples t-tests, and inductive thematic analysis were administered. Findings showed a statistically significant increase in participants' algorithmic thinking, debugging, and pattern recognition skills but not in abstraction skills. Attitudes toward CT and CS improved but the difference was not statistically significant. Qualitative themes revealed benefits of game-based learning to promote CT skills, collaboration to promote successful error debugging, and enjoyment of programming resulting from a balance between structured guidance and creative freedom. Findings emphasize the importance of low-threshold and engaging strategies to introduce novice learners to CT and CS.

关键词： Hamming distances   Graph theory   Error correction codes   Eigenvalues and eigenfunctions   Color   Random variables   Indexes   Geometry   Computer science   Bounds on codes   expander graphs   proper colorings   sphere packing  

摘要： We introduce graphical error-correcting codes, a new notion of error-correcting codes on [q](n) where a code is a set of proper q-colorings of some fixed n-vertex graph G. We then say that a set of M proper q-colorings of G form a (G,M,d) code if any pair of colorings in the set have Hamming distance at least d. This directly generalizes typical (n,M,d) codes of q-ary strings of length n since we can take G as the empty graph on n vertices. We investigate how one-sided spectral expansion relates to the largest possible set of error-correcting colorings on a graph. For fixed (delta,lambda)is an element of[0,1]x[-1,1] and positive integer d, let f(delta,lambda,d)(n) denote the maximum M such that there exists some d-regular graph G on at most n vertices with normalized second eigenvalue at most lambda that has a (G,M,d) code. We study the growth of f as n goes to infinity. We partially characterize the regimes of (delta,lambda) where f grows exponentially or is bounded by a constant, respectively. We also prove several sharp phase transitions between these regimes.

关键词： Cloud computing   Security   Resource management   Virtual machines   Surveys   Computer science   Virtual machine monitors   Social networking (online)   Servers   Access control   Cyber threats   hypervisor vulnerability   resource utilization (RU)   secure resource management (SRM)   virtual machine (VM) vulnerability  

摘要： Secure resource management (SRM) within a cloud computing environment is a critical yet infrequently studied research topic. This article provides a comprehensive survey and comparative performance evaluation of potential cyber threat countermeasure strategies that address security challenges during cloud workload execution and resource management. Cybersecurity is explored specifically in the context of cloud resource management, with an emphasis on identifying the associated challenges. The cyber threat countermeasure methods are categorized into three classes: defensive strategies, mitigating strategies, and hybrid strategies. The existing countermeasure strategies belonging to each class are thoroughly discussed and compared. In addition to conceptual and theoretical analysis, the leading countermeasure strategies within these categories are implemented on a common platform and examined using two real-world virtual machine (VM) data traces. Based on this comprehensive study and performance evaluation, this article discusses the tradeoffs among these countermeasure strategies and their utility, providing imperative concluding remarks on the holistic study of cloud cyber threat countermeasures and SRM. Furthermore, the study suggests future methodologies that could effectively address the emerging challenges of secure cloud resource management.

关键词： Data models   Linear matrix inequalities   Noise measurement   Symmetric matrices   Stability analysis   Closed loop systems   Vectors   Numerical stability   Convergence   Computer science   Data informativity   data-driven control   model reference control (MRC)   quadratic matrix inequalities  

摘要： The objective of model reference control is to design a controller that regulates the system's behavior so as to match a specified reference model. This article investigates necessary and sufficient conditions for model reference control from a data-driven perspective, when only a set of data generated by the system is utilized to directly accomplish the matching. Noiseless and noisy data settings are both considered. Notably, all methods we propose build on the concept of data informativity and do not rely on persistently exciting data.