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关键词： Advertising   Network topology   Heuristic algorithms   Vehicles   Trajectory   Topology   Computer science   Vehicle dynamics   Wireless networks   Vehicle-to-everything   Internet of Vehicles (IoV)   advertisements dissemination   influence maximization   DQN   dynamic seed replacement  

摘要： With the development of computing and communication technology, the popularity of Vehicle-to-Everything (V2X) has promoted the research of advertising among vehicles. The problem of vehicle advertising communication is similar to the problem of Influence Maximization (IM) considered in social networks as both prioritize a set of candidate nodes as the initial seed nodes for the initial information dissemination to maximize the influence of the information in the global network. As user nodes in vehicle networks, vehicles have high mobility, which leads to the highly complex and unstable topology of vehicle networks. Therefore, we propose a practical solution to solve the problem of advertising dissemination among Intelligent Networked Vehicles (INVs). In our strategy, advertisements are first sent to a group of selected seed INVs and then spread among INVs. To encourage INVs to disseminate advertising actively, we propose an incentive scheme that combines online and offline to maximize profit. We propose a dynamic seed INVs replacement algorithm using the Deep Q-Network (DQN) algorithm to decide the update cycle of the seed INVs set. Simulation results show that the proposed strategy is superior to the existing methods in terms of delivery ratio of advertisement dissemination and expected profit of merchant.

关键词： Feature extraction   Source coding   Natural languages   Visualization   Computer science   Codes   Software systems   Prototypes   Weaving   Vectors   Software design   software comprehension   natural language processing  

摘要： Complex software systems consist of multiple overlapping design structures, such as abstractions, features, crosscutting concerns, or patterns. This is similar to how a human body has multiple interacting subsystems, such as respiratory, digestive, or circulatory. Unlike in the medical domain, software designers do not have an effective way to distinguish, visualize, comprehend, and analyze these interleaving design structures. As a result, developers often struggle through the maze of source code. In this paper, we present an Automated Concept Explanation (ACE) framework that automatically extracts and categorizes major concepts from source code based on the roles that files play in design structures and their topic frequencies. Based on these categorized concepts, ACE recovers four categories of high-level design models using different algorithms and generates a natural language explanation for each. To assess if and how ACE can help developers better understand design structures, we conducted an empirical study where two groups of graduate students were assigned three design comprehension tasks: identifying feature-related files, identifying dependencies among features, and identifying design patterns used, in an open-source project. The results reveal that the students who used ACE can accomplish these tasks much faster and more accurately, and they acknowledged the usefulness of the categorized concepts and structures, multi-type high-level model visualization, and natural language explanations.

关键词： access   capacity   computer science education   equity   policymakers  

摘要： Access to computer science education (CSEd) has greatly expanded in recent years. Starting with the Computer Science for All Initiative, launched in 2016 under President Obama, CSEd has expanded across the U.S. with over half of high schools offering at least one computer science course. Although there has been growth in computer science course offerings, disparities exist when it comes to 'who' enrolls in CSEd courses, and 'where' those courses are being offered. These disparities highlight that while funding and support for CSEd has increased, little is known about the capacity of states to operationalize (and implement) policies to achieve equitable CSEd. Furthermore, how recent changes at the federal and state level(s) are directly impacting minoritized populations' access, participation, and engagement in CSEd. This commentary focuses on the state-level capacity to implement equity-focused CSEd policies that can lead to improvements in student opportunities and outcomes. We argue that state CSEd leaders engage at the intersection of four areas: (1) growing state investment in CSEd, (2) increasingly polarizing political environments, (3) securing human and fiscal resources to implement CSEd policy with fidelity, and (4) supporting Culturally Responsive Computing that sustains equitable teaching and learning practices in schools and classrooms. This commentary also serves as a Call to Action for STEM education researchers to listen closely and carefully to the communities served by CSEd research, including students, families, and educators.

关键词： Chatbots   Education   Computer science   Databases   Accuracy   Mentoring   Information technology   Information systems   Adaptation models   Vectors   higher education   large language model (LLM)   moodle   moodlebot  

摘要： Contribution: This research explores the benefits and challenges of developing, deploying, and evaluating a large language models (LLMs) chatbot, MoodleBot, in computer science classroom settings. It highlights the potential of integrating LLMs into LMSs like Moodle to support self-regulated learning (SRL) and help-seeking behavior. Background: Computer science educators face immense challenges incorporating novel tools into LMSs to create a supportive and engaging learning environment. MoodleBot addresses this challenge by offering an interactive platform for both students and teachers. Research Questions: Despite issues like bias, hallucinations, and teachers' and educators' resistance to embracing new (AI) technologies, this research investigates two questions: (RQ1) To what extent do students accept MoodleBot as a valuable tool for learning support? (RQ2) How accurately does MoodleBot churn out responses, and how congruent are these with the established course content? Methodology: This study reviews pedagogical literature on AI-driven chatbots and adopts the retrieval-augmented generation (RAG) approach for MoodleBot's design and data processing. The technology acceptance model (TAM) evaluates user acceptance through constructs like perceived usefulness (PU) and Ease of Use. Forty-six students participated, with 30 completing the TAM questionnaire. Findings: LLM-based chatbots like MoodleBot can significantly improve the teaching and learning process. This study revealed a high accuracy rate (88%) in providing course-related assistance. Positive responses from students attest to the efficacy and applicability of AI-driven educational tools. These findings indicate that educational chatbots are suitable for integration into courses to improve personalized learning and reduce teacher administrative burden, although improvements in automated fact-checking are needed.

关键词： Computer science   Galaxies and clusters   Graphene   Machine learning  

摘要： Learning meaningful representations of images in scientific domains that are robust to variations in centroids and orientations remains an important challenge. Here we introduce centroid- and orientation-aware disentangling autoencoder (CODAE), an encoder-decoder-based neural network that learns meaningful content of objects in a latent space. Specifically, a combination of a translation- and rotation-equivariant encoder, Euler encoding and an image moment loss enables CODAE to extract features invariant to positions and orientations of objects of interest from randomly translated and rotated images. We evaluate this approach on several publicly available scientific datasets, including protein images from life sciences, four-dimensional scanning transmission electron microscopy data from material science and galaxy images from astronomy. The evaluation shows that CODAE learns centroids, orientations and their invariant features and outputs, as well as aligned reconstructions and the exact view reconstructions of the input images with high quality.

关键词： Augmented reality   Computer science   Medical education   Virtual reality   VR headset  

摘要： Objective: Although the operating theatre offers unique didactic opportunities, it can be perceived as an uncomfortable environment by medical students due to the lack of theatre etiquette, time pressure and parallel work of different disciplines. We investigated whether virtual reality (VR) training can significantly reduce some of these fears and improve surgical education for medical students. Methods: We randomly divided a group of 24 medical students and investigated the effects of a VR application (digitally recreated operating theatre tour) and compared it with currently-in-use written instructions for operational tasks in the operating theatre. The parameters analyzed in this study included timekeeping, orientation, and the error rate. Results: Medical students who received a preparational VR training for tasks in the operating theatre showed a statistically significant lower rate of getting stuck (P < 0.03), time to find the operation room (P < 0.01), correct gowning (P < 0.05) and better identification of surgical equipment (P < 0.01). The use of a digitally reconstructed operating theatre using VR led to a significant improvement in orientation and error rate in the behavior of medical students in the operating theatre. Conclusions: Routine VR use as part of clinical training could be beneficial in future medical education.

关键词： Computer science   ScratchJr   Early elementary education   Computational thinking   Evidence-based curriculum  

摘要： Background: and Context: Computer programming is increasingly being taught to young children worldwide. Quality programming curricula are needed to enable students to explore computer science concepts and develop a positive attitude towards programming. However, few studies have been conducted on the available curricula for young learners. Objective: This study aims to provide an evidence-based, public, and free computer science curriculum for early childhood education by investigating the efficacy of the CAL-ScratchJr curriculum, among second graders. Method: A cluster-randomized controlled trial involving 11 schools and 21 second-grade classrooms was conducted to examine the impact of the 24-lesson curriculum on students' coding proficiency and computational thinking. Findings: The results indicated that the CAL-ScratchJr curriculum intervention had a medium positive effect on second graders' coding skills, but no significant impact on computational thinking. Implications: Results caution against incorporating disconnected abstract computational thinking practices in education. The features of the curriculum were discussed.

关键词： Low anterior resection syndrome   Rectal cancer   Survivorship care   Bowel dysfunction   Peer support  

摘要： IntroductionLow Anterior Resection Syndrome (LARS) describes bowel dysfunction post-restorative proctectomy (RP) and is associated with poor quality of life (QoL). The aim of this study was to assess the impact of an interactive online informational and peer support App on participants' QoL (primary outcome), LARS, and emotional distress (secondary outcomes).MethodsA multicentre, randomized, parallel-group trial was conducted across five Canadian colorectal surgery practices. Adult patients who: (1) underwent RP for rectal cancer and completed all treatment and (2) had major/minor LARS were included. Participants were randomized in a 1:1 ratio to treatment or comparison group, stratified by hospital site and years post-RP. The treatment group had access to the App for a period of 6 months, and the comparison group received a booklet containing the same educational material as the App. The primary outcome was change in global QoL (EORTC-QLQ-C30) from baseline to 6 months post-intervention. Per-protocol and intention to treat analysis were performed, controlling for a priori selected variables (sex, time from end of treatment).ResultsOf the 101 enrolled participants, 10 individuals were lost to follow-up and 91 completed the study. Participants were well-balanced in terms of baseline characteristics, QoL and bowel dysfunction. Among the 45 App users, median log-in per person was 21, with 30 (66.7%) participants meeting criteria for adequate app usage. On intention to treat analysis, there was no statistically significant difference in QoL in the App group. On the per-protocol analysis, where only participants who met adequate App usage criteria were included in the treatment group, the group reported statistically significant improvement in QoL (beta 9.5, 95% CI 4.6,14.6) and LARS (beta - 2.7, 95%CI - 5.1,- 0.2) scores following App *** multicenter randomized controlled trial support that, when adequately used, an interactive online informational and